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false | 2011-01-19 17:46:39 | Coding: Spike Driven Development | [
"coding"
] | [
"Coding"
] | While reading http://dannorth.net/2011/01/15/on-craftsmanship/[Dan North's second post about software craftsmanship] I was able to resonate quite a lot with a point he made in the 'On value' section:
____
I'm not going to mandate test-driving anything (which is a huge about-face from what I was saying a year ago), unless it will help. Copy-and-paste is fine too. (Before you go all shouty at me again, hold off until I blog about the benefits of copy-and-paste, as it appears in a couple of patterns I'm calling _Spike and Stabilize_ and _Ginger Cake_. You might be surprised.)
____
I've been finding that quite frequently with some of the problems I've worked on recently that we haven't known exactly how to solve it when we started and ended up hacking/spiking the code quite a bit at that stage until we figured out what we needed to do.
Dan replied with http://twitter.com/tastapod/status/26401996319760385[the following on twitter] when I mentioned this to him:
____
@markhneedham kind of deliberately discovering the best way forward by actively reducing your ignorance? hmm, might catch on\...
____
He wrote about this a few months ago in a post titled 'http://dannorth.net/2010/08/30/introducing-deliberate-discovery/[Introducing Deliberate Discovery]'.
I nearly always feel pretty bad when I take this approach because I'm not TDDing code which easily be written using that style.
The reason I don't is that it slows me down when I'm in discovery mode.
I could TDD what I *think* the code needs to look like and end up with nice looking code which doesn't actually solve the problem but that seems to miss the point.
Another approach could be to drive from a higher level by using cucumber or a similar tool but that always ends up being quite fiddly from my experience and again it slows down the discovery that I want to make.
We had a recent example of this while trying to work out how to display the next part of a page we were working on.
Our initial approach was to make an AJAX call to the server and get back a JSON representation of our resource which we could render on the page.
While implementing this approach we realised that there were already a some post backs being made to the server from various other parts of the page which resulted in the page being refreshed.
We initially thought that this would mean that we could use the data being passed to the view on those post backs to do what we wanted.
We kept a copy of our original code and then started trying to implement what we thought would be a simpler solution.
Unfortunately after playing around with that approach for a few hours we realised that it wasn't going to work because loading the data that way led to another part of the page getting completely screwed up.
We therefore ended up back at the first approach again.
One side effect of taking that second approach was that eventually the logic got too complicated for us to verify that what we had written was correct just by eye balling it.
We therefore slowed down a bit and TDD'd the code so that we could document our understanding of what was supposed to happen.
http://cleancoder.posterous.com/software-craftsmanship-things-wars-commandmen[Uncle Bob wrote a reply] to Dan a couple of days ago in which he ends with the following:
____
So when you see someone wearing a green wrist-band that says "Clean Code" or "Test First" or "Test Obsessed" \... _It's a promise made to one's self: "I will do a good job. I will not rush. I will write tests. I will go fast by going well. I will not write crap. And I will practice, practice practice so that I can be a professional."_
____
The code I'm writing during the time when I'm discovering what I need to do certainly isn't clean or test first but it is part of an attempt to allow me to figure out what to do in order to go faster.
I'm more used to taking the approach I've described when explicitly working on 'spikes' or 'http://rethrick.tumblr.com/post/1677240946/experimenting-with-agile-at-google[experiments]' but in a way what we've done is perhaps closer to http://www.markhneedham.com/blog/2009/09/19/set-based-concurrent-engineering-a-simple-example/[concurrent set based engineering].
I think the skill I still quite haven't got right is realising when I've taken the spiking/hacking too far and would benefit from going and TDDing a bit of code but I'm sure I'll figure it out with practice. | null | null | [
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] | coding-spike-driven-development | https://markhneedham.com/blog/2011/01/19/coding-spike-driven-development |
false | 2011-01-26 18:07:07 | Deliberate Discovery: The stuff I don't know list | [
"software-development",
"deliberate-discovery"
] | [
"Software Development"
] | Towards the end of Dan North's post on http://dannorth.net/2010/08/30/introducing-deliberate-discovery/[Deliberate Discovery] he makes the following suggestion:
____
There is much more to say about deliberate discovery. Think about applying the principle to learning a new language, or picking up a new technology, or a new domain. What could you do to identify and reduce your ignorance most rapidly?
____
This reminded me a lot of what I used to do when I came across things that I didn't know how to do a few years ago.
I would write down the thing that I didn't know and then make sure that I looked up the things on my list at the end of the day and then discuss what I'd read/learnt with a colleague the next day.
More recently I've fallen into what I'd call a complacent pattern where if I find something that I don't know 100% how to do I don't go out of my way to check that I actually know how to do it now.
I have more confidence that I'll be able to work out how to do something if the need arises but I don't gain that knowledge right away.
Effectively *I've continued identifying my ignorance but haven't taken the steps to reduce it*.
Now that I've realised I'm doing this I've started writing down things that I don't know on a "Stuff I don't know list" and I'm back to spending some time each evening to run through the list and at least gain some knowledge on each item.
One problem I used to find when I did this before was that I'd start reading about one thing and then I'd notice something else that I didn't know, go off and read about that and so on until I'd forgotten what I was originally trying to learn.
To try and combat that I've been time-boxing myself with a http://www.pomodorotechnique.com/[pomodoro] while I'm working through the list and then adding any new concepts I come across to the end of the list.
Another mistake I've made/sometimes do make is reading very passively i.e. I read the information but don't really understand it.
To get around that problem I've been talking to colleagues about what I've been reading, as suggested by Andy Hunt in http://www.markhneedham.com/blog/2008/10/06/pragmatic-learning-and-thinking-book-review/[Pragmatic Thinking and Learning].
In addition I tend to remember things better if I actually get to use them in practice rather than just learning the theory.
Since the majority of the reading I've been doing lately has been around networking I've been using http://openmaniak.com/tcpdump.php[tcpdump] and http://www.wireshark.org/[wireshark] so I can see the theory in action.
Unfortunately those are another two things I don't know so I'm learning about them as I go. | null | null | [
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] | deliberate-discovery-the-stuff-i-dont-know-list | https://markhneedham.com/blog/2011/01/26/deliberate-discovery-the-stuff-i-dont-know-list |
false | 2011-01-26 18:08:09 | The Five Orders of Ignorance - Phillip G. Armour | [
"software-development"
] | [
"Software Development"
] | While trawling the comments of Dan North's 'http://dannorth.net/2010/08/30/introducing-deliberate-discovery/[Deliberate Discovery]' post I came across an interesting article written by Phillip G. Armour titled 'http://www-plan.cs.colorado.edu/diwan/3308-07/p17-armour.pdf[The Five Orders of Ignorance]'.
The main thing I took from the article is that the author uses the metaphor of *software as a 'knowledge acquisition activity'* for which he then defines five orders of ignorance that we can have in our attempts to acquire that knowledge.
These are as follows:
. *0th Order Ignorance - Lack of Ignorance* i.e. I know how to do something and can display by lack of ignorance with some sort of output
. *1st Order Ignorance - Lack of Knowledge* i.e. I don't know something but I know that I don't know how to do it and I know what I need to learn in order to be able to do it.
. *2nd Order Ignorance - Lack of Awareness* i.e. I don't know that I don't know something.
. *3rd Order Ignorance - Lack of Process* i.e. I don't know a suitability efficient way to find out I don't know that I don't know something</strong>
. *4th Order Ignorance - Meta Ignorance* i.e. I don't know about the five orders of igorance
Armour points out that the biggest problems when building any system are 2nd and 3rd order ignorance
We can reduce these types of ignorance by having people on the team who have experienced similar situations before and therefore don't have as much 'lack of awareness' as other people who haven't experienced the same situations.
On the majority of projects that I've worked on the main source of ignorance for us has often been around the politics within the organisation.
Most of the developers I work with tend to be quite straight forward in their communication which often isn't the best style of communication when working with people from another 'vendor' or from the client.
I think you do become better at dealing with these situations after you've come across them a few times although from my observations each situation has played out a little differently even if the underlying reasons for the human behaviour were the same.
A few months ago Toni wrote http://www.the-arm.com/2010/10/wanna-go-fast-reduce-your-feedback-loops/[a blog post about the way that he works at Forward] in which he describes how they don't have a need for several of the 'agile practices' often used on teams.
I've also been questioning the point of several of them as it feels like we sometimes just dogmatically follow a practice because that's what we've always done.
Thinking about it from the angle of ignorance I'm now more inclined to believe that the intention of the practices is to help us reduce our ignorance in some way:
* *Stand-up*: Helps to reduce the ignorance that people have about what others are working on and whether someone else can help us reduce our own ignorance in some way
* *Retrospective*: Helps to reduce our ignorance of how to work more effectively in a team in the context we're in
* *Writing tests*: Helps to reduce someone else's ignorance about what a piece of code is supposed to do when they come across it. Also provides protection around our ignorance of what we might break by changing code
From what I know about Forward it seems like people would have less ignorance than you might have if you were working as a consultant in a big bureaucratic organisation.
Of course the fact that they only hire very strong developers presumably also means that their technological ignorance is also reduced and it now makes more sense to me how they're able to work effectively with such a stream lined process.
I do think it still makes sense to question the practices we're using and constantly assess whether they are actually helping us to reduce our ignorance.
If not then we might as well use the time to do something else.
These are the main two things that came to mind for me while reading the article but I'm sure there are other things to be gained from it.
Armour has also written another article titled 'http://www.google.co.in/url?sa=t&source=web&cd=1&ved=0CBkQFjAA&url=http%3A%2F%2Fwww.ism-journal.com%2FITToday%2FAU1489_C01.pdf&ei=x2FATb7MNYOvrAf1j8GVAw&usg=AFQjCNH2YZIu6FjzKYVB5JqzVKqh8yDqkw&sig2=XmQQLqElPvMZ4KENKT2Ufg[The Nature of Software and the Laws of Software Process]' in which he expands on the orders of ignorance further. | null | null | [
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] | the-five-orders-of-ignorance-phillip-g-armour | https://markhneedham.com/blog/2011/01/26/the-five-orders-of-ignorance-phillip-g-armour |
false | 2011-01-21 03:46:21 | Listening to feedback mechanisms | [
"feedback"
] | [
"Feedback"
] | In http://static.mockobjects.com/labels/listening%20to%20the%20tests.html[Growing Object Oriented Software] the authors talk about the value of listening to our tests to understand potential problems with our code and I've started to notice recently that there are implicit feedback mechanisms dotted around at a higher level which we can also listen to.
A couple of examples come to mind:
== Nothing to show in the showcase
I've worked on a couple of projects where we've got to the end of the iteration and realised that we don't actually have anything tangible to show the product owner.
This tends to be because we've spent the majority of our time working on 'technical stories' which typically have no visible output.
This may be as a result of horizontal slicing of work rather than vertical slicing but what it essentially means is that the work you've done has no immediate value to anyone.
Sometimes there are technical aspects to a solution which have a lot of unknowns and combining those with a vertically sliced story would mean that the story becomes too big to fit in an iteration.
From my experience a way around this which has worked well before is to run a spike/experiment card where we work out all the technical details/gotchas and setup any necessary 'framework' and then have the other vertically sliced chunks of work plug into this.
Having said that I'm no expert in breaking down work into manageable chunks so if anyone has any other ideas I'd be interested in hearing about those.
== Boring meetings
The typical response if someone complains of http://boycottameetingday.com/[being bored in a meeting] or walks out of a meeting is that they should deal with it but that response doesn't help us that much.
I think if people are bored then it's an indication that the meeting isn't particularly interactive/inclusive or that the person shouldn't be in the meeting.
We can try to resolve that first point by having meetings which are designed more as a discussion/learning forum rather than a brain dump session by one person to the group.
This encourages more of a http://www.markhneedham.com/blog/2010/10/31/distributed-agile-context/[pull approach over a push] one and seems to be more effective at keeping people's attention as long as the topic of the discussion is actually relevant to them.
Frequently it seems that a more effective approach would be to have fewer people involved in a meeting and have one of the participants quickly summarise what happened for the rest of the team. | null | null | [
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] | listening-to-feedback-mechanisms | https://markhneedham.com/blog/2011/01/21/listening-to-feedback-mechanisms |
false | 2011-01-08 13:15:19 | Ruby: Sorting by boolean fields | [
"ruby"
] | [
"Ruby"
] | We were doing a bit of work on http://rapidftr.com/[RapidFTR] in the ThoughtWorks Pune office today and one problem my pair and I were trying to solve was how to sort a collection of objects by a boolean field.
Therefore given the following array of values:
[source,ruby]
----
form_sections = [FormSection.new(:enabled => false, :name => "a", :order => 1),
FormSection.new(:enabled => true, :name => "b", :order => 2)]
----
We wanted to display those form sections which were disabled at the bottom of the page.
We originally tried the following:
[source,ruby]
----
form_sections.sort_by { |row| [row.enabled, row.order] }
----
But got the following error:
[source,ruby]
----
undefined method `<=>' for true:TrueClass
----
We figured we'd need to convert the true and false values to equivalent values which is demonstrated on http://stackoverflow.com/questions/903877/sort-objects-by-boolean-values-in-ruby[this Stack Overflow post]:
[source,ruby]
----
form_sections.sort_by { |row| [row.enabled ? 0 : 1, row.order] }
----
I didn't realise it would be that simple to do - it's pretty neat. | null | null | [
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false | 2011-01-24 03:34:47 | Distributed Agile: Stories - Negotiable | [
"agile",
"stories"
] | [
"Agile",
"Distributed Agile"
] | I was recently reading http://www.subcide.com/articles/how-to-write-meaningful-user-stories/[an article about how to write meaningful user stories] and towards the end of it the author mentioned the INVEST acronym which suggests that stories should be:
. Independent
. Negotiable
. Valuable
. Estimable
. Small
. Testable
From what I've seen the most difficult one to achieve in a distributed context is that stories should be 'negotiable', in particular when it comes to negotiating the way that the UX of a bit of functionality should work.
On most of the projects that I've worked on the people designing the UX tend to work slightly detached from the development team and then send their designs over as wire frames.
It's not the most ideal setup even if you're working onshore but it becomes even more challenging when you're working offshore.
Typically onshore if a particular user flow was very difficult to implement then one of the developers might go and talk with the UX guys and then explain the problem and give another potential solution.
The trade off between the cost of implementation and the user experience that the UX person has suggested is clearly outlined in these conversations.
When that feedback comes from offshore it has much less impact and I think it comes across much more as a criticism of someone's work rather than an attempt to be pragmatic in helping the client to deliver a product within a time frame.
One possible solution to this problem if you have some onshore colleagues is to have them go and talk about the problem but we've found it difficult to do that because we try to split onshore/offshore stories so that we're working on different parts of the code base.
Therefore it is pretty difficult for an onshore developer to go and discuss it for you.
To add to the problem we tend to realise the difficult of implementing a certain UX during the middle of our day which means we need to wait half a day to see if we can get it changed.
Given that time lag we often just end up designing it the way that's been specified so that we don't 'waste' time.
It's clearly not an idea situation so I'd be keen to hear if anyone has come up with ideas to get around this. | null | null | [
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] | distributed-agile-stories-negotiable | https://markhneedham.com/blog/2011/01/24/distributed-agile-stories-negotiable |
false | 2011-01-24 03:33:39 | While in India: Osmotic communication | [
"communication"
] | [
"Communication"
] | One of the things that has been puzzling me during my time in India is the amount of time that is spent in meetings http://www.markhneedham.com/blog/2010/10/31/distributed-agile-context/[pushing information to people rather than them pulling it].
In previous projects that I've worked on a lot of the knowledge was moved between around as a result of http://alistair.cockburn.us/Osmotic+communication[osmotic communication]
____
Osmotic communication means that information flows into the background hearing of members of the team, so that they pick up relevant information as though by osmosis. This is normally accomplished by seating them in the same room. Then, when one person asks a question, others in the room can either tune in or tune out, contributing to the discussion or continuing with their work.
____
After thinking about it a bit more I've identified a few reasons why I think this approach doesn't work so well on my current project.
== The ability to ignore background noise
The ThoughtWorks Pune office is pretty much one big room with over 100 people in it so the amount of background noise is fairly constant.
When we've tried to run our standup near where we sit it's been impossible to hear people standing 5 or 6 metres away from you.
You therefore end up getting into the habit of blocking out anything going on around you as was evident when http://www.markhneedham.com/blog/2010/12/15/india-cultural-differences-tolerancepatience/[there was drilling] being done in the office.
The side effect of doing this, of course, is that there could be relevant discussions going on around you and you'd be much less likely to notice.
== Team size/distribution
The second problem is that the team is distributed which means that we're never going to overhear any conversations in Chicago and vice versa.
To add to this our team is now 25+ in size so it's spread out over 3 tables one of which is only within shouting distance.
Martin Fowler wrote an article about http://martinfowler.com/bliki/TeamRoom.html[team rooms] quite recently and while the ideas make sense I'm not sure how they scale as team size increases.
== Overlap of roles
Although this by no means applies to everyone that I've worked with I've noticed a tendency for people to stick to their role much more than I have in other countries.
Therefore a developer will only do 'developer tasks' and a QA will only do 'QA tasks' for example.
When you have overlap such that a developer may be 'pairing' with a QA or BA on something then the types of conversations that are head seem to lead to information moving around the team more effectively. | null | null | [
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] | while-in-india-osmotic-communication | https://markhneedham.com/blog/2011/01/24/while-in-india-osmotic-communication |
false | 2011-01-15 19:05:26 | Installing git-svn on Mac OS X | [
"software-development"
] | [
"Software Development"
] | I somehow managed to uninstall git-svn on my machine and http://blog.emmanuelbernard.com/2009/01/how-to-install-git-and-git-svn-on-mac.html[Emmanuel Bernard's blog post] suggested it could be installed using ports:
[source,text]
----
sudo port install git-core +svn
----
I tried that and was ending up with the following error:
[source,text]
----
---> Computing dependencies for git-core
---> Dependencies to be installed: p5-svn-simple subversion-perlbindings apr-util db46 cyrus-sasl2 neon serf subversion p5-term-readkey
---> Verifying checksum(s) for db46
Error: Checksum (md5) mismatch for patch.4.6.21.1
Error: Checksum (md5) mismatch for patch.4.6.21.2
Error: Checksum (md5) mismatch for patch.4.6.21.3
Error: Checksum (md5) mismatch for patch.4.6.21.4
Error: Target org.macports.checksum returned: Unable to verify file checksums
----
A bit of googling led me to the https://trac.macports.org/ticket/26075[macports website] where it was pointed out that this problem was happening in that user's case because the link to the patch now redirects to a HTML page:
____
It's actually the fact that the links pointing to those patches have become invalid. http://www.oracle.com/technology/products/berkeley-db/db/update/4.6.21/ redirects to the Berkley-DB webpage http://www.oracle.com/technetwork/database/berkeleydb/overview/index.html and you get a HTML instead of the real patch.
____
I'm not sure if that's the case for me because only the Checksum is failing, nothing is mentioned about downloading from Oracle's website.
By adapting one of the suggestions for downloading the patches manually I arrived at the following combination of commands to fix the db46 dependency:
[source,text]
----
cd /opt/local/var/macports/distfiles/db4/4.6.21_6/
sudo rm -rf patch*
for i in 1 2 3 4; do echo $i && sudo curl http://distfiles.macports.org/db4/4.6.21_6/patch.4.6.21.$i -O; done
----
Followed by:
[source,text]
----
sudo port install git-core +svn
----
And I'm back in the game! | null | null | [
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] | installing-git-svn-on-mac-os-x | https://markhneedham.com/blog/2011/01/15/installing-git-svn-on-mac-os-x |
false | 2011-01-15 18:31:07 | mount_smbfs: mount error..File exists | [
"shell-scripting-2"
] | [
"Shell Scripting"
] | I've been playing around with mounting a Windows file share onto my machine via the terminal because I'm getting bored of constantly having to go to Finder and manually mounting it each time!
After a couple of times of mounting and unmounting the drive I ended up with this error:
[source,text]
----
> mount_smbfs //mneedham@punedc02/shared punedc02_shared/
mount_smbfs: mount error: /Volumes/punedc02_shared: File exists
----
I originally thought the 'file exists' part of the message was suggesting that I'd already mounted a share on 'punedc02_shared' but calling the 'umount' command led to the following error:
[source,text]
----
> umount punedc02_shared
umount: punedc02_shared: not currently mounted
----
I had actually absent mindedly gone and mounted the drive elsewhere through Finder which I only realised after reading http://www.cmsimike.com/blog/2009/06/30/os-x-failure-mounting-via-shell/comment-page-1/#comment-7714[Victor's comments on this post].
____
Make sure that you already do not have the same share mounted on your Mac. I had //host/share already mounted in /Volumes/share, so when I tried to mount //host/share to /Volumes/newshare it gave me the "`file exists`" error.
____
I learnt, thanks to the http://www.unix.com/71392-post2.html[unix.com forums], that you can see which devices are mounted by using 'df'.
This is where Finder had mounted the drive for me:
[source,text]
----
> df
Filesystem 512-blocks Used Available Capacity Mounted on
...
//mneedham@punedc02/shared 209696376 199773696 9922680 96% /Volumes/shared
----
Since the shared drive gets unmounted when I disconnect from the network I decided to write a shell script that would set it up for me again.
[source,text]
----
#!/bin/sh
function mount_drive {
mkdir -p $2
mount_smbfs $1 $2
}
drives_to_unmount=`df | awk '/mneedham@punedc02/ { print $6 }'`
if [ "$drives_to_unmount" != "" ]; then
echo "Unmounting existing drives on punedc02: \n$drives_to_unmount"
umount $drives_to_unmount
fi
mount_drive //mneedham@punedc02/media /Volumes/punedc02_media
mount_drive //mneedham@punedc02/shared /Volumes/punedc02_shared
----
At the moment I've just put that in '/usr/bin' so that it's available on the path.
If there's a better way to do this or a way to simplify the code please let me know.
I did come across a few ways to do the mounting using Apple Script in http://hints.macworld.com/article.php?story=20020610225855377[this post] but that's not half as fun as using the shell! | null | null | [
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] | mount_smbfs-mount-error-file-exists | https://markhneedham.com/blog/2011/01/15/mount_smbfs-mount-error-file-exists |
false | 2011-01-13 20:02:49 | Chris Argyris: Espoused Theory vs Theory in Action | [
"systems-thinking-2"
] | [
"Systems Thinking"
] | Via some combination of http://twitter.com/christianralph[Christian Blunden], http://twitter.com/#!/patkua[Pat Kua], http://twitter.com/#!/dpjoyce[David Joyce] and http://twitter.com/#!/benjaminm[Benjamin Mitchell] I've been spending some time lately reading about the work of http://blog.benjaminm.net/argyris/[Chris Argyris].
I've previously come across his name while reading http://www.amazon.com/Fifth-Discipline-Practice-Learning-Organization/dp/0385517254/ref=sr_1_1?ie=UTF8&qid=1294946576&sr=8-1[The Fifth Discipline] but I didn't realise how interesting his work actually is.
One of the interesting concepts I've come across so far is the difference between http://www.scu.edu.au/schools/gcm/ar/arp/argyris.html#a_arg_intro[espoused theory and theory in use]:
Espoused theory
____
The world view and values people believe their behaviour is based on.
____
Theory-in-use
____
The world view and values implied by their behaviour, or the maps they use to take action.
____
There are two areas that really stood out for me when I read these definitions.
== Interviews
In face to face interviews the candidate is likely to give an answer based on their espoused theory of the world and hence can come across as being very good if they know the type of answers you're looking for.
I've interviewed a couple of people over the last few years where I couldn't find fault with any of the answers being given but I was convinced that they weren't giving me an accurate picture of the candidate. The answers were too perfect.
Luckily we have an opportunity to get a closer look at a candidate's theory in action in the pair programming interview that we do.
I believe http://www.hashrocket.com/[HashRocket] take this even further by having candidates pair with their team for a week before they potentially get hired.
== Knowledge vs Experience
In a recent conversation with http://twitter.com/#!/davcamer[Dave Cameron] I was telling him about the difficulties I'd been having in applying the ideas I'd read in http://www.amazon.com/Crucial-Confrontations-Resolving-promises-expectations/dp/0071446524/ref=sr_1_1?ie=UTF8&qid=1294948454&sr=8-1[Crucial Confrontations], http://www.amazon.com/Agile-Coaching-Rachel-Davies/dp/1934356433/ref=sr_1_1?s=books&ie=UTF8&qid=1294948478&sr=1-1[Agile Coaching] and http://www.amazon.com/Fearless-Change-Patterns-Introducing-Ideas/dp/0201741571/ref=sr_1_1?s=books&ie=UTF8&qid=1294948497&sr=1-1[Fearless Change].
I understand the ideas that the books are suggesting but in a real life situation I nearly always make a mistake.
Dave pointed out that this is the difference between knowledge and experience - just because you know what to do doesn't mean that you will do it unless you've had some experience of the situation before.
This sounds pretty similar to the difference between espoused theory and theory in action - I know what I want to do in a situation but at the moment that isn't what I actually do. | null | null | [
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] | chris-argyris-espoused-theory-vs-theory-in-action | https://markhneedham.com/blog/2011/01/13/chris-argyris-espoused-theory-vs-theory-in-action |
false | 2011-01-14 14:15:19 | Sed: 'sed: 1: invalid command code R' on Mac OS X | [
"shell-scripting-2"
] | [
"Shell Scripting"
] | A few days ago I wrote about how we'd been http://www.markhneedham.com/blog/2011/01/11/sed-across-multiple-files/[using Sed to edit multiple files] and while those examples were derived from what we'd been using on Ubuntu I realised that they didn't actually work on Mac OS X.
For example, the following command:
[source,text]
----
sed -i 's/require/include/' Rakefile
----
Throws this error:
[source,text]
----
sed: 1: "Rakefile": invalid command code R
----
What I hadn't realised is that on the Mac version of sed the '-i' flag has a mandatory suffix, http://hintsforums.macworld.com/showpost.php?p=393450&postcount=11[as described in this post].
The appropriate section of the man page for sed on the Mac looks like this:
____
-i extension Edit files in-place, saving backups with the specified extension. If a zero-length extension is given, no backup will be saved. It is not recommended togive a zero-length extension when in-place editing files, as you risk corruption or partial content in situations where disk space is exhausted, etc.
____
Whereas on Ubuntu the suffix is optional so we see this:
____
-i[SUFFIX], --in-place[=SUFFIX] edit files in place (makes backup if extension supplied)
____
In order to get around this we need to provide a blank suffix when using the '-i' flag on the Mac:
[source,text]
----
sed -i "" 's/require/include/' Rakefile
----
I didn't http://en.wikipedia.org/wiki/RTFM[RTFM] closely enough the first time! | null | null | [
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] | sed-sed-1-invalid-command-code-r-on-mac-os-x | https://markhneedham.com/blog/2011/01/14/sed-sed-1-invalid-command-code-r-on-mac-os-x |
false | 2011-06-04 17:24:16 | Sbt: Zipping files without their directory structure | [
"scala",
"sbt"
] | [
"Build",
"Scala"
] | We're using http://code.google.com/p/simple-build-tool/[SBT] on our project and http://twitter.com/#!/patforna[Pat] and I have been trying to work out how to zip together some artifacts so that they're all available from the top level of the zip file i.e. we don't want to copy the directory structure where the files come from.
I've been playing around with this in the Scala REPL which we can launch with our project's dependencies loaded with the following command:
[source,text]
----
./sbt console-project
----
Our original attempt to zip together the artifacts looked like this:
[source,scala]
----
FileUtilities.zip(List(("ops" / "deploy")), "dist.zip", true, log)
----
But unfortunately that keeps the directory structure which isn't what we want!
[source,text]
----
[email protected] ~/Projects/core$ unzip -l dist.zip
Archive: dist.zip
Length Date Time Name
-------- ---- ---- ----
0 06-04-11 17:52 ops/
0 06-04-11 17:52 ops/deploy/
2534 06-03-11 17:47 ops/deploy/start-server.sh
-------- -------
2534 3 files
----
Pat figured out that what we needed to do was http://code.google.com/p/simple-build-tool/wiki/Paths[make use of the ## function after our path] so our code would read like this:
[source,scala]
----
FileUtilities.zip(List(("ops" / "deploy") ##), "dist.zip", true, log)
----
Et voila:
[source,text]
----
[email protected] ~/Projects/core$ unzip -l dist.zip
Archive: dist.zip
Length Date Time Name
-------- ---- ---- ----
2534 06-03-11 17:47 start-server.sh
-------- -------
2534 1 file
----
The https://github.com/rossabaker/xsbt/blob/master/sbt/src/main/scala/sbt/Path.scala[## function is defined like so] and converts a path object into a BaseDirectory:
[source,scala]
----
override def ## : Path = new BaseDirectory(this)
----
The https://github.com/rossabaker/xsbt/blob/master/sbt/src/main/scala/sbt/FileUtilities.scala[code in FileUtilities] that generates an entry for each file in the zip file looks like this:
[source,scala]
----
def makeFileEntry(path: Path) =
{
val relativePath = path.relativePathString("/")
log.debug("\tAdding " + path + " as " + relativePath + " ...")
val e = createEntry(relativePath)
e setTime path.lastModified
e
}
def addFileEntry(path: Path)
{
val file = path.asFile
if(file.exists)
{
output putNextEntry makeFileEntry(path)
transferAndClose(new FileInputStream(file), output, log)
output.closeEntry()
}
else
log.warn("\tFile " + file + " does not exist.")
}
----
Line 179 is where the meta data is defined for the archive and it makes use of "relativePathString" which has been overriden by BaseDirectory to return "":
[source,scala]
----
private final class BaseDirectory(private[sbt] val path: Path) extends Path
{
override def ## : Path = this
override def toString = path.toString
def asFile = path.asFile
def relativePathString(separator: String) = ""
def projectRelativePathString(separator: String) = path.projectRelativePathString(separator)
private[sbt] def prependTo(s: String) = "." + sep + s
}
----
Line 176 returns the file in its original location so it can still be copied into the archive.
The problem with using an identifier like ## is that it's very difficult to Google so you end up trawling the source code for its uses or hoping that you can find the explanation for its use in the documentation! | null | null | [
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] | sbt-zipping-files-without-their-directory-structure | https://markhneedham.com/blog/2011/06/04/sbt-zipping-files-without-their-directory-structure |
false | 2011-06-20 22:36:48 | MarkLogic: Customising a result set | [
"marklogic"
] | [
"Mark Logic"
] | One of the stories we worked on last week had us needing to be able to customise the output of a MarkLogic search query to include some elements which aren't included in the default view.
We started off with this:
search.xqy
[source,text]
----
xquery version "1.0-ml";
import module namespace search = "http://marklogic.com/appservices/search" at "/MarkLogic/appservices/search/search.xqy";
declare variable $term as xs:string := xdmp:get-request-field("query", "");
search:search($term)
----
Which gives us back a list of results showing where in the documents the search term appeared.
We wanted to be able to get the title of the document and some other meta data about it though so we needed to make use of the +++<cite>+++http://developer.marklogic.com/pubs/4.1/apidocs/SearchAPI.html[transform-results]+++</cite>+++ option to do this.
The original query changes to look like this:
.search.xqy
[source,text]
----
xquery version "1.0-ml";
import module namespace search = "http://marklogic.com/appservices/search" at "/MarkLogic/appservices/search/search.xqy";
declare variable $term as xs:string := xdmp:get-request-field("query", "");
search:search($term,
<options xmlns="http://marklogic.com/appservices/search">
<transform-results apply="transformed-result" ns="http://www.markhneedham.com/search" at="transform.xqy" />
</options>)
----
And then we have another xquery file which we use to do the transformation:
.transfom.xqy
[source,text]
----
xquery version "1.0-ml";
module namespace custom-search = "http://markhneedham.com/search";
import module namespace search = "http://marklogic.com/appservices/search" at "/MarkLogic/appservices/search/search.xqy";
declare function custom-search:transformed-result(
$result as node(),
$ctsquery as schema-element(cts:query),
$options as element(search:transform-results)?
) as element(search:snippet)
{
<search:snippet>
{
(
search:snippet($result, $ctsquery, $options)/*,
<extra>{$result//*:Id}{$result//*:Title}</extra>
)
}
</search:snippet>
};
----
We put the extra elements that we wanted to include in our search result in the +++<cite>++++++<extra>+++</cite> tag but we can name that anything we want.+++</extra>++++++</cite>+++
The code snippets assume that both +++<cite>+++search.xqy+++</cite>+++ and +++<cite>+++transform.xqy+++</cite>+++ are both at the top level of the documents database. | null | null | [
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] | marklogic-customising-a-result-set | https://markhneedham.com/blog/2011/06/20/marklogic-customising-a-result-set |
false | 2011-06-18 18:45:29 | Chef, Fedora and 'ArgumentError: Attribute domain is not defined!' | [
"chef",
"fedora"
] | [
"DevOps"
] | I've been playing around with http://wiki.opscode.com/display/chef/Chef+Solo[Chef Solo] on Fedora and executing the following:
[source,text]
----
sudo chef-solo -c config/solo.rb -j config/node.json
----
(where +++<cite>+++node.json+++</cite>+++ just contains the example code from the http://wiki.opscode.com/display/chef/Chef+Solo[resolver example on the Chef documentation page] and the cookbooks folder contains https://github.com/opscode/cookbooks/tree/master[all the opscode cookbooks].)
leads to the following error:
[source,text]
----
...
ERROR: Running exception handlers
ERROR: Exception handlers complete
FATAL: Stacktrace dumped to /home/mark/chef-solo/chef-stacktrace.out
FATAL: ArgumentError: Attribute domain is not defined!
----
A bit of googling led me to believe that this error is happening because http://lists.opscode.com/sympa/arc/chef/2010-03/msg00075.html[the machine doesn't have a fully qualified domain name (fqdn) defined] which can be seen by calling the following command:
[source,text]
----
$ hostname -f
> hostname: Name of service not known
----
One way to fix it is to add the following entry to +++<cite>+++/etc/hosts</etc>+++</cite>+++
[source,text]
----
127.0.0.1 mark-fedora
----
Which results in the script running fine with no errors.
[source,text]
----
...
INFO: Running report handlers
INFO: Report handlers complete
----
A suggestion I read while googling about fqdn was to add the hostname of the machine into a file called +++<cite>+++/etc/HOSTNAME+++</cite>+++ but that didn't seem to have any impact for me.
On the Mac +++<cite>+++hostname -f+++</cite>+++ works fine even without an entry like the above in +++<cite>+++/etc/hosts+++</cite>+++ so I'm not entirely sure how it all works!
If anyone could explain it to me that'd be awesome. | null | null | [
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] | chef-fedora-and-argumenterror-attribute-domain-is-not-defined | https://markhneedham.com/blog/2011/06/18/chef-fedora-and-argumenterror-attribute-domain-is-not-defined |
false | 2011-06-18 16:08:47 | MarkLogic: Deleting all the documents in a database | [
"marklogic"
] | [
"Mark Logic"
] | We're using the http://www.marklogic.com/[MarkLogic] database on my current project and something that we wanted to do recently was delete all the documents as part of a deployment script.
Getting all of the documents is reasonably easy - we just need to make a call to the +++<cite>+++doc()+++</cite>+++ function.
We can then iterate through the documents like so:
[source,text]
----
for $doc in doc() return $doc
----
We wanted to make use of the +++<cite>+++http://docs.marklogic.com/4.2doc/docapp.xqy#search.xqy?start=1&cat=all&query=xdmp:document-delete&button=search[xdmp:document-delete]+++</cite>+++ function to tear down all of the modules but that needs a uri representing the location of the document in the database which isn't available in +++<cite>+++$doc+++</cite>+++:
____
.xdmp:document-delete
*xdmp:document-delete*( $uri as xs:string ) as empty-sequence() Summary: Deletes a document from the database.
____
A colleague pointed out that what we needed to do was pass the document to +++<cite>+++http://docs.marklogic.com/4.2doc/docapp.xqy#search.xqy?start=1&cat=all&query=xdmp:node-uri&button=search[xdmp:node-uri]+++</cite>+++ and then our troubles would be over!
The final solution therefore looks like this:
[source,text]
----
for $doc in doc() return xdmp:document-delete(xdmp:node-uri($doc))
----
I was expecting that we would delete the documents by some sort of identifier but I guess this approach makes more sense given the way the data is stored.
It all seems a bit esoteric at the moment! | null | null | [
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] | marklogic-deleting-all-the-documents-in-a-database | https://markhneedham.com/blog/2011/06/18/marklogic-deleting-all-the-documents-in-a-database |
false | 2011-06-27 23:21:56 | Scala: Self type annotations and structured types | [
"scala"
] | [
"Scala"
] | A few days ago I http://twitter.com/markhneedham/status/84025938903437312[tweeted that I didn't really see the point in structured types in Scala]...
____
Not sure I understand where you would use structural types in #scala instead of defining a method on a trait http://bit.ly/jgiW7b
____
...but today my colleague Uday came up with a cool way of combining http://programming-scala.labs.oreilly.com/ch12.html#SelfTypeAnnotations[self type annotations] with structured types inside a trait we defined.
We had some code duplicated across two classes which looked roughly like this:
[source,scala]
----
class OnePageType {
lazy val peopleNodes = root \\ "SomeNode" \ "SomeSubNode" \ "People" \ "Person"
private def fullName(personName: Node): String = // code to build person's name
lazy val people: String = peopleNodes.map(fullName).mkString(", ")
}
----
[source,scala]
----
class AnotherPageType {
lazy val peopleNodes = root \\ "OtherNode" \ "OtherSubNode" \ "People" \ "Person"
private def fullName(personName: Node): String = // code to build person's name
lazy val people: String = peopleNodes.map(fullName).mkString(", ")
}
----
The first line is different but the other two are identical because the data is stored in exactly the same format once we get down to that level.
Since We want to keep the XPathish queries as descriptive as possible so that we don't accidentally end up pulling the wrong elements onto the page, making those a bit looser wasn't an option in this case.
Instead we pulled out a trait like so:
[source,scala]
----
trait People {
self: {val peopleNodes: NodeSeq} =>
private def fullName(personName: Node): String = // code to build person's name
lazy val people: String = peopleNodes.map(fullName).mkString(", ")
}
----
Which we include in the classes like this:
[source,scala]
----
class OnePageType extends People {}
class AnotherPageType extends People {}
----
What we're done on line 2 of the +++<cite>+++People+++</cite>+++ trait is to define a self annotation which says that we need a val of +++<cite>+++peopleNodes+++</cite>+++ to be present on the classes in which the trait is mixed.
If a val of +++<cite>+++peopleNodes+++</cite>+++ doesn't exist then the class won't compile!
In this case the structure type works quite well because we wouldn't really want to pull out +++<cite>+++peopleNodes+++</cite>+++ into a trait just to reference it as a self type annotation. | null | null | [
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] | scala-self-type-annotations-and-structured-types | https://markhneedham.com/blog/2011/06/27/scala-self-type-annotations-and-structured-types |
false | 2011-06-16 07:27:15 | Fedora: Recovering from the IntelliJ 'Ctrl-Alt-F7' | [
"software-development"
] | [
"Software Development"
] | We're using Fedora on our local developer work stations and some of the default key bindings of the operating system seem to conflict with ones provided by IntelliJ IDEA.
One particular amusing one is 'Ctrl-Alt-F7' which you use in IntelliJ to see the usages of a piece of code.
In Fedora that seems to switch into a different X Server session and you just see a blank screen with seemingly no way out!
Pressing 'Ctrl-Alt-F1' helps us get back to our original session again.
'''
I'm no expert of all things Unix so if I've described anything incorrectly feel free to point it out in the comments. | null | null | [
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] | fedora-recovering-from-the-intellij-ctrl-alt-f7 | https://markhneedham.com/blog/2011/06/16/fedora-recovering-from-the-intellij-ctrl-alt-f7 |
false | 2011-06-28 22:09:18 | Git: Deleting a remote branch on a gitolite configured repository | [
"git"
] | [
"Version Control"
] | We've had an https://github.com/harrah/xsbt[xsbt] branch on our https://github.com/sitaramc/gitolite[gitolite] powered repository for the last couple of weeks while we worked out how to move our build from sbt 0.7 to sbt 0.10 but having finally done that we needed to delete it.
I originally tried running the following command from one of our developer workstations:
[source,text]
----
git push origin :xsbt
----
But ended up with the following error:
____
remote: error: denying ref deletion for regs/head/xsbt ! [remote rejected] xsbt (deletion prohibited)
____
A bit of googling led me to http://stackoverflow.com/questions/5723511/how-do-i-remove-a-remote-branch-when-i-get-an-error[this stackoverflow thread] which suggested that you needed to be an administrator in order to delete a remote branch.
Once we've done that we can run the following command on each machine to delete the remote tracking reference to the repository:
[source,text]
----
git branch -d -r origin/xsbt
---- | null | null | [
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] | git-deleting-a-remote-branch-on-a-gitolite-configured-repository | https://markhneedham.com/blog/2011/06/28/git-deleting-a-remote-branch-on-a-gitolite-configured-repository |
false | 2011-06-10 00:16:05 | Sbt: Rolling with continuous/incremental compilation and Jetty | [
"sbt"
] | [
"Build",
"Scala"
] | As I mentioned http://www.markhneedham.com/blog/2011/06/04/sbt-zipping-files-without-their-directory-structure/[in an earlier post] we're using SBT on our project and one of it's cool features is that it will listen to the source directory and then automatically recompile the code when it detects file changes.
We've also installed the https://github.com/glenford/sbt-jetty-embed[sbt-jetty-embed] plugin which allows us to create a war which has Jetty embedded so that we can http://patforna.blogspot.com/2011/04/containerless.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+patforna+%28Patric+Fornasier%27s+Blog%29[keep our application containerless].
That plugin adds an action called 'jetty' to sbt so we (foolishly in hindsight) thought that we would be able to launch the application in triggered execution mode by making use of a ~ in front of that:
[source,text]
----
$ ./sbt
> ~jetty
----
Unfortunately that doesn't do any continuous compilation which left us quite confused until we realised that http://code.google.com/p/simple-build-tool/wiki/TriggeredExecution[RTFM] might be a good idea...
What we actually needed to launch the application locally and edit code/see changes as if it's written in a dynamic language was the following:
[source,text]
----
$ ./sbt
> jetty-run
> ~ prepare-webapp
---- | null | null | [
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] | sbt-rolling-with-continuousincremental-compilation-and-jetty | https://markhneedham.com/blog/2011/06/10/sbt-rolling-with-continuousincremental-compilation-and-jetty |
false | 2011-06-26 17:05:07 | Bounded Rationality | [
"systems-thinking-2"
] | [
"Systems Thinking"
] | In http://www.amazon.co.uk/Thinking-Systems-Primer-ebook/dp/B001OC6NS6/ref=sr_1_2?ie=UTF8&qid=1309103523&sr=8-2[Thinking In Systems: A Primer]' one of the most interesting ideas that Donella Meadows describes is what Herbert Simon coined http://en.wikipedia.org/wiki/Bounded_rationality[bounded rationality]:
____
Bounded rationality means that people make quite reasonable decisions based on the information they have. But they don't have perfect information, especially about more distant parts of the system
____
Later on in the chapter the following idea is suggested:
____
If you become a manager, you probably will stop seeing labour as a deserving partner in production, and start seeing it as a cost to be minimised.
____
This helps explains something that I've noticed happen quite frequently.
Someone who was previously non management gets pulled into a management position and 'mysteriously' starts acting exactly like all the others in that type of role rather than having a holistic view.
The strange thing is that we don't expect this to happen. The person was on 'our' side very recently so surely they should be able to see both perspectives!
Esther Derby referred to this problem in http://www.markhneedham.com/blog/2011/05/13/xp-2011-esther-derby-still-no-silver-bullets/[her keynote at XP2011] where she talked about two different types of information that occur in a system:
* Day to day information - this is possessed by people 'on the ground'
* System information - this is possessed by people 'in management'
When the people who recently moved into a management position are challenged on this they will often point out that "you can't see the bigger picture" which is true but still doesn't account for the fact that they probably aren't seeing it either!
We're both just seeing different parts of the system.
Meadows goes on to point out that the design of the system tends to encourage this type of behaviour:
____
Seeing how individual decisions are rational within the bounds of the information available does not provide an excuse for narrow-minded behaviour. It provides an understanding of why that behaviour arises. Taking out one individual from a position of bounded rationality and putting in another person is not likely to make much difference. Blaming the individual rarely helps create a more desirable outcome.
____
Meadows finishes this section of the book with the following suggestion which I think is especially useful in a consulting environment where both consultants and management quite obviously tend to suffer from bounded rationality.
____
It's amazing how quickly and easily behaviour changes can come, with even slight enlargement of bounded rationality, by providing better, more complete, timelier information.
____
I've seen various attempts at trying to help people enlarge their bounded rationality at ThoughtWorks, such as:
* Presentations by the finance director showing where the revenue of the company gets spent
* Management team members taking the time to have one on one discussions with consultants
* Discussions about the sales pipeline and the types of work available in the market
I think if this type of thing happened more frequently then you'd probably see an enlargement of everyone's bounded rationality which would be useful for all involved! | null | null | [
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] | bounded-rationality | https://markhneedham.com/blog/2011/06/26/bounded-rationality |
false | 2011-06-26 13:58:10 | Coding: Light weight wrapper vs serialisation/deserialisation | [
"coding"
] | [
"Coding"
] | image::{{<siteurl>}}/uploads/2011/06/WrapperObjects.jpg[WrapperObjects,231]
As I've http://www.markhneedham.com/blog/2011/06/18/marklogic-deleting-all-the-documents-in-a-database/[mentioned] http://www.markhneedham.com/blog/2011/06/20/marklogic-customising-a-result-set/[before], we're making use of a MarkLogic database on the project I'm working on which means that we're getting quite big XML data structures coming into our application whenever we execute a query.
The normal way that I've seen for dealing with external systems would be to create an http://www.markhneedham.com/blog/2009/07/07/domain-driven-design-anti-corruption-layer/[anti corruption layer] where we initialise objects in our system with the required data from the external system.
In this case we've decided that approach doesn't seem to make as much sense because we don't need to do that much with the data that we get back.
We effectively map straight into a http://codebetter.com/gregyoung/2010/02/15/cqrs-is-more-work-because-of-the-read-model/[read model] where the only logic is some formatting for how the data will be displayed on the page.
The read model objects look a bit like this:
[source,scala]
----
class Content(root : xml.Node) {
def numberOfResults: Int = (root \ "@count").text.toInt
}
----
They are just lightweight wrapper objects and we make use of Scala's XML support to retrieve the various bits of content onto the page.
The advantage of doing things this way is that it means we have less code to write than we would with the serialisation/deserialisation approach although it does mean that we're strongly coupled to the data format that our storage mechanism uses.
However, since this is one bit of the architecture which is not going to change it seems to makes sense to accept the leakage of that layer.
So far the approach seems to be working out fine but it'll be interesting to see how well it holds up if those lightweight wrappers do end up needing to have more logic in them. | null | null | [
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] | coding-light-weight-wrapper-vs-serialisationdeserialisation | https://markhneedham.com/blog/2011/06/26/coding-light-weight-wrapper-vs-serialisationdeserialisation |
false | 2011-06-09 23:10:23 | IntelliJ: Adding resources with unusual extensions onto the classpath | [
"intellij"
] | [
"Software Development"
] | We're making use of http://www.marklogic.com/[MarkLogic] and therefore http://www.w3schools.com/xquery/default.asp[xquery] on the project I'm currently working on and recently wanted to add our xquery setup files onto the classpath so they could be used in a test.
We added them into 'src/main/resources' and set that as a source path in IntelliJ assuming that was all we needed to do.
Despite doing that our test kept failing because it couldn't locate the files on the classpath.
http://www.linkedin.com/profile/view?id=8818047&authType=name&authToken=w9yv&locale=en_US&pvs=pp&trk=ppro_viewmore[Charles] eventually came across the compiler resource patterns settings which are accessible from the Preferences > Compiler menu:
image::{{<siteurl>}}/uploads/2011/06/intellij.jpg[Intellij,434]
We had to add "*.xqy" to the end of the list of patterns to get our files picked up.
We came across another file extension that we needed to be on the classpath about 10 minutes later and obviously solved it much quicker that time! | null | null | [
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] | intellij-adding-resources-with-unusual-extensions-onto-the-classpath | https://markhneedham.com/blog/2011/06/09/intellij-adding-resources-with-unusual-extensions-onto-the-classpath |
false | 2011-06-12 16:03:30 | Scala: Setting a default value | [
"scala"
] | [
"Scala"
] | We wanted to try and generate a build label to use for the name of the artifacts archive that gets generated each time we run the build but wanted to default it to a hard coded value if the system property representing the build label wasn't available.
In Ruby we would be able to do something like this:
[source,ruby]
----
buildLabel = ENV["GO_PIPELINE_LABEL"] || "LOCAL"
----
There isn't a function in Scala that does that so we initially ended up with this:
[source,scala]
----
def buildLabel() = [{
System.getenv("GO_PIPELINE_LABEL") match {
case null => "LOCAL"
case label => label
}
}
----
My colleague http://twitter.com/#!/mushtaqA[Mushtaq] suggested passing the initial value into an Option like so...
[source,scala]
----
def buildLabel() = {
Option(System.getenv("GO_PIPELINE_LABEL")).getOrElse("LOCAL")
}
----
...which I think is pretty neat!
I tried to see what the definition of an operator to do it the Ruby way would look like and ended up with the following:
[source,scala]
----
class RichAny[A](value:A ) {
def || (default:A ) = { Option(value).getOrElse(default) }
}
----
[source,scala]
----
implicit def any2RichAny[A <: AnyRef](x: A) = new RichAny(x)
----
Which we can use like so:
[source,scala]
----
def buildLabel() = {
System.getenv("GO_PIPELINE_LABEL") || "LABEL"
}
----
I imagine that's probably not the idiomatic Scala way to do it so I'd be curious to know what is. | null | null | [
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] | scala-setting-a-default-value | https://markhneedham.com/blog/2011/06/12/scala-setting-a-default-value |
false | 2011-06-13 23:02:57 | Parkinson's Law and Iteration Zero | [
"software-development"
] | [
"Agile"
] | I've been thinking a bit about http://en.wikipedia.org/wiki/Parkinson's_Law[Parkinson's Law] recently and its' applicability in software development.
Parkinson's law is defined as follows:
____
Parkinson's Law is the adage first articulated by Cyril Northcote Parkinson as the first sentence of a humorous essay published in The Economist in 1955: "`Work expands so as to fill the time available for its completion`"
____
My colleagues quite frequently reference this law with respect to stories taking the amount of time that reflects the story point estimate assigned to them.
I haven't noticed this so much but I think we're more susceptible to the law when what we're working on doesn't have a clear goal or doesn't have a fast feedback loop.
One of the times where I think we run into this problem is in the agile 'iteration zero'.
Iteration Zero is an iteration reserved at the start of a project for setting up project infrastructure, building a walking skeleton and other such tasks. It's typically a week long.
While I think it's useful to do some up front work like this what I've noticed having participated in several of these is that we probably don't need a week for this type of work even though it will easily fill a week if it needs to.
Despite my belief that the work fills the time it's interesting to notice that we still don't get everything perfectly setup in iteration zero and probably wouldn't even if it was 2 weeks long instead.
We need to actually start driving some user functionality end to end and getting it deployed across our environments so that we can get proper feedback on the work that we've done.
For example one of the tasks of an iteration zero might be to have all the developer work stations ready to go by the time we start.
It's certainly possible to get the work stations to a stage where we think we've got everything setup correctly but it's not until people are actually using them that we know for sure.
The idea of an iteration zero is still useful but we should try to keep it as short as possible and accept that we're still going to be learning/spending time in the first few iterations on iteration zero type stuff and expect a 'slower velocity' accordingly. | null | null | [
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] | parkinsons-law-and-iteration-zero | https://markhneedham.com/blog/2011/06/13/parkinsons-law-and-iteration-zero |
false | 2011-06-22 21:24:06 | Scala/Mustache: Creating a comma separated list | [
"scala",
"mustache"
] | [
"Scala"
] | We're using the http://scalate.fusesource.org/documentation/mustache.html[Mustache] templating engine on my project at the moment and one thing that we wanted to do was build a comma separated list.
Mustache is designed so that you pretty much can't do any logic in the template which made it really difficult to do what we wanted.
It's easy enough to get a comma after each item in a list with something like the following code:
[source,text]
----
{{#people}}<a href="/link/to/{{toString}}">{{toString}}</a>{{/people}}
----
where +++<cite>+++people+++</cite>+++ is passed to the template as a collection of strings.
To get rid of the trailing comma we ended up building a collection of +++<cite>+++Pairs+++</cite>+++ containing the person's name and a boolean value indicating whether or not to show the comma.
We need to show the comma before every element except for the first one so we can pass the following collection to the template:
[source,scala]
----
val values = names.zipWithIndex.map { case(item, index) => if(index == 0) (item, false) else (item, true) }
----
+++<cite>+++zipWithIndex+++</cite>+++ returns a collection of pairs containing the original strings and their position in the collection.
We can then map to a different result for just the first element and then use those pairs in the template like so:
[source,text]
----
{{#people}} {{#_2}}, {{/_2}}<a href="/link/to/{{_1}}">{{_1}}</a>{{/people}}
----
It's truly horrendous so if anyone knows a better way then please let me know! | null | null | [
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] | scalamustache-creating-a-comma-separated-list | https://markhneedham.com/blog/2011/06/22/scalamustache-creating-a-comma-separated-list |
false | 2011-06-22 23:48:08 | Tech Leading: Keeping the passion | [
"tech-leading"
] | [
"Software Development"
] | As I http://www.markhneedham.com/blog/2011/04/17/tech-leading-initial-thoughts/[mentioned a couple of months ago], while I was in India I was acting as the Tech Lead on the project the TWU grads were working on and one thing I learnt from doing that is the importance of trying to keep the passion of the developers on the team.
When we started off I was more focused on trying to encourage the team to try and develop as many of the stories as possible.
This meant that on one occasion when one of the developers was really keen to try something out which he thought would make our life easier I overruled him in favour of working on a story that more directly contributed to what we were trying to do.
Luckily he didn't get dissuaded by me doing that and a few days later he again asked if he could explore that avenue as he was convinced it would be useful.
We decided that it would be worth trying for the rest of the day and it was noticeable that he was significantly more pumped up/enthusiastic on most things that he worked on after that.
I appreciate that I was in an unusual situation where the output of the project came second to the learning of the participants but I still feel like there is something to be said for helping encourage and keep the passion of people on our teams.
It will mean sacrificing a bit of short term productivity, but if it means that the person has satisfied their curiosity about the viability of a bit of technology or even better has solved a problem for the team by doing so then it might be worth it.
As I found out it's much easier to knock someone back and you have justification to do so because what they want to do isn't directly on the value path of what's being paid for but that might not be the best decision if you look at the whole!
I'd be curious to hear the opinions of people who have played the tech lead role frequently because my observations are only based on a short stint and from being on the other side of the equation! | null | null | [
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] | tech-leading-keeping-the-passion | https://markhneedham.com/blog/2011/06/22/tech-leading-keeping-the-passion |
false | 2011-06-22 23:04:44 | Scala: val, lazy val and def | [
"scala"
] | [
"Scala"
] | We have a variety of +++<cite>+++val+++</cite>+++, </cite>lazy val</cite> and +++<cite>+++def+++</cite>+++ definitions across our code base but have been led to believe that idiomatic Scala would have us using +++<cite>+++lazy val+++</cite>+++ as frequently as possible.
As far as I understand so far this is what the different things do:
* +++<cite>+++val+++</cite>+++ evaluates as soon as you initialise the object and stores the result.
* +++<cite>+++lazy+++</cite>+++ val evaluates the first time that it's accessed and stores the result.
* +++<cite>+++def+++</cite>+++ executes the piece of code every time - pretty much like a Java method would.
In Java, C# or Ruby I would definitely favour the 3rd option because it http://www.markhneedham.com/blog/2009/09/02/coding-reduce-fields-delay-calculations/[reduces the amount of state that an object has to hold].
I'm not sure that having that state matters so much in Scala because all the default data structures we use are immutable so you can't do any harm by having access to them.
I recently read http://www.codequarterly.com/2011/rich-hickey/[an interesting quote from Rich Hickey] which seems applicable here:
____
To the extent the data is immutable, there is little harm that can come of providing access, other than that someone could come to depend upon something that might change. Well, okay, people do that all the time in real life, and when things change, they adapt.
____
If the data was mutable then it would be possible to change it from any other place in the class which would make it difficult to reason about the object because the data might be in an unexpected state.
If we define something as a +++<cite>+++val+++</cite>+++ in Scala then it's not even possible to change the reference to that value so it doesn't seem problematic.
Perhaps I just require a bit of a mind shift to not worry so much about state if it's immutable.
It's only been a few weeks so I'd be interested to hear the opinions of more seasoned Scala users.
'''
I've read that there are various performance gains to be had from making use of +++<cite>+++lazy val+++</cite>+++ or +++<cite>+++def+++</cite>+++ depending on the usage of the properties but that would seem to be a premature optimisation so we haven't been considering it so far. | null | null | [
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] | scala-val-lazy-val-and-def | https://markhneedham.com/blog/2011/06/22/scala-val-lazy-val-and-def |
false | 2011-12-05 23:13:34 | Continuous Delivery: Removing manual scenarios | [
"continuous-delivery"
] | [
"Software Development"
] | On the project that I'm currently working on we're trying to move to the stage where we'd be able to deploy multiple times a week while still having a reasonable degree of confidence that the application still works.
One of the (perhaps obvious) things that we've had to do as a result of wanting to do this is *reduce the number of manual scenarios* that our QAs need to run through.
At the moment it takes a few hours of manual testing time on top of all our automated scenarios before we can put the application in production which is fine if you release infrequently but doesn't really scale.
Following the ideas of http://www.markhneedham.com/blog/2011/08/21/pain-driven-development/[pain driven development] we delayed automating any bits of the application if we couldn't work out how to automate them easily.
For example we have quite a few Javascript driven light boxes which pop up on various users actions and we weren't able to test using the HTML Unit Driver in http://code.google.com/p/selenium/[Web Driver] so we created automated tests only for the non Javascript version of those features.
We've started work on automating these scenarios recently and although we're having to invest some time in fiddling around with the Firefox Driver to do so, it will save us time on each deployment so it should be worth it.
My colleague http://www.linkedin.com/pub/harinee-muralinath/13/157/531[Harinee] showed me an interesting post by Anand Bagmar in which he describes http://essenceoftesting.blogspot.com/2011/08/to-test-or-not-to-test-do-you-ask.html[a cost/value matrix which can help us decide whether or not to automate something].
In this case the lightbox feature was initially only used in a couple of places and we realised it would be quite difficult to test it compared to our current approach so it fitted in the 'Naaaah' section (Low value, High cost).
Over time it has been introduced in more and more places so it's become more important that we find a way to automatically test it since the application can fail in many more places if it doesn't work.
It's therefore moved into section #2 (High value, High cost) and become a candidate for automation.
Although not directly related to manual scenarios, one thing we haven't quite worked out yet is what the balance should be between getting something into production and ensuring that it isn't full of bugs.
This is also something which James Birchler addresses in http://engineering.imvu.com/2010/04/09/imvus-approach-to-integrating-quality-assurance-with-continuous-deployment/[his post about IMVU's approach to continuous deployment]:
____
We're definitely not perfect: with constrained QA resources and a persistent drive by the team to deliver value to customers quickly, we do often ship bugs into production or deliver features that are imperfect. The great thing is that we know right away what our customers want us to do about it, and we keep on iterating.
____
At the moment the application is only being beta tested by a small number of users so we're veering towards pushing something even if it's not perfect but as we open it up to more people I imagine it'll become a bit more stringent.
At times it's quite painful working out what you need to change in your approach to make it possible to release frequently but it's cool to see the progress we're making as we get better at doing so. | null | null | [
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] | continuous-delivery-removing-manual-scenarios | https://markhneedham.com/blog/2011/12/05/continuous-delivery-removing-manual-scenarios |
false | 2011-12-20 23:57:51 | The supposed black box | [
"software-development"
] | [
"Software Development"
] | On a reasonable number of the systems that I've worked on over the past few years there's been a 'black box' component which the team I've been on has needed to integrate with.
I've always found it a little strange that you wouldn't need to/want to know how that part of the system worked or that you could actually believe that it was truly a black box.
If it doesn't work then you have no way of diagnosing the problem - did you do something wrong, was there something wrong inside the black box or was it something else.
On a project I worked on a few years ago the reason for the black box thinking was that http://www.markhneedham.com/blog/2009/04/14/lean-big-picture-over-local-optimisations/[each layer was being developed by people from a different company].
The problem we had was that we were working on the top layer, the one that was visible to the end user and therefore our progress was very visible to the stakeholders who were paying for the product to be built.
We therefore had no choice but to go into the metaphorical black box and try and gather as much information as we could to pass on to the teams working on the other layers so that they would be able to help us better.
I recently watched a talk by Artur Bergman titled 'http://www.youtube.com/watch?v=oebqlzblfyo[Full Stack Awareness]' where he talks about the necessity of understanding exactly what is happening when our code gets executed rather than thinking of it as magic.
Although Artur is working in a different context to most application developers who maybe don't need to know the stack as well as he does I think the advice about treating something as magic is useful.
If we think of something as a 'black box' then effectively we are saying that it's somewhat magic.
If the integrated component is being custom written then I think the team who needs to integrate with it should at the very least have someone who knows how it works very well so they can diagnose any problems quickly.
That person then needs to spread their knowledge amongst the rest of the team so that they don't end up being the bottle neck.
In summary I think the term 'black box' is frequently a misnomer and we'll rarely be able to view said black box in such an opaque way. | null | null | [
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] | the-supposed-black-box | https://markhneedham.com/blog/2011/12/20/the-supposed-black-box |
false | 2011-12-18 21:00:04 | The Lean Startup: Book Review | [
"lean-startup",
"books",
"book-review"
] | [
"Books"
] | I'd heard about http://www.amazon.co.uk/Lean-Startup-Innovation-Successful-Businesses/dp/0670921602/ref=sr_1_1?ie=UTF8&qid=1324224276&sr=8-1[The Lean Startup] for a long time before I actually read it, mainly from following the 'http://www.startuplessonslearned.com/[Startup Lessons Learned]' blog, but I didn't get the book until a colleague suggested a meetup to discuss how we might apply the ideas on our projects.
My general learning from the book is that we need to take the idea of *creating tight feedback loops*, which we've learnt in the agile/lean worlds, and apply it to product development.
Eric Ries talks about the ideas of the *Minimum Viable Product* (MVP), which is something that I've heard mentioned a lot in the last few projects I've worked on so I thought I knew what it meant.
I'd always considered the MVP to effectively be the first release of any product you were building but Ries' frames it as the minimum product you can release to get feedback on whether your idea is viable or not. For example Dropbox's MVP was a video demonstrating how it would work when the team had written the code to sync files on all operating systems.
On a lot of the projects that I've worked on we start after the point at which the business has decided what their product vision is and we're responsible for implementing it. They haven't necessarily then gone on to make a big return from building the product which I always found strange.
The most frequent argument I've heard against releasing an 'incomplete' product early in the organisations that I've worked for is that it could ruin their brand if they took this approach. One suggestion the book makes is to release the product under a spin off subsidiary if we're worried about that.
The book also discussed the ways that we need to treat early adopters of a product and mainstream customers differently.
For example *early adopters won't mind/may actually prefer to play with an unfinished product* if they can help influence its future direction.
By the time we have proved that we have a viable product and are looking to aim it at the mainstream market it will need to be more feature complete and polished in order to please that crowd. </li>
There is a big focus on making *data driven decisions* such that we gather metrics showing how our product is actually being used by customers rather than just guessing/going on intuition as to what we should be doing next.
Facebook http://www.facebook.com/video/video.php?v=10100259101684977[released an interesting video] where towards the end they describe the metrics which they have around their application such that *they can tell whether a deployment is losing them money* and therefore needs to be rolled back.
One particular thing that the book talks about is http://52weeksofux.com/post/646711369/cohort-analysis-measuring-engagement-over-time[cohort analysis]:
____
A cohort analysis is a tool that helps measure user engagement over time. It helps UX designers know whether user engagement is actually getting better over time or is only appearing to improve because of growth.
____
We tend to use metrics to help us see the quality of code and which things we might want to work on there but I think the idea of using it to measure user engagement is really cool and should help us to build a more useful product.</li>
I especially enjoyed the parts of the book where Ries talks about ways that some of the ideas have been applied with startups which are doing well at the moment although I think it'd be fair to say that the lean startup framework has been retrospectively fitted to explain these stories.
I think the danger of thinking that they were following lean startup principles is that it can lead to us not thinking through problems ourselves which I guess is the same problem with any framework/methodology.
I'm intrigued as to whether it will make a difference to the overall success rate of startups or not if they follow the ideas from the book.
I imagine we'll see some ideas failing much more quickly than they might have otherwise and the suggestion is that when this happens we need to+++<strong>+++pivot and try and find another approach that will make money+++</strong>+++. Despite that, there there will come a point when the startup runs out of money without finding a way to monetise their product and it'll be game over.
Overall the book is quite easy reading and worth a flick through as it has some cool ideas which can help us to spend less time building products which don't actually get used. | null | null | [
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] | the-lean-startup-book-review | https://markhneedham.com/blog/2011/12/18/the-lean-startup-book-review |
false | 2011-12-27 23:53:56 | Learning Android: WebView character encoding | [
"android"
] | [
"Android"
] | In my continued attempts to learn how to write an Android application I came across a problem with character encoding when trying to load some text into a http://developer.android.com/reference/android/webkit/WebView.html[WebView].
I was initially trying to write the text to the WebView like this:
[source,java]
----
WebView webview = new WebView(collection.getContext());
webview.loadData(textWithQuotesIn, "text/html", "UTF-8");
----
image::{{<siteurl>}}/uploads/2011/12/android-before-after1.gif[Android before after,555]
But ended up with the output in the picture on the left hand side. I tried playing around with the encoding and debugged the application all the way through until it hit the WebView but there didn't seem to be any problem with the text.
I eventually http://stackoverflow.com/questions/7412763/string-encoding-problem-in-webview[came across a post on StackOverflow] where +++<cite>+++mice+++</cite>+++ suggested using one of the other methods available for writing to a WebView.
I changed my code to read like this:
[source,java]
----
WebView webview = new WebView(collection.getContext());
webview.loadDataWithBaseURL(url, textWithQuotesIn, "text/html", "UTF-8", url);
----
And now the single quotes are rendering correctly as can be seen on the image on the right.
I had a quick look at the Android source code to see if there was any obvious reason why one of the methods would work and the other wouldn't but I couldn't see anything.
Perhaps I'm doing something wrong with my call to 'loadData' and that's why it's not rendering the character set correctly. If that's the case please let me know. | null | null | [
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] | learning-android-webview-character-encoding | https://markhneedham.com/blog/2011/12/27/learning-android-webview-character-encoding |
false | 2011-12-27 12:48:17 | Leiningen: Using goose via a local Maven repository | [
"clojure",
"goose",
"leiningen"
] | [
"Clojure"
] | I've been playing around a little bit with https://github.com/jiminoc/goose[goose] - a HTML content/article extractor - originally in Java but later in clojure where I needed to work out how to include goose and all its dependencies via https://github.com/technomancy/leiningen[Leiningen].
goose isn't included in a Maven repository so I needed to create a local repository, something which I've got stuck on in the past.
Luckily http://www.pgrs.net/2011/10/30/using-local-jars-with-leiningen/[Paul Gross has written a cool blog post] explaining how his team got past this problem.
Following the instructions from Paul's post this is how I got goose playing nicely with clojure:
Inside my clojure project:
[source,text]
----
/Users/mneedham/github/android/text-extraction $ mkdir maven_repository
----
I then ran the following command from where I had goose checked out on my machine:
[source,text]
----
mvn install:install-file -Dfile=target/goose-2.1.6.jar -DartifactId=goose -Dversion=2.1.6 -DgroupId=goose -Dpackaging=jar -DlocalRepositoryPath=/Users/mneedham/github/android/text-extraction/maven_repository -DpomFile=pom.xml
----
I added the repository and goose dependency to my project.clj file which now looks like this:
[source,text]
----
(defproject textextraction "0.1.0"
:description "Extract text from urls"
:dependencies [[org.clojure/clojure "1.2.0"],
[org.clojure/clojure-contrib "1.2.0"],
[ring/ring-jetty-adapter "0.3.11"],
[compojure "0.6.4"]
[goose "2.1.6"]]
:dev-dependencies [[swank-clojure "1.2.1"]]
:repositories {"local" ~(str (.toURI (java.io.File. "maven_repository")))}
:main textextraction.main)
----
I then run:
[source,text]
----
/Users/mneedham/github/android/text-extraction $ lein run
----
And goose and all its dependencies are included in the 'lib' directory. | null | null | [
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] | leiningen-using-goose-via-a-local-maven-repository | https://markhneedham.com/blog/2011/12/27/leiningen-using-goose-via-a-local-maven-repository |
false | 2011-12-29 02:43:34 | Reading Code: Know what you're looking for | [
"reading-code"
] | [
"Reading Code"
] | In the last week or so before Christmas I got the chance to spend some time pairing with my colleague http://www.linkedin.com/pub/alex-harin/13/40b/716[Alex Harin] while trying to understand how an existing application which we were investigating was written.
We knew from watching a demo of the application that the user was able to send some processing off to be done in the background and that they would be emailed once that had happened.
Our starting point was therefore to work backwards from the labels on the UI and finding which code got executed when the user submitted the task.
My initial approach was to find the entry point and then follow the method calls line by line, slowly building my knowledge of how the application actually worked.
Alex used a much quicker approach whereby he *thought about how the code would be designed* and then looked for the bit of code which proved his belief.
In this case we knew that the application had a 2 tier architecture and that it didn't use any middleware which meant that it would more than likely be using the database as a queue to store the tasks to be processed.
Another colleague and I were then able to make use of this approach when looking at another piece of code.
It was being used to do pricing and we knew that there were different algorithms depending on which country you were in, which meant that we needed to look for anything country related to answer our questions.
Effectively we're looking at the code with a hypothesis in hand and then trying to see whether or not what we see proves or disproves that hypotheses.
I need to practice a bit more but it seems to let you navigate code much more quickly and makes you much less likely to dive down a rabbit hole. | null | null | [
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] | reading-code-know-what-youre-looking-for | https://markhneedham.com/blog/2011/12/29/reading-code-know-what-youre-looking-for |
false | 2011-12-29 22:40:19 | Learning Android: Sharing with Twitter/the 'share via' dialog | [
"android"
] | [
"Android"
] | One thing I wanted to do in the little application I'm working on was send data to other apps on my phone using the 'share via' dialog which I've seen used on the https://market.android.com/details?id=com.twitter.android&hl=en[Twitter app].
In this case I wanted to send a link and its title to twitter and came across http://stackoverflow.com/questions/3553017/android-share-via-dialog[a StackOverflow post which explained how to do so].
To keep it simple I added a button to the view and then shared the data via the on click event on that button:
[source,java]
----
Button button = createButton();
button.setOnClickListener(new View.OnClickListener() {
public void onClick(View v) {
Intent shareIntent = new Intent(android.content.Intent.ACTION_SEND);
shareIntent.setType("text/plain");
shareIntent.putExtra(android.content.Intent.EXTRA_TEXT, "Stupid Scanner tricks - http://weblogs.java.net/blog/pat/archive/2004/10/stupid_scanner_1.html");
v.getContext().startActivity(Intent.createChooser(shareIntent, "Share via"));
}
});
----
image::{{<siteurl>}}/uploads/2011/12/android-share-via.jpg[Android share via,226]
In this case if I choose the Twitter app from the drop down list that appears it will create a new tweet with the value of 'android.content.Intent.EXTRA_TEXT' as its body.
If we needed to pass a subject to the other app then we could set that using 'android.content.Intent.EXTRA_SUBJECT' but in this case it's unnecessary.
From what I understand so far only apps which can handle the 'text/plain' format will show up in the drop down list but that seems to be pretty much every app on my phone.
This works reasonably well but I wanted to see if it was possible to share directly with the Twitter app rather than having to choose from a selection of apps.
Via a http://lisudza.wordpress.com/2010/12/29/tweeting-using-twitter-for-android-intent/[combination] http://blog.rafaelsanches.com/2010/06/18/using-native-twitter-app-intent-to-share-on-android/[of blog posts] and http://stackoverflow.com/questions/7545254/android-and-facebook-share-intent[StackOverflow questions] I came across the following solution for posting directly to the Twitter app:
[source,java]
----
Button button = createButton();
button.setOnClickListener(new View.OnClickListener() {
public void onClick(View v) {
Intent shareIntent = new Intent(android.content.Intent.ACTION_SEND);
shareIntent.setType("text/plain");
shareIntent.putExtra(android.content.Intent.EXTRA_SUBJECT, "Some text");
shareIntent.putExtra(android.content.Intent.EXTRA_TEXT, "Stupid Scanner tricks - http://weblogs.java.net/blog/pat/archive/2004/10/stupid_scanner_1.html");
final PackageManager pm = v.getContext().getPackageManager();
final List<ResolveInfo> activityList = pm.queryIntentActivities(shareIntent, 0);
for (final ResolveInfo app : activityList) {
if ("com.twitter.android.PostActivity".equals(app.activityInfo.name)) {
final ActivityInfo activity = app.activityInfo;
final ComponentName name = new ComponentName(activity.applicationInfo.packageName, activity.name);
shareIntent.addCategory(Intent.CATEGORY_LAUNCHER);
shareIntent.setFlags(Intent.FLAG_ACTIVITY_NEW_TASK | Intent.FLAG_ACTIVITY_RESET_TASK_IF_NEEDED);
shareIntent.setComponent(name);
v.getContext().startActivity(shareIntent);
break;
}
}
}
}):;
----
It does depend on the Twitter app being installed on the phone to work but since the app is just for me I think it's ok for the moment. | null | null | [
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] | learning-android-sharing-with-twitterthe-share-via-dialog | https://markhneedham.com/blog/2011/12/29/learning-android-sharing-with-twitterthe-share-via-dialog |
false | 2011-12-10 14:11:13 | The 5 Whys/Root cause analysis - Douglas Squirrel | [
"software-development",
"root-cause-analysis",
"5whys"
] | [
"Software Development"
] | At XP Day I was chatting to http://blog.benjaminm.net/[Benjamin Mitchell] about http://www.markhneedham.com/blog/2011/10/24/retrospective-the-5-whys/[the 5 whys] http://www.markhneedham.com/blog/2011/11/13/the-5-whys-another-attempt/[exercises] that we'd tried on my team and I suggested that beyond http://www.startuplessonslearned.com/2009/07/how-to-conduct-five-whys-root-cause.html[Eric Ries' post on the subject] I hadn't come across an article/video which explained how to do it.
Benjamin mentioned that Douglas Squirrel had recently done a talk on this very subject at Skillsmatter and as with most Skillsmatter talks there's a http://skillsmatter.com/podcast/agile-testing/hands-on-root-cause-analysis[video of the presentation online].
http://gojko.net/2010/05/26/effective-root-cause-analysis-techniques/[Gojko wrote a post summarising the talk at the time] but I was interested in seeing how a 5 whys facilitated by Douglas would compare to the ones that we'd done.
These were some of my observations/learnings:
* Douglas started off with a similar approach to the one we tried in our last attempt whereby he *listed all the initial problems across the board and then worked through them*. One thing he did much better was ensuring that the 5 whys were covered for each problem before moving onto the next one. He described this as '*move down, then across*' and made the interesting observation that when you get to the real root cause (in theory the 5th why) there will be a pause and it will hurt. I don't remember noticing that in any of our 5 whys which means, Douglas suggests, that 'you[/we] are not doing it right'. In terms of actually getting to the root cause he's probably right but you can still learn some useful things even if you don't dig down that far.
* He also made the suggestions that we *shouldn't follow whys which we can immediately see are not going to go anywhere* - we'd be better off going down one of the other nodes which might lead us to some useful learning. I think we made the mistake of following some nodes which we could tell were going to go nowhere the first time that we did the exercise and ended up reaching a 5th why which was so general that we couldn't do anything with it. On the other hand I think it probably takes a couple of goes at the 5 whys before you can say with certainty that following a why is going to go nowhere.
* Another suggestion was to *ensure that everyone linked with the problem being discussed is in the room*, partly so that they don't end up being made the scape goat in absentia. In the two exercises we've run we only included the people on our immediate team and we did reach a point where it was difficult to work out what the answer to some of the whys should be because the person who could answer that question wasn't in the room. It does obviously make it more logistically difficult to organise the meeting, especially if you have people working in different countries.
* Squirrel suggested then *any actions that come out of the meeting should be completable in a week* which helps to ensure that they're realistic and proportionate to the problem. If something goes wrong once then we don't necessarily need to make massive changes to avoid it in future, it might be sufficient to just make some small changes and then observe if things have improved. </ul> Overall I found the talk quite useful and it was especially helpful to be able to see how a more experienced facilitator, like Douglas, was able to guide the discussion back into the framework so that it didn't drift off. I'm not yet convinced that we would want to run a 5 whys exercise every week which is what I've heard suggested before - I think the format could quickly become dull to people as with any other meeting format when used repeatedly. | null | null | [
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] | the-5-whysroot-cause-analysis-douglas-squirrel | https://markhneedham.com/blog/2011/12/10/the-5-whysroot-cause-analysis-douglas-squirrel |
false | 2011-12-31 17:47:47 | Clojure: Casting to a Java class...or not! | [
"clojure"
] | [
"Clojure"
] | I have a bit of Java code for http://stackoverflow.com/questions/2659000/java-how-to-find-the-redirected-url-of-a-url[working out the final destination of a URL] assuming that there might be one redirect which looks like this:
[source,java]
----
private String resolveUrl(String url) {
try {
HttpURLConnection con = (HttpURLConnection) (new URL(url).openConnection());
con.setInstanceFollowRedirects(false);
con.connect();
int responseCode = con.getResponseCode();
if (String.valueOf(responseCode).startsWith("3")) {
return con.getHeaderField("Location");
}
} catch (IOException e) {
return url;
}
return url;
}
----
I need to cast to +++<cite>+++HttpURLConnection+++</cite>+++ on the first line so that I can make the call to +++<cite>+++setInstanceFollowRedirects+++</cite>+++ which isn't available on +++<cite>+++URLConnection+++</cite>+++.
I wanted to write some similar code in Clojure and my first thought was that I needed to work out how to do the cast, which I didn't know how to do.
I then remembered that Clojure is actually dynamically typed so there isn't any need - as long as the object has the method that we want to call on it everything will be fine.
In this case we end up with the following code:
[source,clojure]
----
(defn resolve-url [url]
(let [con (.. (new URL url) openConnection)]
(doall
(.setInstanceFollowRedirects con false)
(.connect con))
(if (.startsWith (str (.getResponseCode con)) "3")
(.getHeaderField con "Location")
url)))
----
Which can be simplified to this:
[source,clojure]
----
(defn resolve-url [url]
(let [con (doto (.. (new URL url) openConnection)
(.setInstanceFollowRedirects false)
(.connect))]
(if (.startsWith (str (.getResponseCode con)) "3")
(.getHeaderField con "Location")
url)))
---- | null | null | [
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] | clojure-casting-to-a-java-class-or-not | https://markhneedham.com/blog/2011/12/31/clojure-casting-to-a-java-class-or-not |
false | 2011-12-31 03:54:00 | Yak Shaving: Tracking the yak stack | [
"yak-shaving"
] | [
"Software Development"
] | image::{{<siteurl>}}/uploads/2011/12/yak-stack.jpg[Yak stack,300]
While I've been http://www.markhneedham.com/blog/category/android-2/[learning how to write an android application] there's been plenty of opportunities for me to go off http://www.markhneedham.com/blog/?s=shaving+yak[shaving yaks], it's pretty much Yakville Central.
Typically I'd end up spending hours trying to work out some obscure thing which I didn't really need to know so I wanted to try and avoid that this time.
I started keeping a track of the 'yak stack' which I was currently following and mentally noting exactly where I was up to.
An example of a yak stack I kept while trying to authorise a user of the app with Twitter using OAuth is shown in the photo on the right hand side.
It ended up looking like this:
* Get the home timeline working
** OAuth blowing up
*** Not actually capturing redirect back to app
**** Launch mode in Android manifest
Once I realise I'm heading down the stack I've been giving myself one http://www.pomodorotechnique.com/[pomodoro] to try and dig myself one level up.
If I still haven't managed to solve the problem I might keep going for one more pomodoro or just find another way around the problem.
I'm sure I'll come across problems where I need to spend more than an hour trying to solve it but for now it's working ok as a rule of thumb.
It's definitely fun chasing yaks but I get to the end of the day and haven't really achieved anything which isn't fun. | null | null | [
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false | 2011-12-30 03:38:58 | The Language of Risk | [
"agile"
] | [
"Agile"
] | A few weeks ago Chris Matts wrote an interesting blog post 'http://theitriskmanager.wordpress.com/2011/12/12/the-language-of-risk/[the language of risk]' in which he describes an approach he used to explain the processes his team uses to an auditor.
____
Why did the auditor like what I said? Because *I explained everything we did in terms of risk*. When they asked for a "`process`", I explained the risk the process was meant to address. I then explained how our different process addressed the risk more effectively.
____
This seems like a pretty cool idea to me and it got me thinking of the different 'processes' we've used in teams I've worked on and what risks they might be addressing:
* Pair Programming
** Becoming dependent on one person with respect to knowledge of part of the code base.
** Having someone new working on an area of the code that they don't know well and making a mistake.
* Retrospective
** Making the same mistakes repeatedly/working in a way that (indirectly) wastes money.
* Story Kick Off
** Building the wrong thing
** Solving the business problem in an inefficient way
** Building something which is very difficult to test
* Stand Up
** Someone getting stuck on something which someone else in the group might be able to help with.
** People going down rabbit holes and getting stuck on things that don't really matter
* Show Case
** Building the wrong thing for too long
* Automated testing
** The application regresses as new functionality is added
** Humans make mistakes when manually going through scenarios
That's just a first attempt at this, I'm sure others could come up with something better!
In coming up with the list I've been working from a process which I've seen used and trying to work out what risk that might be addressing.
Chris seems to look at risks/processes the other way around to i.e. we *think about what risks we need to address and then work out whether we need a process to address it* and if so which one.
Taking that approach would help to explain why some teams don't necessarily need a lot of process - the risks might be catered for in different ways or maybe they just don't exist in specific contexts.
For example a lot of risks around communication go away if the product owner and the team are sitting in the same physical location and can easily just turn and talk to each other if they have any questions.
Even with this new way of looking at risks/process I still think it's useful to keep checking whether or not a process is still necessary because as our team/product changes the risks we face probably do as well. | null | null | [
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] | the-language-of-risk | https://markhneedham.com/blog/2011/12/30/the-language-of-risk |
false | 2011-12-23 22:55:17 | Learning Android: Deploying application to phone from Mac OS X | [
"android"
] | [
"Android"
] | I've been playing around a little bit today with writing an Android application and while for the majority of the time I've been deploying to an emulator I wanted to see what it'd look like on my phone.
http://developer.android.com/guide/developing/device.html[The developer guide contains all the instructions] on how to do this but unfortunately I'm blessed with the ability to skim over instructions which meant that my phone wasn't getting picked up by the http://developer.android.com/guide/developing/tools/adb.html[Android Debug Bridge].
We can check which devices have been detected by running the following command from wherever the SDK is installed:
[source,text]
----
/Users/mneedham/github/android/android-sdk-macosx/platform-tools/adb devices
----
This was initially returning no devices and http://esausilva.com/2010/10/02/how-to-set-up-adb-android-debug-bridge-in-mac-osx/[reading Esau Silva's blog] made me realise that I'd failed to follow this instruction:
____
On the device, go to Settings > Applications > Development and enable USB debugging (on an Android 4.0 device, the setting is located in Settings > Developer options).
____
I'd assumed it was only necessary if I wanted to debug the application on my phone but it seems like you need to set it to be able to deploy in the first place.
And now my phone gets picked up and can be deployed to, yay!
[source,text]
----
/Users/mneedham/github/android/android-sdk-macosx/platform-tools/adb devices
List of devices attached
3933C40945FA00EC device
----
If it still doesn't work then http://esausilva.com/2010/10/02/how-to-set-up-adb-android-debug-bridge-in-mac-osx/[Esau Silva has some other ideas] which I haven't yet needed to try. | null | null | [
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] | learning-android-deploying-application-to-phone-from-mac-os-x | https://markhneedham.com/blog/2011/12/23/learning-android-deploying-application-to-phone-from-mac-os-x |
false | 2011-12-15 23:19:31 | WebDriver: Getting it to play nicely with Xvfb | [
"webdriver"
] | [
"Software Development"
] | Another thing we've been doing with WebDriver is having it run with the FirefoxDriver while redirecting the display output into the http://en.wikipedia.org/wiki/Xvfb[Xvfb framebuffer] so that we can run it on our continuous integration agents which don't have a display attached.
The first thing we needed to do was set the environment property 'webdriver.firefox.bin' to our own script which would point the display to Xvfb before starting Firefox:
[source,scala]
----
import java.lang.System._
lazy val firefoxDriver: FirefoxDriver = {
setProperty("webdriver.firefox.bin", "/our/awesome/starting-firefox.sh")
new FirefoxDriver()
}
----
Our first version of the script looked like this:
/our/awesome/starting-firefox.sh
[source,text]
----
#!/bin/bash
rm -f ~/.mozilla/firefox/*/.parentlock
rm -rf /var/go/.mozilla
XVFB=`which xVfb`
if [ "$?" -eq 1 ];
then
echo "Xvfb not found."
exit 1
fi
$XVFB :99 -ac &
BROWSER=`which firefox`
if [ "$?" -eq 1 ];
then
echo "Firefox not found."
exit 1
fi
export DISPLAY=:99
$BROWSER &
----
The mistake we made here was that we started Xvfb in the background which meant that sometimes it hadn't actually started by the time Firefox tried to connect to the display and we ended up with this error message:
[source,text]
----
No Protocol specified
Error cannot open display :99
----
We really wanted to keep Xvfb running regardless of whether the Firefox instances being used by WebDriver were alive or not so we moved the starting of Xvfb out into a separate script which we run as one of the earlier steps in the build.
We also struggled to get the FirefoxDriver to kill itself after each test as calling 'close' or 'quit' on the driver didn't seem to kill off the process.
We eventually resorted to putting a 'pkill firefox' statement at the start of our firefox starting script:
/our/awesome/starting-firefox.sh
[source,text]
----
#!/bin/bash
rm -f ~/.mozilla/firefox/*/.parentlock
rm -rf /var/go/.mozilla
pkill firefox
BROWSER=`which firefox`
if [ "$?" -eq 1 ];
then
echo "Firefox not found."
exit 1
fi
export DISPLAY=:99
$BROWSER &
----
It's a bit hacky but it does the job more deterministically than anything else we've tried previously. | null | null | [
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] | webdriver-getting-it-to-play-nicely-with-xvfb | https://markhneedham.com/blog/2011/12/15/webdriver-getting-it-to-play-nicely-with-xvfb |
false | 2011-12-13 23:31:02 | WebDriver: Getting it to play nicely with jQuery ColorBox | [
"webdriver"
] | [
"Software Development"
] | As I http://www.markhneedham.com/blog/2011/12/05/continuous-delivery-removing-manual-scenarios/[mentioned in an earlier post about removing manual test scenarios] we've been trying to automate some parts of our application where a user action leads to a http://jacklmoore.com/colorbox/[jQuery ColorBox] powered overlay appearing.
With this type of feature there tends to be some sort of animation which accompanies the overlay so we have to wait for an element inside the overlay to become visible on the screen before trying to do any assertions on the overlay.
We have a simple method to do that:
[source,scala]
----
def iWaitUntil(waitingFor: => Boolean) {
for (i <- 1 to 5) {
if(waitingFor) {
return
}
Thread.sleep(200)
}
}
----
It can then be called like this in our tests:
[source,scala]
----
def driver: WebDriver = new FirefoxDriver()
iWaitUntil(driver.findElements(By.cssSelector(".i-am .inside-the-colorbox h3")).nonEmpty)
driver.findElement(By.cssSelector(".i-am .inside-the-colorbox h3")).getText should equal("Awesome Title")
----
Annoyingly what we noticed was that this wasn't enough and although the h3 element was coming back as being visible it was then failing the following assertion because 'getText' was returning nothing despite the fact that it clearly had text inside it!
http://twitter.com/#!/uday_rayala[Uday] came up with the neat idea of adding an additional wait clause which would wait until the text was non empty so we now have something like this...
[source,scala]
----
def driver: WebDriver = new FirefoxDriver()
iWaitUntil(driver.findElements(By.cssSelector(".i-am .inside-the-colorbox h3")).nonEmpty)
driver.findElement(By.cssSelector(".i-am .inside-the-colorbox h3")).getText should equal("Awesome Title")
iWaitUntil(driver.findElement(By.cssSelector(".i-am .inside-the-colorbox h3")).getText != "")
----
...which seems to do the job nicely.
An alternative approach would have been to disable the animation of jQuery ColorBox just for our tests but the approach we took was a much quicker win at the time.
We did realise later on that we didn't need to write our own wait method since http://seleniumhq.org/docs/04_webdriver_advanced.html[WebDriver has one built into the API] but I guess they both do similar things so it's not such a big problem. | null | null | [
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] | webdriver-getting-it-to-play-nicely-with-jquery-colorbox | https://markhneedham.com/blog/2011/12/13/webdriver-getting-it-to-play-nicely-with-jquery-colorbox |
false | 2016-04-18 19:49:02 | R: substr - Getting a vector of positions | [
"r-2"
] | [
"R"
] | I recently found myself writing an R script to extract parts of a string based on a beginning and end index which is reasonably easy using the +++<cite>+++https://stat.ethz.ch/R-manual/R-devel/library/base/html/substr.html[substr]+++</cite>+++ function:
[source,r]
----
> substr("mark loves graphs", 0, 4)
[1] "mark"
----
But what if we have a vector of start and end positions?
[source,r]
----
> substr("mark loves graphs", c(0, 6), c(4, 10))
[1] "mark"
----
Hmmm that didn't work as I expected! It turns out we actually need to use the +++<cite>+++https://stat.ethz.ch/R-manual/R-devel/library/base/html/substr.html[substring]+++</cite>+++ function instead which wasn't initially obvious to me on reading the documentation:
[source,r]
----
> substring("mark loves graphs", c(0, 6, 12), c(4, 10, 17))
[1] "mark" "loves" "graphs"
----
Easy when you know how! | null | null | [
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] | r-substr-getting-a-vector-of-positions | https://markhneedham.com/blog/2016/04/18/r-substr-getting-a-vector-of-positions |
false | 2016-04-11 05:40:06 | R: tm - Unique words/terms per document | [
"r-2"
] | [
"R"
] | I've been doing a bit of text mining over the weekend using the R https://cran.r-project.org/web/packages/tm/index.html[tm package] and I wanted to only count a term once per document which isn't how it works out the box.
For example let's say we're writing a bit of code to calculate the frequency of terms across some documents. We might write the following code:
[source,r]
----
library(tm)
text = c("I am Mark I am Mark", "Neo4j is cool Neo4j is cool")
corpus = VCorpus(VectorSource(text))
tdm = as.matrix(TermDocumentMatrix(corpus, control = list(wordLengths = c(1, Inf))))
> tdm
Docs
Terms 1 2
am 2 0
cool 0 2
i 2 0
is 0 2
mark 2 0
neo4j 0 2
> rowSums(tdm)
am cool i is mark neo4j
2 2 2 2 2 2
----
We've created a small corpus over a vector which contains two bits of text. On the last line we output a TermDocumentMatrix which shows how frequently each term shows up across the corpus. I had to tweak the default word length of 3 to make sure we could see 'am' and 'cool'.
But we've actually got some duplicate terms in each of our documents so we want to get rid of those and only count unique terms per document.
We can achieve that by mapping over the corpus using the +++<cite>+++tm_map+++</cite>+++ function and then applying a function which returns unique terms. I wrote the following function:
[source,r]
----
uniqueWords = function(d) {
return(paste(unique(strsplit(d, " ")[[1]]), collapse = ' '))
}
----
We can then apply the function like so:
[source,r]
----
corpus = tm_map(corpus, content_transformer(uniqueWords))
tdm = as.matrix(TermDocumentMatrix(corpus, control = list(wordLengths = c(1, Inf))))
> tdm
Docs
Terms 1 2
am 1 0
cool 0 1
i 1 0
is 0 1
mark 1 0
neo4j 0 1
> rowSums(tdm)
am cool i is mark neo4j
1 1 1 1 1 1
----
And now each term is only counted once. Success! | null | null | [
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] | r-tm-unique-wordsterms-per-document | https://markhneedham.com/blog/2016/04/11/r-tm-unique-wordsterms-per-document |
false | 2016-05-22 09:09:27 | Neo4j vs Relational: Refactoring - Add a new field/property | [
"neo4j"
] | [
"neo4j"
] | A couple of months ago I presented http://info.neo4j.com/intro-to-cypher-for-the-sql-developer-lp.html[a webinar comparing how you'd model and evolve a data model using a Postgres SQL database and Neo4j].
This is what the two data models looked like after the initial data import and before any refactoring/migration had been done:
+++<cite>+++Relational+++</cite>+++
image::{{<siteurl>}}/uploads/2016/05/2016-05-22_09-49-23.png[2016 05 22 09 49 23,400]
+++<cite>+++Graph+++</cite>+++
image::{{<siteurl>}}/uploads/2016/05/2016-05-22_09-52-16.png[2016 05 22 09 52 16,400]
I wanted to add a 'nationality' property to the players table in the SQL schema and to the nodes with the 'Player' label in the graph.
This refactoring is quite easy in both models. In the relational database we first run a query to add the 'nationality' field to the table:
[source,sql]
----
ALTER TABLE players
ADD COLUMN nationality varying(30);
----
And then we need to generate UPDATE statements from our data dump to update all the existing records:
[source,sql]
----
UPDATE players
SET nationality = 'Brazil'
WHERE players.id = '/aldair/profil/spieler/4151';
...
----
In the graph we can do this in a single step by processing our data dump using the LOAD CSV command and then setting a property on each player:
[source,cypher]
----
USING PERIODIC COMMIT
LOAD CSV WITH HEADERS FROM "file:///transfers.csv" AS row
MATCH (player:Player {id: row.playerUri})
SET player.nationality = row.playerNationality
----
If we wanted to make the nationality field non nullable we could go back and run the following queries:
[source,sql]
----
ALTER TABLE players
ALTER COLUMN nationality SET NOT NULL
----
[source,cypher]
----
CREATE CONSTRAINT ON (player:Player)
ASSERT exists(player.nationality)
----
And we're done! | null | null | [
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] | neo4j-vs-relational-refactoring-add-a-new-fieldproperty | https://markhneedham.com/blog/2016/05/22/neo4j-vs-relational-refactoring-add-a-new-fieldproperty |
false | 2016-05-22 09:58:38 | Neo4j vs Relational: Refactoring - Extracting node/table | [
"neo4j"
] | [
"neo4j"
] | In my http://www.markhneedham.com/blog/2016/05/22/neo4j-vs-relational-refactoring-add-a-new-fieldproperty/[previous blog post] I showed how to add a new property/field to a node with a label/record in a table for a football transfers dataset that I've been playing with.
After introducing this 'nationality' property I realised that I now had some duplication in the model:
</p>
image::{{<siteurl>}}/uploads/2016/05/2016-05-22_10-15-15.png[2016 05 22 10 15 15,401]
+++<cite>+++players.nationality+++</cite>+++ and +++<cite>+++clubs.country+++</cite>+++ are referring to the same countries but they've both got them stored as strings so we can't ensure the integrity of our countries and ensure that we're referring to the same country.
We have the same issue in the graph model as well:
image::{{<siteurl>}}/uploads/2016/05/2016-05-22_10-40-40.png[2016 05 22 10 40 40,401]
This time +++<cite>+++Player.nationality+++</cite>+++ and +++<cite>+++Club.country+++</cite>+++ refer to the same countries.
We can solve our problem by introducing a countries table in the relational model and a set of nodes with a 'Country' label in the graph model. Let's start with relational.
This is the model we're driving towards:
image::{{<siteurl>}}/uploads/2016/05/2016-05-22_10-50-43.png[2016 05 22 10 50 43,395]
The first thing we need to do is create a countries table and populate it:
[source,sql]
----
CREATE TABLE countries (
"code" character varying(3) NOT NULL PRIMARY KEY,
"name" character varying(50) NOT NULL
);
----
[source,sql]
----
INSERT INTO countries VALUES('MNE', 'Montenegro');
INSERT INTO countries VALUES('SWZ', 'Swaziland');
...
----
Next let's update the clubs table to reference the countries table:
[source,sql]
----
ALTER TABLE clubs
ADD COLUMN country_id character varying(3)
REFERENCES countries(code);
----
And let's run a query to populate that column:
[source,sql]
----
UPDATE clubs AS cl
SET country_id = c.code
FROM clubs
INNER JOIN countries AS c
ON c.name = clubs.country
WHERE cl.id = clubs.id;
----
This query iterates over all the clubs, queries the country table to find the country id for that row and then stores it in the 'country_id' field. Finally we can remove the 'country' field:
[source,sql]
----
ALTER TABLE clubs
DROP COLUMN country;
----
Now we do the same drill for the players table:
[source,sql]
----
ALTER TABLE players
ADD COLUMN country_id character varying(3)
REFERENCES countries(code);
----
[source,sql]
----
UPDATE players AS p
SET country_id = c.code
FROM players
INNER JOIN countries AS c
ON c.name = players.nationality
WHERE p.id = players.id;
----
[source,sql]
----
ALTER TABLE players
DROP COLUMN nationality;
----
Now it's time for the graph. This is the model we want to get to:
image::{{<siteurl>}}/uploads/2016/05/2016-05-22_10-51-49.png[2016 05 22 10 51 49,334]
First we'll create the countries:
[source,cypher]
----
CREATE CONSTRAINT ON (c:Country)
ASSERT c.id IS UNIQUE
----
[source,cypher]
----
LOAD CSV WITH HEADERS FROM "file:///countries.csv"
AS row
MERGE (country:Country {id: row.countryCode})
ON CREATE SET country.name = row.country
----
And now let's get clubs and players to point at those countries nodes and get rid of their respective nationality/country properties:
[source,cypher]
----
MATCH (club:Club)
MATCH (country:Country {name: club.country})
MERGE (club)-[:PART_OF]->(country)
REMOVE club.country
----
[source,cypher]
----
MATCH (player:Player)
MATCH (country:Country {name: player.nationality})
MERGE (player)-[:PLAYS_FOR]->(country)
REMOVE player.nationality
----
And that's it, we can now write queries against our new model. | null | null | [
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] | neo4j-vs-relational-refactoring-extracting-nodetable | https://markhneedham.com/blog/2016/05/22/neo4j-vs-relational-refactoring-extracting-nodetable |
false | 2016-02-28 20:40:11 | Neo4j: A procedure for the SLM clustering algorithm | [
"neo4j"
] | [
"neo4j"
] | In the middle of last year http://www.markhneedham.com/blog/2015/06/17/coding-explore-and-retreat/[I blogged about the Smart Local Moving algorithm]which is used for community detection in networks and with the http://jexp.de/blog/2016/02/neo4j-3-0-stored-procedures/[upcoming introduction of procedures] in Neo4j I thought it'd be fun to make that code accessible as one.
If you want to grab the code and follow along it's sitting on the https://github.com/mneedham/slm[SLM repository on my github].
At the moment the procedure is hard coded to work with a +++<cite>+++KNOWS+++</cite>+++ relationship between two nodes but that could easily be changed.
To check it's working correctly I thought it'd make most sense to use the Karate Club data set described on the http://www.ludowaltman.nl/slm/[SLM home page]. I think this data set is originally from https://www.cs.cornell.edu/home/kleinber/networks-book/networks-book.pdf[Networks, Crowds and Markets].
I wrote the following LOAD CSV script to create the graph in Neo4j:
[source,cypher]
----
LOAD CSV FROM "file:///Users/markneedham/projects/slm/karate_club_network.txt" as row
FIELDTERMINATOR "\t"
MERGE (person1:Person {id: row[0]})
MERGE (person2:Person {id: row[1]})
MERGE (person1)-[:KNOWS]->(person2)
----
image::{{<siteurl>}}/uploads/2016/02/graph.png[Graph,566]
Next we need to call the procedure which will add an appropriate label to each node depending which community it belongs to. This is what the procedure code looks like:
[source,java]
----
public class ClusterAllTheThings
{
@Context
public org.neo4j.graphdb.GraphDatabaseService db;
@Procedure
@PerformsWrites
public Stream<Cluster> knows() throws IOException
{
String query = "MATCH (person1:Person)-[r:KNOWS]->(person2:Person) \n" +
"RETURN person1.id AS p1, person2.id AS p2, toFloat(1) AS weight";
Result rows = db.execute( query );
ModularityOptimizer.ModularityFunction modularityFunction = ModularityOptimizer.ModularityFunction.Standard;
Network network = Network.create( modularityFunction, rows );
double resolution = 1.0;
int nRandomStarts = 1;
int nIterations = 10;
long randomSeed = 0;
double modularity;
Random random = new Random( randomSeed );
double resolution2 = modularityFunction.resolution( resolution, network );
Map<Integer, Node> cluster = new HashMap<>();
double maxModularity = Double.NEGATIVE_INFINITY;
for ( int randomStart = 0; randomStart < nRandomStarts; randomStart++ )
{
network.initSingletonClusters();
int iteration = 0;
do
{
network.runSmartLocalMovingAlgorithm( resolution2, random );
iteration++;
modularity = network.calcQualityFunction( resolution2 );
} while ( (iteration < nIterations) );
if ( modularity > maxModularity )
{
network.orderClustersByNNodes();
cluster = network.getNodes();
maxModularity = modularity;
}
}
for ( Map.Entry<Integer, Node> entry : cluster.entrySet() )
{
Map<String, Object> params = new HashMap<>();
params.put("userId", String.valueOf(entry.getKey()));
db.execute("MATCH (person:Person {id: {userId}})\n" +
"SET person:`" + (format( "Community-%d`", entry.getValue().getCluster() )),
params);
}
return cluster
.entrySet()
.stream()
.map( ( entry ) -> new Cluster( entry.getKey(), entry.getValue().getCluster() ) );
}
public static class Cluster
{
public long id;
public long clusterId;
public Cluster( int id, int clusterId )
{
this.id = id;
this.clusterId = clusterId;
}
}
}
----
I've hardcoded some parameters to use defaults which could be exposed through the procedure to allow more control if necessary. The +++<cite>+++https://github.com/mneedham/slm/blob/master/src/main/java/org/neo4j/slm/Network.java#L69[Network#create]+++</cite>+++ function assumes it is going to receive a stream of rows containing columns 'p1', 'p2' and 'weight' to represent the 'source', 'destination' and 'weight' of the relationship between them.
We call the procedure like this:
[source,cypher]
----
CALL org.neo4j.slm.knows()
----
It will return each of the nodes and the cluster it's been assigned to and if we then visualise the network in the neo4j browser we'll see this:
image::{{<siteurl>}}/uploads/2016/02/graph-1.png[Graph 1,591]
which is similar to the visualisation from the SLM home page:
image::{{<siteurl>}}/uploads/2016/02/network.png[Network]
If you want to play around with the code feel free. You'll need to run the following commands to create the JAR for the plugin and deploy it.
[source,bash]
----
$ mvn clean package
$ cp target/slm-1.0.jar /path/to/neo4j/plugins/
$ ./path/to/neo4j/bin/neo4j restart
----
And you'll need http://neo4j.com/download/other-releases/[the latest milestone of Neo4j] which has procedures enabled. | null | null | [
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] | neo4j-a-procedure-for-the-slm-clustering-algorithm | https://markhneedham.com/blog/2016/02/28/neo4j-a-procedure-for-the-slm-clustering-algorithm |
false | 2016-11-01 22:10:57 | Neo4j: Find the intermediate point between two lat/longs | [
"neo4j"
] | [
"neo4j"
] | Yesterday I wrote a blog post showing how to find the midpoint between two lat/longs using Cypher which worked well as a first attempt at filling in missing locations, but I realised I could do better.
As I mentioned in the last post, when I find a stop that's missing lat/long coordinates I can usually find two nearby stops that allow me to triangulate this stop's location.
I also have train routes which indicate the number of seconds it takes to go from one stop to another, which allows me to indicate whether the location-less stop is closer to one stop than the other.
For example, consider stops a, b, and c where b doesn't have a location. If we have these distances between the stops:
[source,text]
----
(a)-[:NEXT {time: 60}]->(b)-[:NEXT {time: 240}]->(c)
----
it tells us that point 'b' is actually 0.2 of the distance from 'a' to 'c' rather than being the midpoint.
There's http://www.movable-type.co.uk/scripts/latlong.html#intermediate-point[a formula] we can use to work out that point:
[source,text]
----
a = sin((1βf)β
Ξ΄) / sin Ξ΄
b = sin(fβ
Ξ΄) / sin Ξ΄
x = a β
cos Ο1 β
cos Ξ»1 + b β
cos Ο2 β
cos Ξ»2
y = a β
cos Ο1 β
sin Ξ»1 + b β
cos Ο2 β
sin Ξ»2
z = a β
sin Ο1 + b β
sin Ο2
Οi = atan2(z, βxΒ² + yΒ²)
Ξ»i = atan2(y, x)
Ξ΄ is the angular distance d/R between the two points.
Ο = latitude
Ξ» = longitude
----
Translated to Cypher (with mandatory Greek symbols) it reads like this to find the point 0.2 of the way from one point to another
~~~cypher with {latitude: 51.4931963543, longitude: -0.0475185810} AS p1, {latitude: 51.47908, longitude: -0.05393950 } AS p2 WITH p1, p2, distance(point(p1), point(p2)) / 6371000 AS Ξ΄, 0.2 AS f WITH p1, p2, Ξ΄, sin((1-f) * Ξ΄) / sin(Ξ΄) AS a, sin(f * Ξ΄) / sin(Ξ΄) AS b WITH radians(p1.latitude) AS Ο1, radians(p1.longitude) AS Ξ»1, radians(p2.latitude) AS Ο2, radians(p2.longitude) AS Ξ»2, a, b WITH a * cos(Ο1) * cos(Ξ»1) + b * cos(Ο2) * cos(Ξ»2) AS x, a * cos(Ο1) * sin(Ξ»1) + b * cos(Ο2) * sin(Ξ»2) AS y, a * sin(Ο1) + b * sin(Ο2) AS z RETURN degrees(atan2(z, sqrt(x{caret}2 + y{caret}2))) AS Οi, degrees(atan2(y,x)) AS Ξ»i ~~~ ~~~text βββββββββββββββββββ€βββββββββββββββββββββ βΟi βΞ»i β βββββββββββββββββββͺβββββββββββββββββββββ‘ β51.49037311149128β-0.04880308288561931β βββββββββββββββββββ΄βββββββββββββββββββββ ~~~
A quick sanity check plugging in 0.5 instead of 0.2 finds the midpoint which I was able to sanity check against yesterday's post: ~~~text βββββββββββββββββββ€ββββββββββββββββββββββ βΟi βΞ»i β βββββββββββββββββββͺββββββββββββββββββββββ‘ β51.48613822097523β-0.050729537454086385β βββββββββββββββββββ΄ββββββββββββββββββββββ ~~~
That's all for now! | null | null | [
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] | neo4j-find-the-intermediate-point-between-two-latlongs | https://markhneedham.com/blog/2016/11/01/neo4j-find-the-intermediate-point-between-two-latlongs |
false | 2016-11-13 12:30:08 | Neo4j 3.1 beta3 + docker: Creating a Causal Cluster | [
"neo4j"
] | [
"neo4j"
] | Over the weekend I've been playing around with docker and learning how to spin up a https://neo4j.com/blog/neo4j-3-1-beta-release/[Neo4j Causal Cluster].
Causal Clustering is Neo4j's new clustering architecture which makes use of https://twitter.com/ongardie[Diego Ongaro's] https://raft.github.io/[Raft consensus algorithm] to ensure writes are committed on a majority of servers. It'll be available in the 3.1 series of Neo4j which is currently in beta. I'll be using https://neo4j.com/download/other-releases/[BETA3] in this post.
image::{{<siteurl>}}/uploads/2016/11/2016-11-13_09-14-41.png[2016 11 13 09 14 41,300]
I don't know much about docker but luckily my colleague Kevin Van Gundy wrote a blog post a couple of weeks ago explaining how to http://kvangundy.com/wp/set-up-neo4j-and-docker/[spin up Neo4j inside a docker container] which was very helpful for getting me started.
Kevin spins up a single Neo4j server using the latest released version, which at the time of writing is 3.0.7. Since we want to use a beta version we'll need to use a docker image from the https://hub.docker.com/r/neo4j/neo4j-experimental/[neo4j-experimental repository].
We're going to create 3 docker instances, each running Neo4j, and have them form a cluster. We'll name them +++<cite>+++instance0+++</cite>+++, +++<cite>+++instance1+++</cite>+++, and +++<cite>+++instance2+++</cite>+++. We'll create config files for each instance on the host machine and refer to those from our docker instance. This is the config file for +++<cite>+++instance0+++</cite>+++:
+++<cite>+++/tmp/ce/instance0/conf/neo4j.conf+++</cite>+++
[source,text]
----
unsupported.dbms.edition=enterprise
dbms.mode=CORE
dbms.security.auth_enabled=false
dbms.memory.heap.initial_size=512m
dbms.memory.heap.max_size=512m
dbms.memory.pagecache.size=100M
dbms.tx_log.rotation.retention_policy=false
dbms.connector.bolt.type=BOLT
dbms.connector.bolt.enabled=true
dbms.connector.bolt.listen_address=0.0.0.0:7687
dbms.connector.http.type=HTTP
dbms.connector.http.enabled=true
dbms.connector.http.listen_address=0.0.0.0:7474
dbms.connectors.default_listen_address=0.0.0.0
dbms.connectors.default_advertised_address=instance0
causal_clustering.initial_discovery_members=instance0:5000,instance1:5000,instance2:5000
causal_clustering.leader_election_timeout=2s
----
The only config that changes between instances is +++<cite>+++dbms.connectors.default_advertised_address+++</cite>+++ which would have a value of +++<cite>+++instance1+++</cite>+++ or +++<cite>+++instance2+++</cite>+++ for the other members of our cluster.
We can create a docker instance using this config:
[source,bash]
----
docker run --name=instance0 --detach \
--publish=7474:7474 \
--publish=7687:7687 \
--net=cluster \
--hostname=instance0 \
--volume /tmp/ce/instance0/conf:/conf \
--volume /tmp/ce/instance0/data:/data \
neo4j/neo4j-experimental:3.1.0-M13-beta3-enterprise
----
We create the network 'cluster' referenced on the 4th line like this:
[source,bash]
----
docker network create --driver=bridge cluster
----
It's a bit of a pain having to create these config files and calls to docker by hand but luckily https://twitter.com/mesirii[Michael] has https://gist.github.com/mneedham/1e2f34a1fae89c92c0b2c88946302cac[scripted the whole thing for us].
+++<cite>+++docker.sh+++</cite>+++
[source,text]
----
function config {
mkdir -p /tmp/ce/$1/conf
cat > /tmp/ce/$1/conf/neo4j.conf << EOF
unsupported.dbms.edition=enterprise
dbms.mode=CORE
dbms.security.auth_enabled=false
dbms.memory.heap.initial_size=512m
dbms.memory.heap.max_size=512m
dbms.memory.pagecache.size=100M
dbms.tx_log.rotation.retention_policy=false
dbms.connector.bolt.type=BOLT
dbms.connector.bolt.enabled=true
dbms.connector.bolt.listen_address=0.0.0.0:7687
dbms.connector.http.type=HTTP
dbms.connector.http.enabled=true
dbms.connector.http.listen_address=0.0.0.0:7474
dbms.connectors.default_listen_address=0.0.0.0
dbms.connectors.default_advertised_address=${1}
causal_clustering.initial_discovery_members=instance0:5000,instance1:5000,instance2:5000
causal_clustering.leader_election_timeout=2s
EOF
}
function run {
HOST=$1
INSTANCE=instance$HOST
config $INSTANCE
docker run --name=$INSTANCE --detach \
--publish=$[7474+$HOST]:7474 \
--publish=$[7687+$HOST]:7687 \
--net=cluster \
--hostname=$INSTANCE \
--volume /tmp/ce/$INSTANCE/conf:/conf \
--volume /tmp/ce/$INSTANCE/data:/data \
neo4j/neo4j-experimental:3.1.0-M13-beta3-enterprise
}
docker network create --driver=bridge cluster
run 0
run 1
run 2
----
Once we run the script we can run the following command to check that the cluster has come up:
[source,bash]
----
$ docker logs instance0
Starting Neo4j.
2016-11-13 11:46:55.863+0000 INFO Starting...
2016-11-13 11:46:57.241+0000 INFO Bolt enabled on 0.0.0.0:7687.
2016-11-13 11:46:57.255+0000 INFO Initiating metrics...
2016-11-13 11:46:57.439+0000 INFO Waiting for other members to join cluster before continuing...
2016-11-13 11:47:17.816+0000 INFO Started.
2016-11-13 11:47:18.054+0000 INFO Mounted REST API at: /db/manage
2016-11-13 11:47:19.068+0000 INFO Remote interface available at http://instance0:7474/
----
Each instance is available at port 7474 but we've mapped these to different ports on the host OS by using this line in the parameters we passed to +++<cite>+++docker run+++</cite>+++:
[source,bash]
----
--publish=$[7474+$HOST]:7474
----
We can therefore access each of these Neo4j instances from the host OS at the following ports:
[source,text]
----
instance0 -> http://localhost:7474
instance1 -> http://localhost:7475
instance2 -> http://localhost:7476
----
If we open one of those we'll be confronted with the following dialog:
image::{{<siteurl>}}/uploads/2016/11/2016-11-13_12-10-06.png[2016 11 13 12 10 06,597]
This is a bit strange as we explicitly disabled security in our config.
The actual problem is that the Neo4j browser is unable to communicate with the underlying database. There are two ways to work around this:</p>
== Connect using HTTP instead of BOLT
We can tell the browser to connect to the database using the HTTP protocol rather than BOLT by unticking the checkbox:
image::{{<siteurl>}}/uploads/2016/11/2016-11-13_12-12-24.png[2016 11 13 12 12 24,189]
== Update the BOLT host
Or we can update the Bolt host value to refer to a +++<cite>+++host:port+++</cite>+++ value that's accessible from the host OS. Each server is accessible from port 7687 but we mapped those ports to different ports on the host OS with this flag that we passed to +++<cite>+++docker run+++</cite>+++:
[source,bash]
----
--publish=$[7687+$HOST]:7687 \
----
We can access BOLT from the following ports:
[source,text]
----
instance0 -> localhost:7687
instance1 -> localhost:7688
instance2 -> localhost:7689
----
Let's try changing it for +++<cite>+++instance2+++</cite>+++:+++<div>++++++</div>+++
image::{{<siteurl>}}/uploads/2016/11/2016-11-13_12-20-29.png[2016 11 13 12 20 29,174]
You might have to refresh your web browser after you change value but it usually updates automatically. We can run the +++<cite>+++:sysinfo+++</cite>+++ command in the browser to see the state of our cluster:
image::{{<siteurl>}}/uploads/2016/11/2016-11-13_12-22-55.png[2016 11 13 12 22 55,453]
And we're good to go. The https://gist.github.com/mneedham/1e2f34a1fae89c92c0b2c88946302cac[full script is available as a gist] if you want to give it a try.
Let me know how you get on! | null | null | [
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] | neo4j-3-1-beta3-docker-creating-a-causal-cluster | https://markhneedham.com/blog/2016/11/13/neo4j-3-1-beta3-docker-creating-a-causal-cluster |
false | 2016-11-22 19:56:31 | Kubernetes: Writing hostname to a file | [
"kubernetes"
] | [
"Software Development"
] | Over the weekend I spent a bit of time playing around with Kubernetes and to get the hang of the technology I set myself the task of writing the hostname of the machine to a file.
I'm using the excellent https://github.com/kubernetes/minikube[minikube] tool to create a local Kubernetes cluster for my experiments so the first step is to spin that up:
[source,bash]
----
$ minikube start
Starting local Kubernetes cluster...
Kubectl is now configured to use the cluster.
----
The first thing I needed to work out how to get the hostname. I figured there was probably an environment variable that I could access. We can call the +++<cite>+++env+++</cite>+++ command to see a list of all the environment variables in a container so I created a pod template that would show me that information:
+++<cite>+++hostname_super_simple.yaml+++</cite>+++
[source,text]
----
apiVersion: v1
kind: Pod
metadata:
name: mark-super-simple-test-pod
spec:
containers:
- name: test-container
image: gcr.io/google_containers/busybox:1.24
command: [ "/bin/sh", "-c", "env" ]
dnsPolicy: Default
restartPolicy: Never
----
I then created a pod from that template and checked the logs of that pod:
[source,bash]
----
$ kubectl create -f hostname_super_simple.yaml
pod "mark-super-simple-test-pod" created
----
[source,bash]
----
$ kubectl logs mark-super-simple-test-pod
KUBERNETES_SERVICE_PORT=443
KUBERNETES_PORT=tcp://10.0.0.1:443
HOSTNAME=mark-super-simple-test-pod
SHLVL=1
HOME=/root
KUBERNETES_PORT_443_TCP_ADDR=10.0.0.1
PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
KUBERNETES_PORT_443_TCP_PORT=443
KUBERNETES_PORT_443_TCP_PROTO=tcp
KUBERNETES_SERVICE_PORT_HTTPS=443
KUBERNETES_PORT_443_TCP=tcp://10.0.0.1:443
PWD=/
KUBERNETES_SERVICE_HOST=10.0.0.1
----
The information we need is in +++<cite>+++$HOSTNAME+++</cite>+++ so the next thing we need to do is created a pod template which puts that into a file.
+++<cite>+++hostname_simple.yaml+++</cite>+++
[source,text]
----
apiVersion: v1
kind: Pod
metadata:
name: mark-test-pod
spec:
containers:
- name: test-container
image: gcr.io/google_containers/busybox:1.24
command: [ "/bin/sh", "-c", "echo $HOSTNAME > /tmp/bar; cat /tmp/bar" ]
dnsPolicy: Default
restartPolicy: Never
----
We can create a pod using this template by running the following command:
[source,bash]
----
$ kubectl create -f hostname_simple.yaml
pod "mark-test-pod" created
----
Now let's check the logs of the instance to see whether our script worked:
[source,bash]
----
$ kubectl logs mark-test-pod
mark-test-pod
----
Indeed it did, good times! | null | null | [
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] | kubernetes-writing-hostname-to-a-file | https://markhneedham.com/blog/2016/11/22/kubernetes-writing-hostname-to-a-file |
false | 2016-11-25 16:55:56 | Kubernetes: Spinning up a Neo4j 3.1 Causal Cluster | [
"neo4j",
"kubernetes"
] | [
"neo4j"
] | A couple of weeks ago I wrote a blog post explaining how I'd http://www.markhneedham.com/blog/2016/11/13/neo4j-3-1-beta3-docker-creating-a-causal-cluster/[created a Neo4j causal cluster using docker containers directly] and for my next pet project I wanted to use Kubernetes as an orchestration layer so that I could declaratively change the number of servers in my cluster.
I'd never used Kubernetes before but I saw a presentation showing how to use it to create an Elastic cluster at the https://www.meetup.com/gdgcloud/events/233298216/[GDG Cloud meetup a couple of months ago].
In that presentation I was introduced to the idea of a http://kubernetes.io/docs/user-guide/petset/[PetSet] which is an abstraction exposed by Kubernetes which allows us to manage a set of pods (containers) which have a fixed identity. The documentation explains it better:
____
A PetSet ensures that a specified number of "`pets`" with unique identities are running at any given time. The identity of a Pet is comprised of:
* a stable hostname, available in DNS
* an ordinal index
* stable storage: linked to the ordinal & hostname
____
In my case I need to have a stable hostname because each member of a Neo4j cluster is given a list of other cluster members with which it can create a new cluster or join an already existing one. This is the first use case described in the documentation:
____
PetSet also helps with the 2 most common problems encountered managing such clustered applications:
* discovery of peers for quorum
* startup/teardown ordering
____
So the first thing we need to do is create some stable storage for our pods to use.
We'll create a cluster of 3 members so we need to create one http://kubernetes.io/docs/user-guide/persistent-volumes/[PersistentVolume] for each of them. The following script does the job:
+++<cite>+++volumes.sh+++</cite>+++
[source,text]
----
for i in $(seq 0 2); do
cat <<EOF | kubectl create -f -
kind: PersistentVolume
apiVersion: v1
metadata:
name: pv${i}
labels:
type: local
app: neo4j
spec:
capacity:
storage: 1Gi
accessModes:
- ReadWriteOnce
hostPath:
path: "/tmp/${i}"
EOF
cat <<EOF | kubectl create -f -
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
name: datadir-neo4j-${i}
labels:
app: neo4j
spec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 1Gi
EOF
done;
----
If we run this script it'll create 3 volumes which we can see by running the following command:
[source,bash]
----
$ kubectl get pv
NAME CAPACITY ACCESSMODES STATUS CLAIM REASON AGE
pv0 1Gi RWO Bound default/datadir-neo4j-0 7s
pv1 1Gi RWO Bound default/datadir-neo4j-1 7s
pv2 1Gi RWO Bound default/datadir-neo4j-2 7s
----
[source,bash]
----
$ kubectl get pvc
NAME STATUS VOLUME CAPACITY ACCESSMODES AGE
datadir-neo4j-0 Bound pv0 1Gi RWO 26s
datadir-neo4j-1 Bound pv1 1Gi RWO 26s
datadir-neo4j-2 Bound pv2 1Gi RWO 25s
----
Next we need to create a PetSet template. After a lot of iterations I ended up with the following:
[source,text]
----
# Headless service to provide DNS lookup
apiVersion: v1
kind: Service
metadata:
labels:
app: neo4j
name: neo4j
spec:
clusterIP: None
ports:
- port: 7474
selector:
app: neo4j
---
# new API name
apiVersion: "apps/v1alpha1"
kind: PetSet
metadata:
name: neo4j
spec:
serviceName: neo4j
replicas: 3
template:
metadata:
annotations:
pod.alpha.kubernetes.io/initialized: "true"
pod.beta.kubernetes.io/init-containers: '[
{
"name": "install",
"image": "gcr.io/google_containers/busybox:1.24",
"command": ["/bin/sh", "-c", "echo \"
unsupported.dbms.edition=enterprise\n
dbms.mode=CORE\n
dbms.connectors.default_advertised_address=$HOSTNAME.neo4j.default.svc.cluster.local\n
dbms.connectors.default_listen_address=0.0.0.0\n
dbms.connector.bolt.type=BOLT\n
dbms.connector.bolt.enabled=true\n
dbms.connector.bolt.listen_address=0.0.0.0:7687\n
dbms.connector.http.type=HTTP\n
dbms.connector.http.enabled=true\n
dbms.connector.http.listen_address=0.0.0.0:7474\n
causal_clustering.raft_messages_log_enable=true\n
causal_clustering.initial_discovery_members=neo4j-0.neo4j.default.svc.cluster.local:5000,neo4j-1.neo4j.default.svc.cluster.local:5000,neo4j-2.neo4j.default.svc.cluster.local:5000\n
causal_clustering.leader_election_timeout=2s\n
\" > /work-dir/neo4j.conf" ],
"volumeMounts": [
{
"name": "confdir",
"mountPath": "/work-dir"
}
]
}
]'
labels:
app: neo4j
spec:
containers:
- name: neo4j
image: "neo4j/neo4j-experimental:3.1.0-M13-beta3-enterprise"
imagePullPolicy: Always
ports:
- containerPort: 5000
name: discovery
- containerPort: 6000
name: tx
- containerPort: 7000
name: raft
- containerPort: 7474
name: browser
- containerPort: 7687
name: bolt
securityContext:
privileged: true
volumeMounts:
- name: datadir
mountPath: /data
- name: confdir
mountPath: /conf
volumes:
- name: confdir
volumeClaimTemplates:
- metadata:
name: datadir
annotations:
volume.alpha.kubernetes.io/storage-class: anything
spec:
accessModes: [ "ReadWriteOnce" ]
resources:
requests:
storage: 1Gi
----
The main thing I had trouble with was getting the members of the cluster to talk to each other. The default docker config uses hostnames but I found that pods were unable to contact each other unless I specified the FQDN in the config file. We can run the following command to create the PetSet:
[source,bash]
----
$ kubectl create -f neo4j.yaml
service "neo4j" created
petset "neo4j" created
----
We can check if the pods are up and running by executing the following command:
[source,bash]
----
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
neo4j-0 1/1 Running 0 2m
neo4j-1 1/1 Running 0 14s
neo4j-2 1/1 Running 0 10s
----
And we can tail neo4j's log files like this:
[source,bash]
----
$ kubectl logs neo4j-0
Starting Neo4j.
2016-11-25 16:39:50.333+0000 INFO Starting...
2016-11-25 16:39:51.723+0000 INFO Bolt enabled on 0.0.0.0:7687.
2016-11-25 16:39:51.733+0000 INFO Initiating metrics...
2016-11-25 16:39:51.911+0000 INFO Waiting for other members to join cluster before continuing...
2016-11-25 16:40:12.074+0000 INFO Started.
2016-11-25 16:40:12.428+0000 INFO Mounted REST API at: /db/manage
2016-11-25 16:40:13.350+0000 INFO Remote interface available at http://neo4j-0.neo4j.default.svc.cluster.local:7474/
----
[source,bash]
----
$ kubectl logs neo4j-1
Starting Neo4j.
2016-11-25 16:39:53.846+0000 INFO Starting...
2016-11-25 16:39:56.212+0000 INFO Bolt enabled on 0.0.0.0:7687.
2016-11-25 16:39:56.225+0000 INFO Initiating metrics...
2016-11-25 16:39:56.341+0000 INFO Waiting for other members to join cluster before continuing...
2016-11-25 16:40:16.623+0000 INFO Started.
2016-11-25 16:40:16.951+0000 INFO Mounted REST API at: /db/manage
2016-11-25 16:40:17.607+0000 INFO Remote interface available at http://neo4j-1.neo4j.default.svc.cluster.local:7474/
----
[source,bash]
----
$ kubectl logs neo4j-2
Starting Neo4j.
2016-11-25 16:39:57.828+0000 INFO Starting...
2016-11-25 16:39:59.166+0000 INFO Bolt enabled on 0.0.0.0:7687.
2016-11-25 16:39:59.176+0000 INFO Initiating metrics...
2016-11-25 16:39:59.329+0000 INFO Waiting for other members to join cluster before continuing...
2016-11-25 16:40:19.216+0000 INFO Started.
2016-11-25 16:40:19.675+0000 INFO Mounted REST API at: /db/manage
2016-11-25 16:40:21.029+0000 INFO Remote interface available at http://neo4j-2.neo4j.default.svc.cluster.local:7474/
----
I wanted to log into the servers from my host machine's browser so I setup port forwarding for each of the servers:
[source,bash]
----
$ kubectl port-forward neo4j-0 7474:7474 7687:7687
----
We can then get an overview of the cluster by running the following procedure:
[source,bash]
----
CALL dbms.cluster.overview()
ββββββββββββββββββββββββββββββββββββββ€ββββββββββββββββββββββββββββββββββββββββββββββββββββββ€βββββββββ
βid βaddresses βrole β
ββββββββββββββββββββββββββββββββββββββͺββββββββββββββββββββββββββββββββββββββββββββββββββββββͺβββββββββ‘
β81d8e5e2-02db-4414-85de-a7025b346e84β[bolt://neo4j-0.neo4j.default.svc.cluster.local:7687,βLEADER β
β β http://neo4j-0.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
β347b7517-7ca0-4b92-b9f0-9249d46b2ad3β[bolt://neo4j-1.neo4j.default.svc.cluster.local:7687,βFOLLOWERβ
β β http://neo4j-1.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
βa5ec1335-91ce-4358-910b-8af9086c2969β[bolt://neo4j-2.neo4j.default.svc.cluster.local:7687,βFOLLOWERβ
β β http://neo4j-2.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββ
----
So far so good. What if we want to have 5 servers in the cluster instead of 3? We can run the following command to increase our replica size:
[source,bash]
----
$ kubectl patch petset neo4j -p '{"spec":{"replicas":5}}'
"neo4j" patched
----
Let's run that procedure again:
[source,bash]
----
CALL dbms.cluster.overview()
ββββββββββββββββββββββββββββββββββββββ€ββββββββββββββββββββββββββββββββββββββββββββββββββββββ€βββββββββ
βid βaddresses βrole β
ββββββββββββββββββββββββββββββββββββββͺββββββββββββββββββββββββββββββββββββββββββββββββββββββͺβββββββββ‘
β81d8e5e2-02db-4414-85de-a7025b346e84β[bolt://neo4j-0.neo4j.default.svc.cluster.local:7687,βLEADER β
β β http://neo4j-0.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
β347b7517-7ca0-4b92-b9f0-9249d46b2ad3β[bolt://neo4j-1.neo4j.default.svc.cluster.local:7687,βFOLLOWERβ
β β http://neo4j-1.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
βa5ec1335-91ce-4358-910b-8af9086c2969β[bolt://neo4j-2.neo4j.default.svc.cluster.local:7687,βFOLLOWERβ
β β http://neo4j-2.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
β28613d06-d4c5-461c-b277-ddb3f05e5647β[bolt://neo4j-3.neo4j.default.svc.cluster.local:7687,βFOLLOWERβ
β β http://neo4j-3.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
β2eaa0058-a4f3-4f07-9f22-d310562ad1ecβ[bolt://neo4j-4.neo4j.default.svc.cluster.local:7687,βFOLLOWERβ
β β http://neo4j-4.neo4j.default.svc.cluster.local:7474]β β
ββββββββββββββββββββββββββββββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββ
----
Neat! And it's as easy to go back down to 3 again:
[source,bash]
----
$ kubectl patch petset neo4j -p '{"spec":{"replicas":3}}'
"neo4j" patched
----
[source,bash]
----
CALL dbms.cluster.overview()
ββββββββββββββββββββββββββββββββββββββ€βββββββββββββββββββββββββββββββββββββββββββββββββββββββ€βββββββββ
βid βaddresses βrole β
ββββββββββββββββββββββββββββββββββββββͺβββββββββββββββββββββββββββββββββββββββββββββββββββββββͺβββββββββ‘
β81d8e5e2-02db-4414-85de-a7025b346e84β[bolt://neo4j-0.neo4j.default.svc.cluster.local:7687, βLEADER β
β βhttp://neo4j-0.neo4j.default.svc.cluster.local:7474] β β
ββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
β347b7517-7ca0-4b92-b9f0-9249d46b2ad3β[bolt://neo4j-1.neo4j.default.svc.cluster.local:7687, βFOLLOWERβ
β βhttp://neo4j-1.neo4j.default.svc.cluster.local:7474] β β
ββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββ€
βa5ec1335-91ce-4358-910b-8af9086c2969β[bolt://neo4j-2.neo4j.default.svc.cluster.local:7687, βFOLLOWERβ
β βhttp://neo4j-2.neo4j.default.svc.cluster.local:7474] β β
ββββββββββββββββββββββββββββββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββ
----
Next I need to look at how we can add read replicas into the cluster. These don't take part in the membership/quorum algorithm so I think I'll be able to use the more common ReplicationController/Pod architecture for those.
If you want to play around with this https://gist.github.com/mneedham/abd2e28e9ce3ce736ccc5895c7cfda6a[the code is available as a gist]. I'm using the https://github.com/kubernetes/minikube[minikube library] for all my experiments but I'll hopefully get around to trying this on GCE or AWS soon. | null | null | [
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0.039282407611608505,
0.051218703389167786,
-0.022263722494244576,
-0.0033845449797809124
] | kubernetes-spinning-up-a-neo4j-3-1-causal-cluster | https://markhneedham.com/blog/2016/11/25/kubernetes-spinning-up-a-neo4j-3-1-causal-cluster |
false | 2016-10-04 22:33:43 | Neo4j: requirement failed | [
"neo4j"
] | [
"neo4j"
] | Last week during a hands on Cypher meetup, using Neo4j's built in movie dataset, one of the attendees showed me the following query which wasn't working as expected:
[source,cypher]
----
MATCH (p:Person)-[:ACTED_IN]->(movie)
RETURN p, COLLECT(movie.title) AS movies
ORDER BY COUNT(movies) DESC
LIMIT 10
----
[source,text]
----
requirement failed
----
We can get a full stack trace in +++<cite>+++logs/debug.log+++</cite>+++ if we run the same query from the cypher-shell, which was introduced during one fo the Neo4j 3.1 milestone releases:
[source,text]
----
2016-10-03 23:25:07.529+0000 ERROR [o.n.b.v.r.ErrorReporter] Client triggered an unexpected error [UnknownError]: requirement failed, reference to. requirement failed
java.lang.IllegalArgumentException: requirement failed
at scala.Predef$.require(Predef.scala:212)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.steps.sortSkipAndLimit$.apply(sortSkipAndLimit.scala:38)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.PlanEventHorizon$.apply(PlanEventHorizon.scala:43)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.PlanEventHorizon$.apply(PlanEventHorizon.scala:31)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.PlanWithTail.apply(PlanWithTail.scala:46)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.PlanWithTail.apply(PlanWithTail.scala:29)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.PlanSingleQuery.apply(PlanSingleQuery.scala:47)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.PlanSingleQuery.apply(PlanSingleQuery.scala:30)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.DefaultQueryPlanner$$anonfun$2.apply(QueryPlanner.scala:51)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.DefaultQueryPlanner$$anonfun$2.apply(QueryPlanner.scala:51)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.DefaultQueryPlanner.planQueries(QueryPlanner.scala:51)
at org.neo4j.cypher.internal.compiler.v3_1.planner.logical.DefaultQueryPlanner.plan(QueryPlanner.scala:36)
at org.neo4j.cypher.internal.compiler.v3_1.planner.CostBasedExecutablePlanBuilder.produceLogicalPlan(CostBasedExecutablePlanBuilder.scala:95)
at org.neo4j.cypher.internal.compiler.v3_1.planner.CostBasedExecutablePlanBuilder$$anonfun$1.apply(CostBasedExecutablePlanBuilder.scala:71)
at org.neo4j.cypher.internal.compiler.v3_1.planner.CostBasedExecutablePlanBuilder$$anonfun$1.apply(CostBasedExecutablePlanBuilder.scala:71)
at org.neo4j.cypher.internal.compiler.v3_1.helpers.package$$anonfun$closing$1.apply(package.scala:29)
at org.neo4j.cypher.internal.compiler.v3_1.helpers.package$$anonfun$closing$1.apply(package.scala:29)
at org.neo4j.cypher.internal.compiler.v3_1.helpers.package$.using(package.scala:37)
at org.neo4j.cypher.internal.compiler.v3_1.helpers.package$.closing(package.scala:29)
at org.neo4j.cypher.internal.compiler.v3_1.planner.CostBasedExecutablePlanBuilder.producePlan(CostBasedExecutablePlanBuilder.scala:70)
at org.neo4j.cypher.internal.compiler.v3_1.executionplan.procs.DelegatingProcedureExecutablePlanBuilder.producePlan(DelegatingProcedureExecutablePlanBuilder.scala:99)
at org.neo4j.cypher.internal.compiler.v3_1.executionplan.FallbackBuilder$class.producePlan(SilentFallbackPlanBuilder.scala:37)
at org.neo4j.cypher.internal.compiler.v3_1.executionplan.SilentFallbackPlanBuilder.producePlan(SilentFallbackPlanBuilder.scala:56)
at org.neo4j.cypher.internal.compiler.v3_1.executionplan.ExecutionPlanBuilder.build(ExecutionPlanBuilder.scala:106)
at org.neo4j.cypher.internal.compiler.v3_1.CypherCompiler$$anonfun$5.apply(CypherCompiler.scala:176)
at org.neo4j.cypher.internal.compiler.v3_1.CypherCompiler$$anonfun$5.apply(CypherCompiler.scala:176)
at org.neo4j.cypher.internal.compiler.v3_1.QueryCache$$anonfun$getOrElseUpdate$1$$anonfun$apply$1.apply(CacheAccessor.scala:36)
at org.neo4j.cypher.internal.compiler.v3_1.MonitoringCacheAccessor$$anonfun$1.apply(CacheAccessor.scala:57)
at org.neo4j.cypher.internal.compiler.v3_1.LFUCache$$anon$1.apply(LFUCache.scala:31)
----
The problem line seems to be https://github.com/neo4j/neo4j/blob/0f1c7439d5ba2bf4bfbd2b990bf214b5a28406bf/community/cypher/cypher-compiler-3.1/src/main/scala/org/neo4j/cypher/internal/compiler/v3_1/planner/logical/steps/sortSkipAndLimit.scala#L38[this one]:
[source,scala]
----
require(sortItems.forall(_.expression.isInstanceOf[Variable]))
----
The solution is actually quite simple. We should be using the +++<cite>+++SIZE+++</cite>+++ function to calculate the size of a list rather then the +++<cite>+++COUNT+++</cite>+++ function:
[source,cypher]
----
MATCH (p:Person)-[:ACTED_IN]->(movie)
RETURN p, COLLECT(movie.title) AS movies
ORDER BY SIZE(movies) DESC
LIMIT 10
---- | null | null | [
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] | neo4j-requirement-failed | https://markhneedham.com/blog/2016/10/04/neo4j-requirement-failed |
false | 2016-10-02 10:13:26 | Neo4j: Procedure call inside a query does not support passing arguments implicitly (pass explicitly after procedure name instead) | [
"neo4j",
"cypher"
] | [
"neo4j"
] | A couple of days I was trying to write a Cypher query to filter the labels in my database.
I started with the following procedure call to get the list of all the labels:
[source,cypher]
----
CALL db.labels
----
[source,text]
----
ββββββββββββ
βlabel β
ββββββββββββ‘
βAirport β
ββββββββββββ€
βFlight β
ββββββββββββ€
βAirline β
ββββββββββββ€
βMovie β
ββββββββββββ€
βAirportDayβ
ββββββββββββ€
βPerson β
ββββββββββββ€
βEngineer β
ββββββββββββ
----
I was only interested in labels that contained the letter 'a' so I tweaked the query to filter the output of the procedure:
[source,cypher]
----
CALL db.labels
YIELD label
WITH label WHERE tolower(label) contains "a"
RETURN label
----
Unfortunately that didn't work as I expected:
[source,text]
----
Procedure call inside a query does not support passing arguments implicitly (pass explicitly after procedure name instead) (line 1, column 9 (offset: 8))
"CALL db.labels"
^
----
The mistake I made was calling the procedure implicitly without using parentheses. If you want to do any post processing on the output of a procedure you need to call it explicitly otherwise Cypher gets very confused.
If we add back the parentheses it's much happier:
[source,cypher]
----
CALL db.labels()
YIELD label
WITH label WHERE tolower(label) contains "a"
RETURN label
----
[source,text]
----
ββββββββββββ
βlabel β
ββββββββββββ‘
βAirport β
ββββββββββββ€
βAirline β
ββββββββββββ€
βAirportDayβ
ββββββββββββ
----
It stumped me for a while until I figured out what the error message meant! I think I'll just use explicit parentheses all the time from now on to save me running into this one again. | null | null | [
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] | neo4j-procedure-call-inside-a-query-does-not-support-passing-arguments-implicitly-pass-explicitly-after-procedure-name-instead | https://markhneedham.com/blog/2016/10/02/neo4j-procedure-call-inside-a-query-does-not-support-passing-arguments-implicitly-pass-explicitly-after-procedure-name-instead |
false | 2016-10-27 05:29:30 | Neo4j: Dynamically add property/Set dynamic property | [
"neo4j"
] | [
"neo4j"
] | I've been playing around with a dataset which has the timetable for the national rail in the UK and they give you departure and arrival times of each train in a textual format.
For example, the node to represent a stop could be created like this:
[source,cypher]
----
CREATE (stop:Stop {arrival: "0802", departure: "0803H"})
----
That time format isn't particular amenable to querying so I wanted to add another property which indicated the number of seconds since the start of the day.
So we want to add 'arrivalSecondsSinceStartOfDay' and 'departureSecondsSinceStartOfDay' properties to our node. I wrote the following query to calculate the values for those properties.
[source,cypher]
----
MATCH (stop:Stop)
UNWIND ["arrival", "departure"] AS key
WITH key,
toInteger(substring(stop[key], 0, 2)) AS hours,
toInteger(substring(stop[key], 2, 2)) AS minutes,
CASE WHEN substring(stop[key], 4,1) = "H" THEN 30 ELSE 0 END AS seconds
WITH key, (hours * 60 * 60) + (minutes * 60) + seconds AS secondsSinceStartOfDay
RETURN key + "SecondsSinceStartOfDay" AS newKey, secondsSinceStartOfDay
----
[source,text]
----
βββββββββββββββββββββββββββββββββ€βββββββββββββββββββββββ
βnewKey βsecondsSinceStartOfDayβ
βββββββββββββββββββββββββββββββββͺβββββββββββββββββββββββ‘
βarrivalSecondsSinceStartOfDay β28920 β
βββββββββββββββββββββββββββββββββΌβββββββββββββββββββββββ€
βdepartureSecondsSinceStartOfDayβ29010 β
βββββββββββββββββββββββββββββββββ΄βββββββββββββββββββββββ
----
Now we're ready to set those properties on the 'stop' node.
[source,cypher]
----
MATCH (stop:Stop2)
UNWIND ["arrival", "departure"] AS key
WITH stop,
key,
toInteger(substring(stop[key], 0, 2)) AS hours,
toInteger(substring(stop[key], 2, 2)) AS minutes,
CASE WHEN substring(stop[key], 4,1) = "H" THEN 30 ELSE 0 END AS seconds
WITH stop, key, (hours * 60 * 60) + (minutes * 60) + seconds AS secondsSinceStartOfDay
WITH stop, key + "SecondsSinceStartOfDay" AS newKey, secondsSinceStartOfDay
SET stop[newKey] = secondsSinceStartOfDay
----
[source,text]
----
Invalid input '[': expected an identifier character, whitespace, '{', node labels, a property map, a relationship pattern, '.', '(', '=' or "+=" (line 12, column 9 (offset: 447))
"SET stop[newKey] = secondsSinceStartOfDay"
^
----
Hmmm that didn't work as expected! It doesn't look like we can set dynamic properties using Cypher just yet.
Luckily my colleague Michael Hunger and the Neo4j community have been curating the https://neo4j-contrib.github.io/neo4j-apoc-procedures/[APOC procedures library] and it has just the procedure to help us out.
You'll need to https://github.com/neo4j-contrib/neo4j-apoc-procedures/releases[download the jar] for your version of Neo4j and then place it in the +++<cite>+++plugins+++</cite>+++ directory. I'm using Neo4j 3.1 Beta1 so this is what it looks like for me:
[source,bash]
----
$ tree neo4j-enterprise-3.1.0-BETA1/plugins/
neo4j-enterprise-3.1.0-BETA1/plugins/
βββ apoc-3.1.0.1-all.jar
0 directories, 1 file
----
After you've done that you'll need to restart Neo4j so that it can pick up the new procedures that we've added. Once you've done that execute the following query to check they've installed correctly:
[source,cypher]
----
call dbms.procedures()
YIELD name
WITH name
WHERE name STARTS WITH "apoc"
RETURN COUNT(*)
----
[source,text]
----
ββββββββββ
βCOUNT(*)β
ββββββββββ‘
β183 β
ββββββββββ
----
We're now ready to dynamically set properties in the graph. The procedure that we'll use is +++<cite>+++apoc.create.setProperty+++</cite>+++ and it's easy to update our query to use it:
[source,cypher]
----
MATCH (stop:Stop)
UNWIND ["arrival", "departure"] AS key
WITH stop,
key,
toInteger(substring(stop[key], 0, 2)) AS hours,
toInteger(substring(stop[key], 2, 2)) AS minutes,
CASE WHEN substring(stop[key], 4,1) = "H" THEN 30 ELSE 0 END AS seconds
WITH stop, key, (hours * 60 * 60) + (minutes * 60) + seconds AS secondsSinceStartOfDay
WITH stop, key + "SecondsSinceStartOfDay" AS newKey, secondsSinceStartOfDay
CALL apoc.create.setProperty(stop, newKey, secondsSinceStartOfDay)
----
[source,text]
----
Query cannot conclude with CALL (must be RETURN or an update clause) (line 12, column 1 (offset: 439))
"CALL apoc.create.setProperty(stop, newKey, secondsSinceStartOfDay)"
^
----
Oops I spoke too soon! We need to yield the return column of the procedure and return it or just return a count to work around this:
[source,cypher]
----
MATCH (stop:Stop)
UNWIND ["arrival", "departure"] AS key
WITH stop,
key,
toInteger(substring(stop[key], 0, 2)) AS hours,
toInteger(substring(stop[key], 2, 2)) AS minutes,
CASE WHEN substring(stop[key], 4,1) = "H" THEN 30 ELSE 0 END AS seconds
WITH stop, key, (hours * 60 * 60) + (minutes * 60) + seconds AS secondsSinceStartOfDay
WITH stop, key + "SecondsSinceStartOfDay" AS newKey, secondsSinceStartOfDay
CALL apoc.create.setProperty(stop, newKey, secondsSinceStartOfDay)
YIELD node
RETURN COUNT(*)
----
[source,text]
----
ββββββββββ
βCOUNT(*)β
ββββββββββ‘
β2 β
ββββββββββ
----
And that's it, we can now dynamically set properties in our queries. | null | null | [
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] | neo4j-dynamically-add-property | https://markhneedham.com/blog/2016/10/27/neo4j-dynamically-add-property |
false | 2016-10-19 05:16:07 | Neo4j: Detecting rogue spaces in CSV headers with LOAD CSV | [
"neo4j"
] | [
"neo4j"
] | Last week I was helping someone load the data from a CSV file into Neo4j and we were having trouble filtering out rows which contained a null value in one of the columns.
This is what the data looked like:
[source,cypher]
----
load csv with headers from "file:///foo.csv" as row
RETURN row
----
[source,text]
----
ββββββββββββββββββββββββββββββββββββ
βrow β
ββββββββββββββββββββββββββββββββββββ‘
β{key1: a, key2: (null), key3: c}β
ββββββββββββββββββββββββββββββββββββ€
β{key1: d, key2: e, key3: f} β
ββββββββββββββββββββββββββββββββββββ
----
We'd like to filter out any rows which have 'key2' as null, so let's tweak our query to do that:
[source,cypher]
----
load csv with headers from "file:///foo.csv" as row
WITH row WHERE NOT row.key2 is null
RETURN row
----
[source,text]
----
(no rows)
----
Hmmm that's odd, it's got rid of both rows. We'd expect to see the 2nd row since that doesn't have a null value.
At this point we might suspect that what we're seeing on the screen isn't actually what the data looks like. Let's write the following query to check our header values:
[source,cypher]
----
load csv with headers from "file:///foo.csv" as row
WITH row LIMIT 1
UNWIND keys(row) AS key
RETURN key, SIZE(key)
----
[source,text]
----
βββββββ€ββββββββββ
βkey βSIZE(key)β
βββββββͺββββββββββ‘
βkey1 β4 β
βββββββΌββββββββββ€
β key2β5 β
βββββββΌββββββββββ€
β key3β5 β
βββββββ΄ββββββββββ
----
The second column tells us that there are some extra characters in the columns for 'key2' and 'key3' or rather ' key2' and ' key3'. In this case they are spaces, but it could easily be another character:
[source,cypher]
----
load csv with headers from "file:///foo.csv" as row
WITH row LIMIT 1
UNWIND keys(row) AS key
RETURN key, replace(key, " ", "_SPACE_") AS spaces
----
[source,text]
----
βββββββ€ββββββββββββ
βkey βspaces β
βββββββͺββββββββββββ‘
βkey1 βkey1 β
βββββββΌββββββββββββ€
β key2β_SPACE_key2β
βββββββΌββββββββββββ€
β key3β_SPACE_key3β
βββββββ΄ββββββββββββ
----
If we clean up our CSV file and try again everything works as expected:
[source,cypher]
----
load csv with headers from "file:///foo.csv" as row
WITH row LIMIT 1
UNWIND keys(row) AS key
RETURN key, SIZE(key)
----
[source,text]
----
ββββββ€ββββββββββ
βkey βSIZE(key)β
ββββββͺββββββββββ‘
βkey1β4 β
ββββββΌββββββββββ€
βkey2β4 β
ββββββΌββββββββββ€
βkey3β4 β
ββββββ΄ββββββββββ
----
[source,cypher]
----
load csv with headers from "file:///foo.csv" as row
WITH row WHERE NOT row.key2 is null
RETURN row
----
[source,text]
----
βββββββββββββββββββββββββββββ
βrow β
βββββββββββββββββββββββββββββ‘
β{key1: d, key2: e, key3: f}β
βββββββββββββββββββββββββββββ
---- | null | null | [
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] | neo4j-detecting-rogue-spaces-in-csv-headers-with-load-csv | https://markhneedham.com/blog/2016/10/19/neo4j-detecting-rogue-spaces-in-csv-headers-with-load-csv |
false | 2016-10-31 19:31:46 | Neo4j: Find the midpoint between two lat/longs | [
"neo4j",
"cypher"
] | [
"neo4j"
] | image::{{<siteurl>}}/uploads/2016/10/2016-10-31_06-06-00.png[2016 10 31 06 06 00,118]
Over the last couple of weekends I've been playing around with some transport data and I wanted to run the A* algorithm to find the quickest route between two stations.
The A* algorithm takes an +++<cite>+++estimateEvaluator+++</cite>+++ as one of its parameters and the evaluator looks at lat/longs of nodes to work out whether a path is worth following or not. I therefore needed to add lat/longs for each station and I found it surprisingly hard to find this location date for all the points in the dataset.
Luckily I tend to have the lat/longs for two points either side of a station so I can work out the midpoint as an approximation for the missing one.
I found http://www.movable-type.co.uk/scripts/latlong.html#midpoint[an article which defines a formula] we can use to do this and there's http://stackoverflow.com/questions/4656802/midpoint-between-two-latitude-and-longitude[a StackOverflow post] which has some Java code that implements the formula.
I wanted to find the midpoint between Surrey Quays station (51.4931963543,-0.0475185810) and a point further south on the train line (51.47908,-0.05393950). I wrote the following Cypher query to calculate this point:
[source,cypher]
----
WITH 51.4931963543 AS lat1, -0.0475185810 AS lon1,
51.47908 AS lat2 , -0.05393950 AS lon2
WITH radians(lat1) AS rlat1, radians(lon1) AS rlon1,
radians(lat2) AS rlat2, radians(lon2) AS rlon2,
radians(lon2 - lon1) AS dLon
WITH rlat1, rlon1, rlat2, rlon2,
cos(rlat2) * cos(dLon) AS Bx,
cos(rlat2) * sin(dLon) AS By
WITH atan2(sin(rlat1) + sin(rlat2),
sqrt( (cos(rlat1) + Bx) * (cos(rlat1) + Bx) + By * By )) AS lat3,
rlon1 + atan2(By, cos(rlat1) + Bx) AS lon3
RETURN degrees(lat3) AS midLat, degrees(lon3) AS midLon
----
[source,text]
----
βββββββββββββββββββ€ββββββββββββββββββββββ
βmidLat βmidLon β
βββββββββββββββββββͺββββββββββββββββββββββ‘
β51.48613822097523β-0.050729537454086385β
βββββββββββββββββββ΄ββββββββββββββββββββββ
----
The Google Maps screenshot on the right hand side shows the initial points at the top and bottom and the midpoint in between. It's not perfect; ideally I'd like the midpoint to be on the track, but I think it's good enough for the purposes of the algorithm.
Now I need to go and fill in the lat/longs for my location-less stations! | null | null | [
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] | neo4j-find-the-midpoint-between-two-latlongs | https://markhneedham.com/blog/2016/10/31/neo4j-find-the-midpoint-between-two-latlongs |
false | 2016-10-30 22:12:50 | Neo4j: Create dynamic relationship type | [
"neo4j",
"apoc",
"cypher"
] | [
"neo4j"
] | One of the things I've often found frustrating when importing data using Cypher, Neo4j's query language, is that it's quite difficult to create dynamic relationship types.
Say we have a CSV file structured like this:
[source,cypher]
----
load csv with headers from "file:///people.csv" AS row
RETURN row
----
[source,text]
----
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
βrow β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ‘
β{node1: Mark, node2: Reshmee, relationship: MARRIED_TO}β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β{node1: Mark, node2: Alistair, relationship: FRIENDS} β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
----
We want to create nodes with the relationship type specified in the file. Unfortunately, in Cypher we can't pass in relationship types so we have to resort to the FOREACH hack to create our relationships:
[source,cypher]
----
load csv with headers from "file:///people.csv" AS row
MERGE (p1:Person {name: row.node1})
MERGE (p2:Person {name: row.node2})
FOREACH(ignoreMe IN CASE WHEN row.relationship = "MARRIED_TO" THEN [1] ELSE [] END |
MERGE (p1)-[:MARRIED_TO]->(p2))
FOREACH(ignoreMe IN CASE WHEN row.relationship = "FRIENDS" THEN [1] ELSE [] END |
MERGE (p1)-[:FRIENDS]->(p2))
----
This works, but:
. Looks horrendous
. Doesn't scale particularly well when we have multiple relationship types to deal with
As http://www.markhneedham.com/blog/2016/10/27/neo4j-dynamically-add-property/[in my last post] the https://neo4j-contrib.github.io/neo4j-apoc-procedures/[APOC library] comes to the rescue again, this time in the form of the +++<cite>+++apoc.create.relationship+++</cite>+++ procedure.
This procedure allows us to change our initial query to read like this:
[source,cypher]
----
load csv with headers from "file:///people.csv" AS row
MERGE (p1:Person {name: row.node1})
MERGE (p2:Person {name: row.node2})
WITH p1, p2, row
CALL apoc.create.relationship(p1, row.relationship, {}, p2) YIELD rel
RETURN rel
----
Much better! | null | null | [
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] | neo4j-create-dynamic-relationship-type | https://markhneedham.com/blog/2016/10/30/neo4j-create-dynamic-relationship-type |
false | 2016-07-20 17:32:19 | Neo4j: Cypher - Detecting duplicates using relationships | [
"neo4j",
"cypher"
] | [
"neo4j"
] | I've been building a graph of computer science papers on and off for a couple of months and now that I've got a few thousand loaded in I realised that there are quite a few duplicates.
They're not duplicates in the sense that there are multiple entries with the same identifier but rather have different identifiers but seem to be the same paper!
e.g. there are a couple of papers titled 'Authentication in the Taos operating system':
http://dl.acm.org/citation.cfm?id=174614
image::{{<siteurl>}}/uploads/2016/07/2016-07-20_11-43-00.png[2016 07 20 11 43 00]
http://dl.acm.org/citation.cfm?id=168640
image::{{<siteurl>}}/uploads/2016/07/2016-07-20_11-43-38.png[2016 07 20 11 43 38]
This is the same paper published in two different journals as far as I can tell.
Now in this case it's quite easy to just do a string similarity comparison of the titles of these papers and realise that they're identical. I've previously use the excellent https://github.com/datamade/dedupe[dedupe] library to do this and there's also an http://www.slideshare.net/DECK36/deck36-bbuzz2014datadedupsteschasfinal?related=1[excellent talk from Berlin Buzzwords 2014 where the author uses locality-sensitive hashing] to achieve a similar outcome.
However, I was curious whether I could use any of the relationships these papers have to detect duplicates rather than just relying on string matching.
This is what the graph looks like:
image::{{<siteurl>}}/uploads/2016/07/graph-8.png[Graph 8,269]
We'll start by writing a query to see how many common references the different Taos papers have:
[source,cypher]
----
MATCH (r:Resource {id: "168640"})-[:REFERENCES]->(other)
WITH r, COLLECT(other) as myReferences
UNWIND myReferences AS reference
OPTIONAL MATCH path = (other)-[:REFERENCES]->(reference)
WITH other, COUNT(path) AS otherReferences, SIZE(myReferences) AS myReferences
WITH other, 1.0 * otherReferences / myReferences AS similarity WHERE similarity > 0.5
RETURN other.id, other.title, similarity
ORDER BY similarity DESC
LIMIT 10
----
[source,text]
----
ββββββββββ€ββββββββββββββββββββββββββββββββββββββββββββ€βββββββββββ
βother.idβother.title βsimilarityβ
ββββββββββͺββββββββββββββββββββββββββββββββββββββββββββͺβββββββββββ‘
β168640 βAuthentication in the Taos operating systemβ1 β
ββββββββββΌββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββ€
β174614 βAuthentication in the Taos operating systemβ1 β
ββββββββββ΄ββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββββ
----
This query:
* picks one of the Taos papers and finds its references
* finds other papers which reference those same papers
* calculates a similarity score based on how many common references they have
* returns papers that have more than 50% of the same references with the most similar ones at the top
I tried it with other papers to see how it fared:
http://dl.acm.org/citation.cfm?id=74859[Performance of Firefly RPC]
[source,text]
----
ββββββββββ€βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€βββββββββββββββββββ
βother.idβother.title βsimilarity β
ββββββββββͺβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββͺβββββββββββββββββββ‘
β74859 βPerformance of Firefly RPC β1 β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β77653 βPerformance of the Firefly RPC β0.8333333333333334β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β110815 βThe X-Kernel: An Architecture for Implementing Network Protocolsβ0.6666666666666666β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β96281 βExperiences with the Amoeba distributed operating system β0.6666666666666666β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β74861 βLightweight remote procedure call β0.6666666666666666β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β106985 βThe interaction of architecture and operating system design β0.6666666666666666β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β77650 βLightweight remote procedure call β0.6666666666666666β
ββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββββββββββββ
----
http://dl.acm.org/citation.cfm?id=121160[Authentication in distributed systems: theory and practice]
[source,text]
----
ββββββββββ€βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€βββββββββββββββββββ
βother.idβother.title βsimilarity β
ββββββββββͺβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββͺβββββββββββββββββββ‘
β121160 βAuthentication in distributed systems: theory and practiceβ1 β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌβββββββββββββββββββ€
β138874 βAuthentication in distributed systems: theory and practiceβ0.9090909090909091β
ββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββββββββββββββββββ
----
Sadly it's not as simple as finding 100% matches on references! I expect the later revisions of a paper added more content and therefore additional references.
What if we look for author similarity as well?
[source,cypher]
----
MATCH (r:Resource {id: "121160"})-[:REFERENCES]->(other)
WITH r, COLLECT(other) as myReferences
UNWIND myReferences AS reference
OPTIONAL MATCH path = (other)-[:REFERENCES]->(reference)
WITH r, other, authorSimilarity, COUNT(path) AS otherReferences, SIZE(myReferences) AS myReferences
WITH r, other, authorSimilarity, 1.0 * otherReferences / myReferences AS referenceSimilarity
WHERE referenceSimilarity > 0.5
MATCH (r)<-[:AUTHORED]-(author)
WITH r, myReferences, COLLECT(author) AS myAuthors
UNWIND myAuthors AS author
OPTIONAL MATCH path = (other)<-[:AUTHORED]-(author)
WITH other, myReferences, COUNT(path) AS otherAuthors, SIZE(myAuthors) AS myAuthors
WITH other, myReferences, 1.0 * otherAuthors / myAuthors AS authorSimilarity
WHERE authorSimilarity > 0.5
RETURN other.id, other.title, referenceSimilarity, authorSimilarity
ORDER BY (referenceSimilarity + authorSimilarity) DESC
LIMIT 10
----
[source,text]
----
ββββββββββ€βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€ββββββββββββββββββββ€βββββββββββββββββ
βother.idβother.title βreferenceSimilarityβauthorSimilarityβ
ββββββββββͺβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββͺββββββββββββββββββββͺβββββββββββββββββ‘
β121160 βAuthentication in distributed systems: theory and practiceβ1 β1 β
ββββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββββββββββββββΌββββββββββββββββββββΌβββββββββββββββββ€
β138874 βAuthentication in distributed systems: theory and practiceβ0.9090909090909091 β1 β
ββββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄ββββββββββββββββββββ΄βββββββββββββββββ
----
[source,text]
----
ββββββββββ€βββββββββββββββββββββββββββββββ€ββββββββββββββββββββ€βββββββββββββββββ
βother.idβother.title βreferenceSimilarityβauthorSimilarityβ
ββββββββββͺβββββββββββββββββββββββββββββββͺββββββββββββββββββββͺβββββββββββββββββ‘
β74859 βPerformance of Firefly RPC β1 β1 β
ββββββββββΌβββββββββββββββββββββββββββββββΌββββββββββββββββββββΌβββββββββββββββββ€
β77653 βPerformance of the Firefly RPCβ0.8333333333333334 β1 β
ββββββββββ΄βββββββββββββββββββββββββββββββ΄ββββββββββββββββββββ΄βββββββββββββββββ
----
I'm sure I could find some other papers where neither of these similarities worked well but it's an interesting start.
I think the next step is to build up a training set of pairs of documents that are and aren't similar to each other. We could then train a classifier to determine whether two documents are identical.
But that's for another day! | null | null | [
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] | neo4j-cypher-detecting-duplicates-using-relationships | https://markhneedham.com/blog/2016/07/20/neo4j-cypher-detecting-duplicates-using-relationships |
false | 2016-07-27 02:45:28 | scikit-learn: TF/IDF and cosine similarity for computer science papers | [
"python"
] | [
"Python"
] | A couple of months ago I downloaded the meta data for a few thousand computer science papers so that I could try and write a mini recommendation engine to tell me what paper I should read next.
Since I don't have any data on which people read each paper a collaborative filtering approach is ruled out, so instead I thought I could try content based filtering instead.
Let's quickly check the https://en.wikipedia.org/wiki/Recommender_system#Content-based_filtering[Wikipedia definition of content based filtering]:
____
In a content-based recommender system, keywords are used to describe the items and a user profile is built to indicate the type of item this user likes. In other words, these algorithms try to recommend items that are similar to those that a user liked in the past (or is examining in the present).
____
We're going to focus on the finding similar items part of the algorithm and we'll start simple by calculating the similarity of items based on their titles. We'd probably get better results if we used the full text of the papers or at least the abstracts but that data isn't as available.
We're going to take the following approach to work out the similarity between any pair of papers:
[source,text]
----
for each paper:
generate a TF/IDF vector of the terms in the paper's title
calculate the cosine similarity of each paper's TF/IDF vector with every other paper's TF/IDF vector
----
This is very easy to do using the Python scikit-learn library and I've actually done the first part of the process while doing some http://www.markhneedham.com/blog/2015/02/15/pythonscikit-learn-calculating-tfidf-on-how-i-met-your-mother-transcripts/[exploratory analysis of interesting phrases in the TV show How I Met Your Mother].
Let's get started.
We've got one file per paper which contains the title of the paper. We first need to iterate through that directory and build an array containing the papers:
[source,python]
----
import glob
corpus = []
for file in glob.glob("papers/*.txt"):
with open(file, "r") as paper:
corpus.append((file, paper.read()))
----
Next we'll build a TF/IDF matrix for each paper:
[source,python]
----
from sklearn.feature_extraction.text import TfidfVectorizer
tf = TfidfVectorizer(analyzer='word', ngram_range=(1,3), min_df = 0, stop_words = 'english')
tfidf_matrix = tf.fit_transform([content for file, content in corpus])
----
Next we'll write a function that will find us the top n similar papers based on cosine similarity:
[source,python]
----
from sklearn.metrics.pairwise import linear_kernel
def find_similar(tfidf_matrix, index, top_n = 5):
cosine_similarities = linear_kernel(tfidf_matrix[index:index+1], tfidf_matrix).flatten()
related_docs_indices = [i for i in cosine_similarities.argsort()[::-1] if i != index]
return [(index, cosine_similarities[index]) for index in related_docs_indices][0:top_n]
----
Let's try it out:
[source,python]
----
>>> corpus[1619]
('papers/221215.txt', 'TOTEM: a reliable ordered delivery protocol for interconnected local-area networks')
>>> for index, score in find_similar(tfidf_matrix, 1619):
print score, corpus[index]
0.917540397202 ('papers/852338.txt', 'A reliable ordered delivery protocol for interconnected local area networks')
0.248736845733 ('papers/800897.txt', 'Interconnection of broadband local area networks')
0.207309089025 ('papers/103726.txt', 'High-speed local area networks and their performance: a survey')
0.204166719869 ('papers/161736.txt', 'High-speed switch scheduling for local-area networks')
0.198514433132 ('papers/627363.txt', 'Algorithms for Distributed Query Processing in Broadcast Local Area Networks')
----
It's pretty good for finding duplicate papers!
[source,python]
----
>>> corpus[1599]
('papers/217470.txt', 'A reliable multicast framework for light-weight sessions and application level framing')
>>> for index, score in find_similar(tfidf_matrix, 1599):
print score, corpus[index]
1.0 ('papers/270863.txt', 'A reliable multicast framework for light-weight sessions and application level framing')
0.139643354066 ('papers/218325.txt', 'The KryptoKnight family of light-weight protocols for authentication and key distribution')
0.134763799612 ('papers/1251445.txt', 'ALMI: an application level multicast infrastructure')
0.117630311817 ('papers/125160.txt', 'Ordered and reliable multicast communication')
0.117630311817 ('papers/128741.txt', 'Ordered and reliable multicast communication')
----
But sometimes it identifies duplicates that aren't identical:
[source,python]
----
>>> corpus[5784]
('papers/RFC2616.txt', 'Hypertext Transfer Protocol -- HTTP/1.1')
>>> for index, score in find_similar(tfidf_matrix, 5784):
print score, corpus[index]
1.0 ('papers/RFC1945.txt', 'Hypertext Transfer Protocol -- HTTP/1.0')
1.0 ('papers/RFC2068.txt', 'Hypertext Transfer Protocol -- HTTP/1.1')
0.232865694216 ('papers/131844.txt', 'XTP: the Xpress Transfer Protocol')
0.138876842331 ('papers/RFC1866.txt', 'Hypertext Markup Language - 2.0')
0.104775586915 ('papers/760249.txt', 'On the transfer of control between contexts')
----
Having said that, if you were reading and liked the HTTP 1.0 RFC the HTTP 1.1 RFC probably isn't a bad recommendation.
There are obviously also some papers that get identified as being similar which aren't. I created https://github.com/mneedham/computer-science-papers/blob/master/similarities.csv[a CSV file] containing 5 similar papers for each paper as long as the similarity is greater than 0.5. You can see https://github.com/mneedham/computer-science-papers/blob/master/most_similar.py[the script that generates that file] on github as well.
That's as far as I've got for now but there are a couple of things I'm going to explore next:
* How do we know if the similarity suggestions are any good? How do we measure good? Would using a term counting vector work better than TF/IDF?
* Similarity based on abstracts as well as/instead of titles
https://github.com/mneedham/computer-science-papers/blob/master/similarity.py[All the code from this post] for calculating similarities and writing them to CSV is on github as well so feel free to play around with it. | null | null | [
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] | scitkit-learn-tfidf-and-cosine-similarity-for-computer-science-papers | https://markhneedham.com/blog/2016/07/27/scitkit-learn-tfidf-and-cosine-similarity-for-computer-science-papers |
false | 2016-07-11 05:21:43 | Neo4j 3.0 Drivers - Failed to save the server ID and the certificate received from the server | [
"neo4j"
] | [
"neo4j"
] | I've been using the https://neo4j.com/developer/java/[Neo4j Java Driver] on various local databases over the past week and ran into the following certificate problem a few times:
[source,text]
----
org.neo4j.driver.v1.exceptions.ClientException: Unable to process request: General SSLEngine problem
at org.neo4j.driver.internal.connector.socket.SocketClient.start(SocketClient.java:88)
at org.neo4j.driver.internal.connector.socket.SocketConnection.<init>(SocketConnection.java:63)
at org.neo4j.driver.internal.connector.socket.SocketConnector.connect(SocketConnector.java:52)
at org.neo4j.driver.internal.pool.InternalConnectionPool.acquire(InternalConnectionPool.java:113)
at org.neo4j.driver.internal.InternalDriver.session(InternalDriver.java:53)
Caused by: javax.net.ssl.SSLHandshakeException: General SSLEngine problem
at sun.security.ssl.Handshaker.checkThrown(Handshaker.java:1431)
at sun.security.ssl.SSLEngineImpl.checkTaskThrown(SSLEngineImpl.java:535)
at sun.security.ssl.SSLEngineImpl.writeAppRecord(SSLEngineImpl.java:1214)
at sun.security.ssl.SSLEngineImpl.wrap(SSLEngineImpl.java:1186)
at javax.net.ssl.SSLEngine.wrap(SSLEngine.java:469)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.wrap(TLSSocketChannel.java:270)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.runHandshake(TLSSocketChannel.java:131)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.<init>(TLSSocketChannel.java:95)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.<init>(TLSSocketChannel.java:77)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.<init>(TLSSocketChannel.java:70)
at org.neo4j.driver.internal.connector.socket.SocketClient$ChannelFactory.create(SocketClient.java:251)
at org.neo4j.driver.internal.connector.socket.SocketClient.start(SocketClient.java:75)
... 14 more
Caused by: javax.net.ssl.SSLHandshakeException: General SSLEngine problem
at sun.security.ssl.Alerts.getSSLException(Alerts.java:192)
at sun.security.ssl.SSLEngineImpl.fatal(SSLEngineImpl.java:1728)
at sun.security.ssl.Handshaker.fatalSE(Handshaker.java:304)
at sun.security.ssl.Handshaker.fatalSE(Handshaker.java:296)
at sun.security.ssl.ClientHandshaker.serverCertificate(ClientHandshaker.java:1497)
at sun.security.ssl.ClientHandshaker.processMessage(ClientHandshaker.java:212)
at sun.security.ssl.Handshaker.processLoop(Handshaker.java:979)
at sun.security.ssl.Handshaker$1.run(Handshaker.java:919)
at sun.security.ssl.Handshaker$1.run(Handshaker.java:916)
at java.security.AccessController.doPrivileged(Native Method)
at sun.security.ssl.Handshaker$DelegatedTask.run(Handshaker.java:1369)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.runDelegatedTasks(TLSSocketChannel.java:142)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.unwrap(TLSSocketChannel.java:203)
at org.neo4j.driver.internal.connector.socket.TLSSocketChannel.runHandshake(TLSSocketChannel.java:127)
... 19 more
Caused by: java.security.cert.CertificateException: Unable to connect to neo4j at `localhost:10003`, because the certificate the server uses has changed. This is a security feature to protect against man-in-the-middle attacks.
If you trust the certificate the server uses now, simply remove the line that starts with `localhost:10003` in the file `/Users/markneedham/.neo4j/known_hosts`.
The old certificate saved in file is:
-----BEGIN CERTIFICATE-----
7770ee598be69c8537b0e576e62442c84400008ca0d3e3565b379b7cce9a51de
0fd4396251df2e8da50eb1628d44dcbca3fae5c8fb9c0adc29396839c25eb0c8
-----END CERTIFICATE-----
The New certificate received is:
-----BEGIN CERTIFICATE-----
01a422739a39625ee95a0547fa99c7e43fbb33c70ff720e5ae4a8408421aa63b
2fe4f5d6094c5fd770ed1ad214dbdc428a6811d0955ed80d48cc67d84067df2c
-----END CERTIFICATE-----
at org.neo4j.driver.internal.connector.socket.TrustOnFirstUseTrustManager.checkServerTrusted(TrustOnFirstUseTrustManager.java:153)
at sun.security.ssl.AbstractTrustManagerWrapper.checkServerTrusted(SSLContextImpl.java:936)
at sun.security.ssl.ClientHandshaker.serverCertificate(ClientHandshaker.java:1484)
... 28 more
----
I got a bit lazy and just nuked the file it mentions in the error message - +++<cite>+++/Users/markneedham/.neo4j/known_hosts+++</cite>+++ - which led to this error the next time I call the driver in my application:
[source,text]
----
Failed to save the server ID and the certificate received from the server to file /Users/markneedham/.neo4j/known_hosts.
Server ID: localhost:10003
Received cert:
-----BEGIN CERTIFICATE-----
933c7ec5d6a1b876bd186dc6d05b04478ae771262f07d26a4d7d2e6b7f71054c
3e6b7c172474493b7fe93170d940b9cc3544661c7966632361649f2fda7c66be
-----END CERTIFICATE-----
----
I recreated the file with no content and tried again and it worked fine. Alternatively we can choose to turn off encryption when working with local databases and avoid the issue:
[source,java]
----
Config config = Config.build().withEncryptionLevel( Config.EncryptionLevel.NONE ).toConfig();
try ( Driver driver = GraphDatabase.driver( "bolt://localhost:7687", config );
Session session = driver.session() )
{
// use the driver
}
---- | null | null | [
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] | neo4j-3-0-drivers-failed-to-save-the-server-id-and-the-certificate-received-from-the-server | https://markhneedham.com/blog/2016/07/11/neo4j-3-0-drivers-failed-to-save-the-server-id-and-the-certificate-received-from-the-server |
false | 2016-07-11 06:01:22 | Python: Scraping elements relative to each other with BeautifulSoup | [
"python"
] | [
"Python"
] | Last week we hosted a Game of Thrones based intro to Cypher at the http://www.meetup.com/Women-Who-Code-London/events/231014802/[Women Who Code London meetup] and in preparation had to scrape http://gameofthrones.wikia.com/wiki[the wiki] to build a dataset.
I've built lots of datasets this way and it's a painless experience as long as the pages make liberal use of CSS classes and/or IDs.
Unfortunately the Game of Thrones wiki doesn't really do that so I had to find another way to extract the data I wanted - extracting elements *based on their position to more prominent elements on the page*.
For example, I wanted to extract http://gameofthrones.wikia.com/wiki/Arya_Stark[Arya Stark]'s allegiances which look like this on the page:
image::{{<siteurl>}}/uploads/2016/07/2016-07-11_06-45-37.png[2016 07 11 06 45 37,596]
We don't have a direct route to her allegiances but we do have an indirect path via the h3 element with the text 'Allegiance'.
The following code gets us the 'Allegiance' element:
[source,python]
----
from bs4 import BeautifulSoup
file_name = "Arya_Stark"
wikia = BeautifulSoup(open("data/wikia/characters/{0}".format(file_name), "r"), "html.parser")
allegiance_element = [tag for tag in wikia.find_all('h3') if tag.text == "Allegiance"]
> print allegiance_element
[<h3 class="pi-data-label pi-secondary-font">Allegiance</h3>]
----
Now we need to work out the relative position of the div containing the houses. It's inside the same parent div so I thought it'd probably be the next sibling:
[source,python]
----
next_element = allegiance_element[0].next_sibling
> print next_element
----
Nope. Nothing! Hmmm, wonder why:
[source,python]
----
> print next_element.name, type(next_element)
None <class 'bs4.element.NavigableString'>
----
Ah, empty string. Maybe it's the one after that?
[source,python]
----
next_element = allegiance_element[0].next_sibling.next_sibling
> print next_element.name, type(next_element)
[<a href="/wiki/House_Stark" title="House Stark">House Stark</a>, <br/>, <a href="/wiki/Faceless_Men" title="Faceless Men">Faceless Men</a>, u' (Formerly)']
----
Hoorah! Afer this it became a case of working out how the text was structure and pulling out what I wanted.
https://github.com/mneedham/neo4j-got/blob/master/scrape_characters.py[The code I ended up with is on github] if you want to recreate it yourself. | null | null | [
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] | python-scraping-elements-relative-to-each-other-with-beautifulsoup | https://markhneedham.com/blog/2016/07/11/python-scraping-elements-relative-to-each-other-with-beautifulsoup |
false | 2016-07-21 17:57:41 | Mahout: Exception in thread "main" java.lang.IllegalArgumentException: Wrong FS: file:/... expected: hdfs:// | [
"machine-learning-2",
"mahout"
] | [
"Hadoop"
] | I've been playing around with Mahout over the last couple of days to see how well it works for content based filtering.
I started following http://stackoverflow.com/questions/22789986/does-mahout-provide-a-way-to-determine-similarity-between-content-for-content-b/22830903#22830903[a mini tutorial from Stack Overflow] but ran into trouble on the first step:
[source,bash]
----
bin/mahout seqdirectory \
--input file:///Users/markneedham/Downloads/apache-mahout-distribution-0.12.2/foo \
--output file:///Users/markneedham/Downloads/apache-mahout-distribution-0.12.2/foo-out \
-c UTF-8 \
-chunk 64 \
-prefix mah
----
[source,bash]
----
16/07/21 21:19:20 INFO AbstractJob: Command line arguments: {--charset=[UTF-8], --chunkSize=[64], --endPhase=[2147483647], --fileFilterClass=[org.apache.mahout.text.PrefixAdditionFilter], --input=[file:///Users/markneedham/Downloads/apache-mahout-distribution-0.12.2/foo], --keyPrefix=[mah], --method=[mapreduce], --output=[file:///Users/markneedham/Downloads/apache-mahout-distribution-0.12.2/foo-out], --startPhase=[0], --tempDir=[temp]}
16/07/21 21:19:20 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/07/21 21:19:20 INFO deprecation: mapred.input.dir is deprecated. Instead, use mapreduce.input.fileinputformat.inputdir
16/07/21 21:19:20 INFO deprecation: mapred.compress.map.output is deprecated. Instead, use mapreduce.map.output.compress
16/07/21 21:19:20 INFO deprecation: mapred.output.dir is deprecated. Instead, use mapreduce.output.fileoutputformat.outputdir
Exception in thread "main" java.lang.IllegalArgumentException: Wrong FS: file:/Users/markneedham/Downloads/apache-mahout-distribution-0.12.2/foo, expected: hdfs://localhost:8020
at org.apache.hadoop.fs.FileSystem.checkPath(FileSystem.java:646)
at org.apache.hadoop.hdfs.DistributedFileSystem.getPathName(DistributedFileSystem.java:194)
at org.apache.hadoop.hdfs.DistributedFileSystem.access$000(DistributedFileSystem.java:106)
at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1305)
at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1301)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1301)
at org.apache.mahout.text.SequenceFilesFromDirectory.runMapReduce(SequenceFilesFromDirectory.java:156)
at org.apache.mahout.text.SequenceFilesFromDirectory.run(SequenceFilesFromDirectory.java:90)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:84)
at org.apache.mahout.text.SequenceFilesFromDirectory.main(SequenceFilesFromDirectory.java:64)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.ProgramDriver$ProgramDescription.invoke(ProgramDriver.java:71)
at org.apache.hadoop.util.ProgramDriver.run(ProgramDriver.java:144)
at org.apache.hadoop.util.ProgramDriver.driver(ProgramDriver.java:152)
at org.apache.mahout.driver.MahoutDriver.main(MahoutDriver.java:195)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
----
I was trying to run the command against the local file system on my laptop which should have been possible according to the instructions. I couldn't find any flag I could pass any flag that I could pass to Mahout to tell it not to use HDFS but I eventually stumbled on http://stackoverflow.com/questions/23779976/java-lang-illegalargumentexception-wrong-fs-expected-hdfs-localhost9000[someone else experiencing a similar problem].
It turns out the last time I was playing around with Hadoop, in late 2015, I'd actually configured that and had completely forgotten. I needed to comment out the following config:
_/usr/local/Cellar/hadoop/2.7.1/libexec/etc/hadoop/core-site.xml_
[source,xml]
----
<property>
<name>fs.default.name</name>
<value>hdfs://localhost:8020</value>
</property>
----
I commented that property out and all was happy with the (Hadoop) world again. | null | null | [
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] | mahout-exception-in-thread-main-java-lang-illegalargumentexception-wrong-fs-file-expected-hdfs | https://markhneedham.com/blog/2016/07/21/mahout-exception-in-thread-main-java-lang-illegalargumentexception-wrong-fs-file-expected-hdfs |
false | 2016-07-09 06:36:51 | R: Sentiment analysis of morning pages | [
"r-2"
] | [
"R"
] | A couple of months ago I came across a cool blog post by https://twitter.com/juliasilge[Julia Silge] where she http://juliasilge.com/blog/Joy-to-the-World/[runs a sentiment analysis algorithm over her tweet stream] to see how her tweet sentiment has varied over time.
I wanted to give it a try but couldn't figure out how to get a dump of my tweets so I decided to try it out on the text from my http://juliacameronlive.com/basic-tools/morning-pages/[morning pages] writing which I've been experimenting with for a few months.
Here's an explanation of morning pages if you haven't come across it before:
____
Morning Pages are three pages of longhand, stream of consciousness writing, done first thing in the morning. *There is no wrong way to do Morning Pages* -- they are not high art. They are not even "`writing.`" They are about anything and everything that crosses your mind-- and they are for your eyes only. Morning Pages provoke, clarify, comfort, cajole, prioritize and synchronize the day at hand. Do not over-think Morning Pages: just put three pages of anything on the page...and then do three more pages tomorrow.
____
Most of my writing is complete gibberish but I thought it'd be fun to see how my mood changes over time and see if it identifies any peaks or troughs in sentiment that I could then look into further.
I've got one file per day so we'll start by building a data frame containing the text, one row per day:
[source,r]
----
library(syuzhet)
library(lubridate)
library(ggplot2)
library(scales)
library(reshape2)
library(dplyr)
root="/path/to/files"
files = list.files(root)
df = data.frame(file = files, stringsAsFactors=FALSE)
df$fullPath = paste(root, df$file, sep = "/")
df$text = sapply(df$fullPath, get_text_as_string)
----
We end up with a data frame with 3 fields:
[source,r]
----
> names(df)
[1] "file" "fullPath" "text"
----
Next we'll run the sentiment analysis function - +++<cite>+++syuzhet#get_nrc_sentiment+++</cite>+++ - over the data frame and get a score for each type of sentiment for each entry:
[source,r]
----
get_nrc_sentiment(df$text) %>% head()
anger anticipation disgust fear joy sadness surprise trust negative positive
1 7 14 5 7 8 6 6 12 14 27
2 11 12 2 13 9 10 4 11 22 24
3 6 12 3 8 7 7 5 13 16 21
4 5 17 4 7 10 6 7 13 16 37
5 4 13 3 7 7 9 5 14 16 25
6 7 11 5 7 8 8 6 15 16 26
----
Now we'll merge these columns into our original data frame:
[source,r]
----
df = cbind(df, get_nrc_sentiment(df$text))
df$date = ymd(sapply(df$file, function(file) unlist(strsplit(file, "[.]"))[1]))
df %>% select(-text, -fullPath, -file) %>% head()
anger anticipation disgust fear joy sadness surprise trust negative positive date
1 7 14 5 7 8 6 6 12 14 27 2016-01-02
2 11 12 2 13 9 10 4 11 22 24 2016-01-03
3 6 12 3 8 7 7 5 13 16 21 2016-01-04
4 5 17 4 7 10 6 7 13 16 37 2016-01-05
5 4 13 3 7 7 9 5 14 16 25 2016-01-06
6 7 11 5 7 8 8 6 15 16 26 2016-01-07
----
Finally we can build some 'sentiment over time' charts like Julia has in her post:
[source,r]
----
posnegtime <- df %>%
group_by(date = cut(date, breaks="1 week")) %>%
summarise(negative = mean(negative), positive = mean(positive)) %>%
melt
names(posnegtime) <- c("date", "sentiment", "meanvalue")
posnegtime$sentiment = factor(posnegtime$sentiment,levels(posnegtime$sentiment)[c(2,1)])
ggplot(data = posnegtime, aes(x = as.Date(date), y = meanvalue, group = sentiment)) +
geom_line(size = 2.5, alpha = 0.7, aes(color = sentiment)) +
geom_point(size = 0.5) +
ylim(0, NA) +
scale_colour_manual(values = c("springgreen4", "firebrick3")) +
theme(legend.title=element_blank(), axis.title.x = element_blank()) +
scale_x_date(breaks = date_breaks("1 month"), labels = date_format("%b %Y")) +
ylab("Average sentiment score") +
ggtitle("Sentiment Over Time")
----
image::{{<siteurl>}}/uploads/2016/07/2016-07-05_06-47-12.png[2016 07 05 06 47 12,580]
So overall it seems like my writing displays more positive sentiment than negative which is nice to know. The chart shows a rolling one week average and there isn't a single week where there's more negative sentiment than positive.
I thought it'd be fun to drill into the highest negative and positive days to see what was going on there:
[source,r]
----
> df %>% filter(negative == max(negative)) %>% select(date)
date
1 2016-03-19
> df %>% filter(positive == max(positive)) %>% select(date)
date
1 2016-01-05
2 2016-06-20
----
On the 19th March I was really frustrated because my boiler had broken down and I had to buy a new one - I'd completely forgotten how annoyed I was, so thanks sentiment analysis for reminding me!
I couldn't find anything particularly positive on the 5th January or 20th June. The 5th January was the day after my birthday so perhaps I was happy about that but I couldn't see any particular evidence that was the case.
Playing around with the +++<cite>+++get_nrc_sentiment+++</cite>+++ function it does seem to identify positive sentiment when I wouldn't say there is any. For example here's some example sentences from my writing today:
[source,r]
----
> get_nrc_sentiment("There was one section that I didn't quite understand so will have another go at reading that.")
anger anticipation disgust fear joy sadness surprise trust negative positive
1 0 0 0 0 0 0 0 0 0 1
----
[source,r]
----
> get_nrc_sentiment("Bit of a delay in starting my writing for the day...for some reason was feeling wheezy again.")
anger anticipation disgust fear joy sadness surprise trust negative positive
1 2 1 2 2 1 2 1 1 2 2
----
I don't think there's any positive sentiment in either of those sentences but the function claims 3 bits of positive sentiment! It would be interesting to see if I fare any better with https://cran.r-project.org/web/packages/syuzhet/vignettes/syuzhet-vignette.html[Stanford's sentiment extraction tool which you can use with syuzhet] but requires a bit of setup first.
I'll give that a try next but in terms of getting an overview of my mood I thought I might get a better picture if I looked for the difference between positive and negative sentiment rather than absolute values.
The following code does the trick:
[source,R]
----
difftime <- df %>%
group_by(date = cut(date, breaks="1 week")) %>%
summarise(diff = mean(positive) - mean(negative))
ggplot(data = difftime, aes(x = as.Date(date), y = diff)) +
geom_line(size = 2.5, alpha = 0.7) +
geom_point(size = 0.5) +
ylim(0, NA) +
scale_colour_manual(values = c("springgreen4", "firebrick3")) +
theme(legend.title=element_blank(), axis.title.x = element_blank()) +
scale_x_date(breaks = date_breaks("1 month"), labels = date_format("%b %Y")) +
ylab("Average sentiment difference score") +
ggtitle("Sentiment Over Time")
----
image::{{<siteurl>}}/uploads/2016/07/2016-07-09_07-05-34.png[2016 07 09 07 05 34,580]
This one identifies peak happiness in mid January/February. We can find the peak day for this measure as well:
[source,r]
----
> df %>% mutate(diff = positive - negative) %>% filter(diff == max(diff)) %>% select(date)
date
1 2016-02-25
----
Or if we want to see the individual scores:
[source,R]
----
> df %>% mutate(diff = positive - negative) %>% filter(diff == max(diff)) %>% select(-text, -file, -fullPath)
anger anticipation disgust fear joy sadness surprise trust negative positive date diff
1 0 11 2 3 7 1 6 6 3 31 2016-02-25 28
----
After reading through the entry for this day I'm wondering if the individual pieces of sentiment might be more interesting than the positive/negative score.
On the 25th February I was:
* quite excited about reading a distributed systems book I'd just bought (I know?!)
* thinking about how to apply the http://tagging.pui.ch/automated_tag_clustering[tag clustering technique] to meetup topics
* preparing https://www.youtube.com/watch?v=VGCCVNlZmRI[my submission to PyData London] and thinking about what was gonna go in it
* thinking about the soak testing we were about to start doing on our project
+
</ul>
+
Each of those is a type of anticipation so it makes sense that this day scores highly. I looked through some other days which specifically rank highly for anticipation and couldn't figure out what I was anticipating so even this is a bit hit and miss!
+
I have a few avenues to explore further but if you have any other ideas for what I can try next let me know in the comments. | null | null | [
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] | r-sentiment-analysis-of-morning-pages | https://markhneedham.com/blog/2016/07/09/r-sentiment-analysis-of-morning-pages |
false | 2016-07-22 13:55:14 | Mahout/Hadoop: org.apache.hadoop.ipc.RemoteException: Server IPC version 9 cannot communicate with client version 4 | [
"mahout",
"hadoop"
] | [
"Hadoop"
] | I've been working my way through http://stackoverflow.com/a/22830903/1093511[Dragan Milcevski's mini tutorial] on using Mahout to do content based filtering on documents and reached the final step where I needed to read in the generated item-similarity files.
I got the example compiling by using the following Maven dependency:
[source,xml]
----
<dependency>
<groupId>org.apache.mahout</groupId>
<artifactId>mahout-core</artifactId>
<version>0.9</version>
</dependency>
----
Unfortunately when I ran the code I ran into a version incompatibility problem:
[source,text]
----
Exception in thread "main" org.apache.hadoop.ipc.RemoteException: Server IPC version 9 cannot communicate with client version 4
at org.apache.hadoop.ipc.Client.call(Client.java:1113)
at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:229)
at com.sun.proxy.$Proxy1.getProtocolVersion(Unknown Source)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:85)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:62)
at com.sun.proxy.$Proxy1.getProtocolVersion(Unknown Source)
at org.apache.hadoop.ipc.RPC.checkVersion(RPC.java:422)
at org.apache.hadoop.hdfs.DFSClient.createNamenode(DFSClient.java:183)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:281)
at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:245)
at org.apache.hadoop.hdfs.DistributedFileSystem.initialize(DistributedFileSystem.java:100)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:1446)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:67)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:1464)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:263)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:124)
at com.markhneedham.mahout.Similarity.getDocIndex(Similarity.java:86)
at com.markhneedham.mahout.Similarity.main(Similarity.java:25)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:144)
----
Version 0.9.0 of mahout-core was published in early 2014 so I expect it was built against an earlier version of Hadoop than I'm using (2.7.2).
I tried updating the Hadoop dependencies that were being called in the stack trace to no avail.
[source,xml]
----
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<version>2.7.2</version>
</dependency>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-hdfs</artifactId>
<version>2.7.2</version>
</dependency>
----
When stepping through the stack trace I noticed that my program was still using an old version of hadoop-core, so with one last throw of the dice I decided to try explicitly excluding that:
[source,xml]
----
<dependency>
<groupId>org.apache.mahout</groupId>
<artifactId>mahout-core</artifactId>
<version>0.9</version>
<exclusions>
<exclusion>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-core</artifactId>
</exclusion>
</exclusions>
</dependency>
----
And amazingly it worked. Now, finally, I can see how similar my documents are! | null | null | [
-0.005309691186994314,
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] | mahouthadoop-org-apache-hadoop-ipc-remoteexception-server-ipc-version-9-cannot-communicate-with-client-version-4 | https://markhneedham.com/blog/2016/07/22/mahouthadoop-org-apache-hadoop-ipc-remoteexception-server-ipc-version-9-cannot-communicate-with-client-version-4 |
false | 2016-07-22 13:31:15 | Hadoop: DataNode not starting | [
"hadoop"
] | [
"Hadoop"
] | In my http://www.markhneedham.com/blog/2016/07/21/mahout-exception-in-thread-main-java-lang-illegalargumentexception-wrong-fs-file-expected-hdfs/[continued playing with Mahout] I eventually decided to give up using my local file system and use a local Hadoop instead since that seems to have much less friction when following any examples.
Unfortunately all my attempts to upload any files from my local file system to HDFS were being met with the following exception:
[source,text]
----
java.io.IOException: File /user/markneedham/book2.txt could only be replicated to 0 nodes, instead of 1
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:1448)
at org.apache.hadoop.hdfs.server.namenode.NameNode.addBlock(NameNode.java:690)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.ipc.WritableRpcEngine$Server.call(WritableRpcEngine.java:342)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:1350)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:1346)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:396)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:742)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:1344)
at org.apache.hadoop.ipc.Client.call(Client.java:905)
at org.apache.hadoop.ipc.WritableRpcEngine$Invoker.invoke(WritableRpcEngine.java:198)
at $Proxy0.addBlock(Unknown Source)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
at java.lang.reflect.Method.invoke(Method.java:597)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:82)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:59)
at $Proxy0.addBlock(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.locateFollowingBlock(DFSOutputStream.java:928)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.nextBlockOutputStream(DFSOutputStream.java:811)
at org.apache.hadoop.hdfs.DFSOutputStream$DataStreamer.run(DFSOutputStream.java:427)
----
I eventually realised, from looking at the output of +++<cite>+++jps+++</cite>+++, that the DataNode wasn't actually starting up which explains the error message I was seeing.
A quick look at the log files showed what was going wrong:
+++<cite>+++/usr/local/Cellar/hadoop/2.7.1/libexec/logs/hadoop-markneedham-datanode-marks-mbp-4.zte.com.cn.log +++</cite>+++
[source,text]
----
2016-07-21 18:58:00,496 WARN org.apache.hadoop.hdfs.server.common.Storage: java.io.IOException: Incompatible clusterIDs in /usr/local/Cellar/hadoop/hdfs/tmp/dfs/data: namenode clusterID = CID-c2e0b896-34a6-4dde-b6cd-99f36d613e6a; datanode clusterID = CID-403dde8b-bdc8-41d9-8a30-fe2dc951575c
2016-07-21 18:58:00,496 FATAL org.apache.hadoop.hdfs.server.datanode.DataNode: Initialization failed for Block pool <registering> (Datanode Uuid unassigned) service to /0.0.0.0:8020. Exiting.
java.io.IOException: All specified directories are failed to load.
at org.apache.hadoop.hdfs.server.datanode.DataStorage.recoverTransitionRead(DataStorage.java:477)
at org.apache.hadoop.hdfs.server.datanode.DataNode.initStorage(DataNode.java:1361)
at org.apache.hadoop.hdfs.server.datanode.DataNode.initBlockPool(DataNode.java:1326)
at org.apache.hadoop.hdfs.server.datanode.BPOfferService.verifyAndSetNamespaceInfo(BPOfferService.java:316)
at org.apache.hadoop.hdfs.server.datanode.BPServiceActor.connectToNNAndHandshake(BPServiceActor.java:223)
at org.apache.hadoop.hdfs.server.datanode.BPServiceActor.run(BPServiceActor.java:801)
at java.lang.Thread.run(Thread.java:745)
2016-07-21 18:58:00,497 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: Ending block pool service for: Block pool <registering> (Datanode Uuid unassigned) service to /0.0.0.0:8020
2016-07-21 18:58:00,602 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: Removed Block pool <registering> (Datanode Uuid unassigned)
2016-07-21 18:58:02,607 WARN org.apache.hadoop.hdfs.server.datanode.DataNode: Exiting Datanode
2016-07-21 18:58:02,608 INFO org.apache.hadoop.util.ExitUtil: Exiting with status 0
2016-07-21 18:58:02,610 INFO org.apache.hadoop.hdfs.server.datanode.DataNode: SHUTDOWN_MSG:
----
I'm not sure how my clusterIDs got out of sync, although I expect it's because I reformatted HDFS without realising at some stage. There are http://stackoverflow.com/questions/29166837/datanode-is-not-starting-in-singlenode-hadoop-2-6-0[other] http://stackoverflow.com/questions/22316187/datanode-not-starts-correctly[ways] of solving this problem but the quickest for me was to just nuke the DataNode's data directory which the log file told me sits here:
[source,bash]
----
sudo rm -r /usr/local/Cellar/hadoop/hdfs/tmp/dfs/data/current
----
I then re-ran the +++<cite>+++hstart+++</cite>+++ script that I stole from https://getblueshift.com/setting-up-hadoop-2-4-and-pig-0-12-on-osx-locally/[this tutorial] and everything, including the DataNode this time, started up correctly:
[source,bash]
----
$ jps
26736 NodeManager
26392 DataNode
26297 NameNode
26635 ResourceManager
26510 SecondaryNameNode
----
And now I can upload local files to HDFS again. #win! | null | null | [
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false | 2016-09-14 05:33:38 | scikit-learn: First steps with log_loss | [
"scikit-learn"
] | [
"Machine Learning",
"Python"
] | Over the last week I've spent a little bit of time playing around with the data in the https://www.kaggle.com/c/talkingdata-mobile-user-demographics/details/evaluation[Kaggle TalkingData Mobile User Demographics] competition, and came across https://www.kaggle.com/dvasyukova/talkingdata-mobile-user-demographics/a-linear-model-on-apps-and-labels/comments[a notebook] written by https://www.kaggle.com/dvasyukova[dune_dweller] showing how to run a logistic regression algorithm on the dataset.
The metric used to evaluate the output in this competition is https://www.kaggle.com/c/talkingdata-mobile-user-demographics/details/evaluation[multi class logarithmic loss], which is implemented by the +++<cite>+++http://scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html[log_loss]+++</cite>+++ function in the http://scikit-learn.org/stable/index.html[scikit-learn] library.
I've not used it before so I created a small example to get to grips with it.
Let's say we have 3 rows to predict and we happen to know that they should be labelled 'bam', 'spam', and 'ham' respectively:
[source,python]
----
>>> actual_labels = ["bam", "ham", "spam"]
----
To work out the log loss score we need to make a prediction for what we think each label actually is. We do this by passing an array containing a probability between 0-1 for each label
e.g. if we think the first label is definitely 'bam' then we'd pass +++<cite>+++[1, 0, 0]+++</cite>+++, whereas if we thought it had a 50-50 chance of being 'bam' or 'spam' then we might pass +++<cite>+++[0.5, 0, 0.5]+++</cite>+++. As far as I can tell the values get sorted into (alphabetical) order so we need to provide our predictions in the same order.
Let's give it a try. First we'll import the function:
[source,python]
----
>>> from sklearn.metrics import log_loss
----
Now let's see what score we get if we make a perfect prediction:
[source,python]
----
>>> log_loss(actual_labels, [[1, 0, 0], [0, 1, 0], [0, 0, 1]])
2.1094237467877998e-15
----
What about if we make a completely wrong prediction?
[source,python]
----
>>> log_loss(actual_labels, [[0, 0, 1], [1, 0, 0], [0, 1, 0]])
34.538776394910684
----
We can reverse engineer this score to work out the http://stackoverflow.com/questions/35013822/log-loss-output-is-greater-than-1[probability that we've predicted the correct class].
____
If we look at the case where the average log loss exceeds 1, it is when log(pij) < -1 when i is the true class.
This means that the predicted probability for that given class would be less than exp(-1) or around 0.368. So, seeing a log loss greater than one can be expected in the cass that that your model only gives less than a 36% probability estimate for the correct class.
____
This is the formula of logloss:
image::{{<siteurl>}}/uploads/2016/09/NEmt7.png[NEmt7,168]
In which y~ij~ is 1 for the correct class and 0 for other classes and p~ij~ is the probability assigned for that class.
The interesting thing about this formula is that we only care about the correct class. The y~ij~ value of 0 cancels out the wrong classes.
In our two examples so far we actually already know the probability estimate for the correct class - 100% in the first case and 0% in the second case, but we can plug in the numbers to check we end up with the same result.
First we need to work out what value would have been passed to the log function which is easy in this case. The value of y~ij~ is
~~~python # every prediction exactly right >>> math.log(1) 0.0 >>> math.exp(0) 1.0 ~~~ ~~~python # every prediction completely wrong >>> math.log(0.000000001) -20.72326583694641 >>> math.exp(-20.72326583694641) 1.0000000000000007e-09 ~~~
I used a really small value instead of 0 in the second example because +++<cite>+++math.log(0)+++</cite>+++ http://www.rapidtables.com/math/algebra/logarithm/Logarithm_of_0.htm[trends towards negative infinity].
Let's try another example where we have less certainty:
~~~python >>> print log_loss(actual_labels, [[0.8, 0.1, 0.1], [0.3, 0.6, 0.1], [0.15, 0.15, 0.7]]) 0.363548039673 ~~~
We'll have to do a bit more work to figure out what value was being passed to the log function this time, but not too much. This is roughly the calculation being performed:
~~~python # 0.363548039673 = -1/3 * (log(0.8) + log(0.6) + log(0.7) >>> print log_loss(actual_labels, [[0.8, 0.1, 0.1], [0.3, 0.6, 0.1], [0.15, 0.15, 0.7]]) 0.363548039673 ~~~
In this case, on average our probability estimate would be:
~~~python # we put in the negative value since we multiplied by -1/N >>> math.exp(-0.363548039673) 0.6952053289772744 ~~~
We had 60%, 70%, and 80% accuracy for our 3 labels so an overall probability of 69.5% seems about right.
One more example. This time we'll make one more very certain (90%) prediction for 'spam':
~~~python >>> print log_loss(["bam", "ham", "spam", "spam"], [[0.8, 0.1, 0.1], [0.3, 0.6, 0.1], [0.15, 0.15, 0.7], [0.05, 0.05, 0.9]]) 0.299001158669 >>> math.exp(-0.299001158669) 0.741558550213609 ~~~
74% accuracy overall, sounds about right!+++</div>+++ | null | null | [
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] | scikit-learn-first-steps-with-log_loss | https://markhneedham.com/blog/2016/09/14/scikit-learn-first-steps-with-log_loss |
false | 2016-08-27 20:32:09 | scikit-learn: Clustering and the curse of dimensionality | [
"machine-learning-2",
"python",
"scikit-learn"
] | [
"Machine Learning",
"Python"
] | In my last post I attempted to http://www.markhneedham.com/blog/2016/08/25/scikit-learn-trying-to-find-clusters-of-game-of-thrones-episodes/[cluster Game of Thrones episodes based on character appearances without much success]. After I wrote that post I was flicking through the scikit-learn clustering documentation and noticed the following section which describes some of the weaknesses of the K-means clustering algorithm:
____
Inertia is not a normalized metric: we just know that lower values are better and zero is optimal. But in very high-dimensional spaces, Euclidean distances tend to become inflated (this is an instance of the so-called "`curse of dimensionality`"). Running a dimensionality reduction algorithm such as PCA prior to k-means clustering can alleviate this problem and speed up the computations.
____
Each episode has 638 dimensions so this is probably the problem we're seeing. I actually thought the 'curse of dimensionality' referred to the greater than linear increase in computation time; I hadn't realised it could also impact the clustering itself.
As the documentation notes, the K-Means algorithm calculates euclidean distances to work out which cluster episodes should go in. Episodes in the same cluster should have a small euclidean distance and items in different clusters should have larger ones.
I created a little script to help me understand the curse of dimensionality. I've got 4 pairs of vectors, of size 4, 6, 100, and 600. Half of the items in the vector match and the other half differ. I calculate the cosine similarity and euclidean distance for each pair of vectors:
[source,python]
----
from sklearn.metrics.pairwise import cosine_similarity
import numpy as np
def distances(a, b):
return np.linalg.norm(a-b), cosine_similarity([a, b])[0][1]
def mixed(n_zeros, n_ones):
return np.concatenate((np.repeat([1], n_ones), np.repeat([0], n_zeros)), axis=0)
def ones(n_ones):
return np.repeat([1], n_ones)
print distances(mixed(2, 2), ones(4))
print distances(mixed(3, 3), ones(6))
print distances(mixed(50, 50), ones(100))
print distances(mixed(300, 300), ones(600))
(1.4142135623730951, 0.70710678118654746)
(1.7320508075688772, 0.70710678118654768)
(7.0710678118654755, 0.70710678118654757)
(17.320508075688775, 0.70710678118654746)
----
The euclidean distance for the 600 item vector is 17x larger than for the one containing 4 items despite having the same similarity score.
Having convinced myself that reducing the dimensionality of the vectors could make a difference I reduced the size of the episodes vectors using the http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html[the Truncated SVD] algorithm before trying K-means clustering again.
First we reduce the dimensionality of the episodes vectors:
[source,python]
----
from sklearn.decomposition import TruncatedSVD
n_components = 2
reducer = TruncatedSVD(n_components=n_components)
reducer.fit(all)
new_all = reducer.transform(all)
print("%d: Percentage explained: %s\n" % (n_components, reducer.explained_variance_ratio_.sum()))
2: Percentage explained: 0.124579183633
----
I'm not sure how much I should be reducing the number of dimensions so I thought 2 would an interesting place to start. I'm not sure exactly what the output of the +++<cite>+++reducer.explained_variance_ratio_+++</cite>+++ function means so I need to do some more reading to figure out whether it makes sense to carry on with a dimension of 2.
For now though let's try out the clustering algorithm again and see how it gets on:
[source,python]
----
from sklearn.cluster import KMeans
for n_clusters in range(2, 10):
km = KMeans(n_clusters=n_clusters, init='k-means++', max_iter=100, n_init=1)
cluster_labels = km.fit_predict(new_all)
silhouette_avg = metrics.silhouette_score(new_all, cluster_labels, sample_size=1000)
print n_clusters, silhouette_avg
2 0.559681096025
3 0.498456585461
4 0.524704352941
5 0.441580592398
6 0.44703058946
7 0.447895331824
8 0.433698007009
9 0.459874485986
----
This time out silhouette scores are much better. I came across http://www.unesco.org/webworld/idams/advguide/Chapt7_1_1.htm[a tutorial] from the http://www.unesco.org/webworld/idams/advguide/TOC.htm[Guide to Advanced Data Analysis] which includes a table explaining how to interpret this score:
image::{{<siteurl>}}/uploads/2016/08/2016-08-27_21-18-14.png[2016 08 27 21 18 14,400]
We have a couple of cluster sizes which fit in the 'reasonable structure' and a few just on the edge of fitting in that category.
I tried varying the number of dimensions and found that 3 worked reasonably well, but after that the silhouette score dropped rapidly. Once we reach 30 dimensions the silhouette score is almost the same as if we hadn't reduced dimensionality at all.
I haven't figured out a good way of visualising the results of my experiments where I vary the dimensions and number of clusters so that's something to work on next. I find it quite difficult to see what's going on by just staring at the raw numbers.
I also need to read up on the SVD algorithm to understand when it is/isn't acceptable to reduce dimensions and how much I should be reducing them by.
Any questions/thoughts/advice do let me know in the comments. | null | null | [
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] | scikit-learn-clustering-and-the-curse-of-dimensionality | https://markhneedham.com/blog/2016/08/27/scikit-learn-clustering-and-the-curse-of-dimensionality |
false | 2016-08-14 18:56:35 | Python: matplotlib, seaborn, virtualenv - Python is not installed as a framework | [
"python",
"matplotlib"
] | [
"Python"
] | Over the weekend I was following https://github.com/thomhopmans/themarketingtechnologist[The Marketing Technologist's] content based recommender tutorial but ran into the following exception when trying to import the seaborn library:
[source,bash]
----
$ python 5_content_based_recommender/run.py
Traceback (most recent call last):
File "5_content_based_recommender/run.py", line 14, in <module>
import seaborn as sns
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/seaborn/__init__.py", line 6, in <module>
from .rcmod import *
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/seaborn/rcmod.py", line 8, in <module>
from . import palettes, _orig_rc_params
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/seaborn/palettes.py", line 12, in <module>
from .utils import desaturate, set_hls_values, get_color_cycle
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/seaborn/utils.py", line 12, in <module>
import matplotlib.pyplot as plt
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/matplotlib/pyplot.py", line 114, in <module>
_backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup()
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/matplotlib/backends/__init__.py", line 32, in pylab_setup
globals(),locals(),[backend_name],0)
File "/Users/markneedham/projects/themarketingtechnologist/tmt/lib/python2.7/site-packages/matplotlib/backends/backend_macosx.py", line 24, in <module>
from matplotlib.backends import _macosx
RuntimeError: Python is not installed as a framework. The Mac OS X backend will not be able to function correctly if Python is not installed as a framework. See the Python documentation for more information on installing Python as a framework on Mac OS X. Please either reinstall Python as a framework, or try one of the other backends. If you are Working with Matplotlib in a virtual enviroment see 'Working with Matplotlib in Virtual environments' in the Matplotlib FAQ
----
We can see from the stacktrace that seaborn calls matplotlib so that's where the problem lies. There's even a http://matplotlib.org/faq/virtualenv_faq.html[page on the matplotlib website suggesting some workarounds].
I've come across this error before and been unable to get any of the suggestions to work, but this time I was successful. I needed to create the following function in my bash profile file:
+++<cite>+++~/.bash_profile +++</cite>+++
[source,text]
----
function frameworkpython {
if [[ ! -z "$VIRTUAL_ENV" ]]; then
PYTHONHOME=$VIRTUAL_ENV /usr/bin/python "$@"
else
/usr/bin/python "$@"
fi
}
----
And call that function instead of my virtualenv's python:
[source,bash]
----
$ frameworkpython 5_content_based_recommender/run.py
----
This time the matplotlib visualisation works:
image::{{<siteurl>}}/uploads/2016/08/2016-08-14_16-16-08.png[2016 08 14 16 16 08,553]
#win | null | null | [
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] | python-matplotlibseabornvirtualenv-python-is-not-installed-as-a-framework | https://markhneedham.com/blog/2016/08/14/python-matplotlibseabornvirtualenv-python-is-not-installed-as-a-framework |
false | 2016-08-22 21:12:54 | Neo4j/scikit-learn: Calculating the cosine similarity of Game of Thrones episodes | [
"machine-learning-2",
"python"
] | [
"neo4j",
"Machine Learning",
"Python"
] | A couple of months ago https://twitter.com/praveenasekhar[Praveena] and I created a https://github.com/mneedham/neo4j-got[Game of Thrones dataset] to use in a workshop and I thought it'd be fun to run it through some machine learning algorithms and hopefully find some interesting insights.
The dataset is https://github.com/mneedham/neo4j-got/tree/master/data/import[available as CSV files] but for this analysis I'm assuming that it's already been imported into neo4j. If you want to import the data you can run the tutorial by typing the following into the query bar of the neo4j browser:
[source,text]
----
:play http://guides.neo4j.com/got
----
Since we don't have any training data we'll be using unsupervised learning methods, and we'll start simple by calculating the similarity of episodes based character appearances. We'll be using http://scikit-learn.org/stable/[scitkit-learn]'s http://scikit-learn.org/dev/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html[cosine similarity function] to determine episode similarity.
Christian Perone has http://blog.christianperone.com/2013/09/machine-learning-cosine-similarity-for-vector-space-models-part-iii/[an excellent blog post] explaining how to use cosine similarity on text documents which is well worth a read. We'll be using a similar approach here, but instead of building a TF/IDF vector for each document we're going to create a vector indicating whether a character appeared in an episode or not.
e.g. imagine that we have 3 characters - A, B, and C - and 2 episodes. A and B appear in the first episode and B and C appear in the second episode. We would represent that with the following vectors:
[source,text]
----
Episode 1 = [1, 1, 0]
Episode 2 = [0, 1, 1]
----
We could then calculate the cosine similarity between these two episodes like this:
[source,python]
----
>>> from sklearn.metrics.pairwise import cosine_similarity
>>> one = [1,1,0]
>>> two = [0,1,1]
>>> cosine_similarity([one, two])
array([[ 1. , 0.5],
[ 0.5, 1. ]])
----
So this is telling us that Episode 1 is 100% similar to Episode 1, Episode 2 is 100% similar to itself as well, and Episodes 1 and 2 are 50% similar to each other based on the fact that they both have an appearance of Character B.
Note that the character names aren't even mentioned at all, they are implicitly a position in the array. This means that when we use our real dataset we need to ensure that the characters are in the same order for each episode, otherwise the calculation will be meaningless!
In neo4j land we have an +++<cite>+++APPEARED_IN+++</cite>+++ relationship between a character and each episode that they appeared in. We can therefore write the following code using the Python driver to get all pairs of episodes and characters:
[source,python]
----
from neo4j.v1 import GraphDatabase, basic_auth
driver = GraphDatabase.driver("bolt://localhost", auth=basic_auth("neo4j", "neo"))
session = driver.session()
rows = session.run("""
MATCH (c:Character), (e:Episode)
OPTIONAL MATCH (c)-[appearance:APPEARED_IN]->(e)
RETURN e, c, appearance
ORDER BY e.id, c.id""")
----
We can iterate through the rows to see what the output looks like:
[source,python]
----
>>> for row in rows:
print row
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5415 labels=set([u'Character']) properties={u'name': u'Addam Marbrand', u'id': u'/wiki/Addam_Marbrand'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5882 labels=set([u'Character']) properties={u'name': u'Adrack Humble', u'id': u'/wiki/Adrack_Humble'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=6747 labels=set([u'Character']) properties={u'name': u'Aegon V Targaryen', u'id': u'/wiki/Aegon_V_Targaryen'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5750 labels=set([u'Character']) properties={u'name': u'Aemon', u'id': u'/wiki/Aemon'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5928 labels=set([u'Character']) properties={u'name': u'Aeron Greyjoy', u'id': u'/wiki/Aeron_Greyjoy'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5503 labels=set([u'Character']) properties={u'name': u'Aerys II Targaryen', u'id': u'/wiki/Aerys_II_Targaryen'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=6753 labels=set([u'Character']) properties={u'name': u'Alannys Greyjoy', u'id': u'/wiki/Alannys_Greyjoy'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=6750 labels=set([u'Character']) properties={u'name': u'Alerie Tyrell', u'id': u'/wiki/Alerie_Tyrell'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5753 labels=set([u'Character']) properties={u'name': u'Alliser Thorne', u'id': u'/wiki/Alliser_Thorne'}> appearance=None>
<Record e=<Node id=6780 labels=set([u'Episode']) properties={u'season': 1, u'number': 1, u'id': 1, u'title': u'Winter Is Coming'}> c=<Node id=5858 labels=set([u'Character']) properties={u'name': u'Alton Lannister', u'id': u'/wiki/Alton_Lannister'}> appearance=None>
----
Next we'll build a 'matrix' of episodes/characters. If a character appears in an episode then we'll put a '1' in the matrix, if not we'll put a '0':
[source,python]
----
episodes = {}
for row in rows:
if episodes.get(row["e"]["id"]) is None:
if row["appearance"] is None:
episodes[row["e"]["id"]] = [0]
else:
episodes[row["e"]["id"]] = [1]
else:
if row["appearance"] is None:
episodes[row["e"]["id"]].append(0)
else:
episodes[row["e"]["id"]].append(1)
----
Here's an example of one entry in the matrix:
[source,python]
----
>>> len(episodes)
60
>>> len(episodes[1])
638
>>> episodes[1]
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
----
From this output we learn that there are 60 episodes and 638 characters in Game of Thrones so far. We can also see which characters appeared in the first episode, although it's a bit tricky to work out which index in the array corresponds to each character.
The next thing we're going to do is calculate the cosine similarity between episodes. Let's start by seeing how similar the first episode is to all the others:
[source,python]
----
>>> all = episodes.values()
>>> cosine_similarity(all[0:1], all)[0]
array([ 1. , 0.69637306, 0.48196269, 0.54671752, 0.48196269,
0.44733753, 0.31707317, 0.42340087, 0.34989921, 0.43314808,
0.36597766, 0.18421252, 0.30961158, 0.2328101 , 0.30616181,
0.41905818, 0.36842504, 0.35338088, 0.18376917, 0.3569686 ,
0.2328101 , 0.34539847, 0.25043516, 0.31707317, 0.25329221,
0.33342786, 0.34921515, 0.2174909 , 0.2533473 , 0.28429311,
0.23026565, 0.22310537, 0.22365301, 0.23816275, 0.28242289,
0.16070148, 0.24847093, 0.21434648, 0.03582872, 0.21189672,
0.15460414, 0.17161693, 0.15460414, 0.17494961, 0.1234662 ,
0.21426863, 0.21434648, 0.18748505, 0.15308091, 0.20161946,
0.19877675, 0.30920827, 0.21058466, 0.19127301, 0.24607943,
0.18033393, 0.17734311, 0.16296707, 0.18740851, 0.23995201])
----
The first entry in the array indicates that episode 1 is 100% similar to episode 1 which is a good start. It's 69% similar to episode 2 and 48% similar to episode 3. We can sort that array to work out which episodes it's most similar to:
[source,python]
----
>>> for idx, score in sorted(enumerate(cosine_similarity(all[0:1], all)[0]), key = lambda x: x[1], reverse = True)[:5]:
print idx, score
0 1.0
1 0.696373059207
3 0.546717521051
2 0.481962692712
4 0.481962692712
----
Or we can see how similar the last episode of season 6 is compared to the others:
[source,python]
----
>>> for idx, score in sorted(enumerate(cosine_similarity(all[59:60], all)[0]), key = lambda x: x[1], reverse = True)[:5]:
print idx, score
59 1.0
52 0.500670191678
46 0.449085146211
43 0.448218732478
49 0.446296233312
----
I found it a bit painful exploring similarities like this so I decided to write them into neo4j instead and then write a query to find the most similar episodes. The following query creates a +++<cite>+++SIMILAR_TO+++</cite>+++ relationship between episodes and sets a +++<cite>+++score+++</cite>+++ property on that relationship:
[source,python]
----
>>> episode_mapping = {}
>>> for idx, episode_id in enumerate(episodes):
episode_mapping[idx] = episode_id
>>> for idx, episode_id in enumerate(episodes):
similarity_matrix = cosine_similarity(all[idx:idx+1], all)[0]
for other_idx, similarity_score in enumerate(similarity_matrix):
other_episode_id = episode_mapping[other_idx]
print episode_id, other_episode_id, similarity_score
if episode_id != other_episode_id:
session.run("""
MATCH (episode1:Episode {id: {episode1}}), (episode2:Episode {id: {episode2}})
MERGE (episode1)-[similarity:SIMILAR_TO]-(episode2)
ON CREATE SET similarity.score = {similarityScore}
""", {'episode1': episode_id, 'episode2': other_episode_id, 'similarityScore': similarity_score})
session.close()
----
The +++<cite>+++episode_mapping+++</cite>+++ dictionary is needed to map from episode ids to indices e.g. episode 1 is at index 0.
If we want to find the most similar pair of episodes in Game of Thrones we can execute the following query:
[source,cypher]
----
MATCH (episode1:Episode)-[similarity:SIMILAR_TO]-(episode2:Episode)
WHERE ID(episode1) > ID(episode2)
RETURN "S" + episode1.season + "E" + episode1.number AS ep1,
"S" + episode2.season + "E" + episode2.number AS ep2,
similarity.score AS score
ORDER BY similarity.score DESC
LIMIT 10
βββββββ€βββββ€βββββββββββββββββββ
βep1 βep2 βscore β
βββββββͺβββββͺβββββββββββββββββββ‘
βS1E2 βS1E1β0.6963730592072543β
βββββββΌβββββΌβββββββββββββββββββ€
βS1E4 βS1E3β0.6914173051223086β
βββββββΌβββββΌβββββββββββββββββββ€
βS1E9 βS1E8β0.6869464497590777β
βββββββΌβββββΌβββββββββββββββββββ€
βS2E10βS2E8β0.6869037302955034β
βββββββΌβββββΌβββββββββββββββββββ€
βS3E7 βS3E6β0.6819943394704735β
βββββββΌβββββΌβββββββββββββββββββ€
βS2E7 βS2E6β0.6813598225089799β
βββββββΌβββββΌβββββββββββββββββββ€
βS1E10βS1E9β0.6796436827080401β
βββββββΌβββββΌβββββββββββββββββββ€
βS1E5 βS1E4β0.6698105143372364β
βββββββΌβββββΌβββββββββββββββββββ€
βS1E10βS1E8β0.6624062584864754β
βββββββΌβββββΌβββββββββββββββββββ€
βS4E5 βS4E4β0.6518358737330705β
βββββββ΄βββββ΄βββββββββββββββββββ
----
And the least popular?
[source,cypher]
----
MATCH (episode1:Episode)-[similarity:SIMILAR_TO]-(episode2:Episode)
WHERE ID(episode1) > ID(episode2)
RETURN "S" + episode1.season + "E" + episode1.number AS ep1,
"S" + episode2.season + "E" + episode2.number AS ep2,
similarity.score AS score
ORDER BY similarity.score
LIMIT 10
ββββββ€βββββ€ββββββββββββββββββββ
βep1 βep2 βscore β
ββββββͺβββββͺββββββββββββββββββββ‘
βS4E9βS1E5β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS4E9βS1E6β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS4E9βS4E2β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS4E9βS2E9β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS4E9βS2E4β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS5E6βS4E9β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS6E8βS4E9β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS4E9βS4E6β0 β
ββββββΌβββββΌββββββββββββββββββββ€
βS3E9βS2E9β0.03181423814878889β
ββββββΌβββββΌββββββββββββββββββββ€
βS4E9βS1E1β0.03582871819500093β
ββββββ΄βββββ΄ββββββββββββββββββββ
----
The output of this query suggests that there are no common characters between 8 pairs of episodes which at first glance sounds surprising. Let's write a query to check that finding:
[source,cypher]
----
MATCH (episode1:Episode)<-[:APPEARED_IN]-(character)-[:APPEARED_IN]->(episode2:Episode)
WHERE episode1.season = 4 AND episode1.number = 9 AND episode2.season = 1 AND episode2.number = 5
return episode1, episode2
(no changes, no rows)
----
It's possible I made a mistake with the scraping of the data but from a quick look over http://gameofthrones.wikia.com/wiki/The_Watchers_on_the_Wall[the Wiki page] I don't think I have. I found it interesting that Season 4 Episode 9 shows up on 9 of the top 10 least similar pairs of episodes.
Next I'm going to cluster the episodes based on character appearances, but this post is long enough already so that'll have to wait for another post another day. | null | null | [
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] | neo4jscikit-learn-calculating-the-cosine-similarity-of-game-of-thrones-episodes | https://markhneedham.com/blog/2016/08/22/neo4jscikit-learn-calculating-the-cosine-similarity-of-game-of-thrones-episodes |
false | 2016-08-25 22:07:25 | scikit-learn: Trying to find clusters of Game of Thrones episodes | [
"scikit-learn"
] | [
"Machine Learning",
"Python"
] | In my last post I showed how to http://www.markhneedham.com/blog/2016/08/22/neo4jscikit-learn-calculating-the-cosine-similarity-of-game-of-thrones-episodes/[find similar Game of Thrones episodes based on the characters that appear in different episodes]. This allowed us to find similar episodes on an episode by episode basis, but I was curious whether there were *groups of similar episodes* that we could identify.
scikit-learn provides several clustering algorithms that can run over our episode vectors and hopefully find clusters of similar episodes. A clustering algorithm groups similar documents together, where similarity is based on calculating a 'distance' between documents. Documents separated by a small distance would be in the same cluster, whereas if there's a large distance between episodes then they'd probably be in different clusters.
The simplest variant is http://scikit-learn.org/stable/modules/clustering.html#k-means[K-means] clustering:
____
The KMeans algorithm clusters data by trying to separate samples in n groups of equal variance, minimizing a criterion known as the inertia or within-cluster sum-of-squares. This algorithm requires the number of clusters to be specified.
____
The output from the algorithm is a list of labels which correspond to the cluster assigned to each episode.
Let's give it a try on the Game of Thrones episodes. We'll start from the 2 dimensional array of episodes/character appearances that we created in the http://www.markhneedham.com/blog/2016/08/22/neo4jscikit-learn-calculating-the-cosine-similarity-of-game-of-thrones-episodes/[previous post].
[source,python]
----
>>> all.shape
(60, 638)
>>> all
array([[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
...,
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0],
[0, 0, 0, ..., 0, 0, 0]])
----
We have a 60 (episodes) x 638 (characters) array which we can now plug into the K-means clustering algorithm:
[source,python]
----
>>> from sklearn.cluster import KMeans
>>> n_clusters = 3
>>> km = KMeans(n_clusters=n_clusters, init='k-means++', max_iter=100, n_init=1)
>>> cluster_labels = km.fit_predict(all)
>>> cluster_labels
array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 2, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], dtype=int32)
----
+++<cite>+++cluster_labels+++</cite>+++ is an array containing a label for each episode in the +++<cite>+++all+++</cite>+++ array. The spread of these labels is as follows:
[source,python]
----
>>> import numpy as np
>>> np.bincount(cluster_labels)
array([19, 12, 29])
----
i.e. 19 episodes in cluster 0, 12 in cluster 1, and 29 in cluster 2.
== How do we know if the clustering is any good?
Ideally we'd have some labelled training data which we could compare our labels against, but since we don't we can measure the effectiveness of our clustering by calculating http://stackoverflow.com/questions/8102515/selecting-an-appropriate-similarity-metric-assessing-the-validity-of-a-k-means[inter-centroidal separation and intra-cluster variance].
i.e. how close are the episodes to other episodes in the same cluster vs how close are they to episodes in the closest different cluster.
scikit-learn gives us a function that we can use to calculate this score - the http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#example-cluster-plot-kmeans-silhouette-analysis-py[silhouette coefficient].
The output of this function is a score between -1 and 1.
* A score of 1 means that our clustering has worked well and a document is far away from the boundary of another cluster.
* A score of -1 means that our document should have been placed in another cluster.
* A score of 0 means that the document is very close to the decision boundary between two clusters.
I tried calculating this coefficient for some different values of K. This is what I found:
[source,python]
----
from sklearn import metrics
for n_clusters in range(2, 10):
km = KMeans(n_clusters=n_clusters, init='k-means++', max_iter=100, n_init=1)
cluster_labels = km.fit_predict(all)
silhouette_avg = metrics.silhouette_score(all, cluster_labels, sample_size=1000)
sample_silhouette_values = metrics.silhouette_samples(all, cluster_labels)
print n_clusters, silhouette_avg
2 0.0798610142955
3 0.0648416081725
4 0.0390877994786
5 0.020165277756
6 0.030557856406
7 0.0389677156458
8 0.0590721834989
9 0.0466170527996
----
The best score we manage here is 0.07 when we set the number of clusters to 2. Even our highest score is much lower than the http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html#example-cluster-plot-kmeans-silhouette-analysis-py[lowest score on the documentation page]!
I tried it out with some higher values of K but only saw a score over 0.5 once I put the number of clusters to 40 which would mean 1 or 2 episodes per cluster at most.
At the moment our episode arrays contain 638 elements so they're too long to visualise on a 2D silhouette plot. We'd need to apply a dimensionality reduction algorithm before doing that.
In summary it looks like character co-occurrence isn't a good way to cluster episodes. I'm curious what would happen if we flip the array on its head and try and cluster the characters instead, but that's for another day.
If anyone spots anything that I've missed when reading the output of the algorithm let me know in the comments. I'm just learning by experimentation at the moment. | null | null | [
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] | scikit-learn-trying-to-find-clusters-of-game-of-thrones-episodes | https://markhneedham.com/blog/2016/08/25/scikit-learn-trying-to-find-clusters-of-game-of-thrones-episodes |
false | 2016-01-17 12:19:35 | Neo4j: Cypher - avoid duplicate calls to NOT patterns | [
"neo4j"
] | [
"neo4j"
] | I've been reacquainting myself with the https://github.com/neo4j-meetups/modeling-worked-example[meetup.com dataset] ahead of http://www.meetup.com/graphdb-london/[Wednesday's meetup in London] and wanted to write a collaborative filtering type query to work out which groups people in my groups were in.
This started simple enough:
[source,cypher]
----
MATCH (member:Member {name: "Mark Needham"})-[:MEMBER_OF]->(group:Group)<-[:MEMBER_OF]-(other:Member)-[:MEMBER_OF]->(otherGroup:Group)
RETURN otherGroup, COUNT(*) AS commonMembers
ORDER BY commonMembers DESC
LIMIT 5
----
And doesn't take too long to run:
[source,text]
----
Cypher version: CYPHER 2.3, planner: COST. 1084378 total db hits in 1103 ms.
----
However, it was showing up several groups that I'm already a member of so I added in a "WHERE NOT" clause to sort that out:
[source,cypher]
----
MATCH (member:Member {name: "Mark Needham"})-[:MEMBER_OF]->(group:Group)<-[:MEMBER_OF]-(other:Member)-[:MEMBER_OF]->(otherGroup:Group)
WHERE NOT (member)-[:MEMBER_OF]->(otherGroup)
RETURN otherGroup, COUNT(*) AS commonMembers
ORDER BY commonMembers DESC
LIMIT 5
----
Unfortunately when I ran this the amount of db hits increased by 14x and it now took 3x as long to run:
[source,text]
----
Cypher version: CYPHER 2.3, planner: COST. 14061442 total db hits in 3364 ms.
----
The problem is that we're making lots of duplicate calls to +++<cite>+++NOT (member)-[:MEMBER_OF]\->(otherGroup)+++</cite>+++ because each group shows up lots of times.
This is the 'reduce cardinality of work in progress' tip from http://neo4j.com/blog/neo4j-2-2-query-tuning/[Michael Hunger's blog post]:
____
Bonus Query Tuning Tip: Reduce Cardinality of Work in Progress When following longer paths, you'll encounter duplicates. If you're not interested in *all the possible paths* -- but just distinct information from stages of the path -- make sure that you eagerly eliminate duplicates, so that later matches don't have to be executed many multiple times.
____
We can reduce the WIP in our query by doing the counting of common members first and then filtering out the groups we're already a member of:
[source,cypher]
----
MATCH (member:Member {name: "Mark Needham"})-[:MEMBER_OF]->(group:Group)<-[:MEMBER_OF]-(other:Member)-[:MEMBER_OF]->(otherGroup:Group)
WITH otherGroup, member, COUNT(*) AS commonMembers
WHERE NOT (member)-[:MEMBER_OF]->(otherGroup)
RETURN otherGroup, commonMembers
ORDER BY commonMembers DESC
LIMIT 5
----
This gets us back down to something closer to the running time/db hits of our initial query:
[source,text]
----
Cypher version: CYPHER 2.3, planner: COST. 1097114 total db hits in 1004 ms.
---- | null | null | [
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] | neo4j-cypher-avoid-duplicate-calls-to-not-patterns | https://markhneedham.com/blog/2016/01/17/neo4j-cypher-avoid-duplicate-calls-to-not-patterns |
false | 2016-01-24 22:01:43 | Clojure: First steps with reducers | [
"clojure"
] | [
"Clojure"
] | I've been playing around with Clojure a bit today in preparation for https://skillsmatter.com/meetups/7794-using-clojure-neo4j-to-build-a-meetup-recommendation-engine[a talk I'm giving next week] and found myself writing the following code to apply the same function to three different scores:
[source,clojure]
----
(defn log2 [n]
(/ (Math/log n) (Math/log 2)))
(defn score-item [n]
(if (= n 0) 0 (log2 n)))
(+ (score-item 12) (score-item 13) (score-item 5)) 9.60733031374961
----
I'd forgotten about folding over a collection but quickly remembered that I could achieve the same result with the following code:
[source,clojure]
----
(reduce #(+ %1 (score-item %2)) 0 [12 13 5]) 9.60733031374961
----
The added advantage here is that if I want to add a 4th score to the mix all I need to do is append it to the end of the vector:
[source,clojure]
----
(reduce #(+ %1 (score-item %2)) 0 [12 13 5 6]) 12.192292814470767
----
However, while Googling to remind myself of the order of the arguments to reduce I kept coming across http://clojure.org/reference/reducers[articles and documentation about reducers] which I'd heard about but never used.
As I understand they're used to http://ianrumford.github.io/blog/2013/08/25/some-trivial-examples-of-using-clojure-reducers/[achieve performance gains and easier composition of functions over collections] so I'm not sure how useful they'll be to me but I thought I'd give them a try.
Our first step is to bring the namespace into scope:
[source,clojure]
----
(require '[clojure.core.reducers :as r])
----
Now we can compute the same result using the +++<cite>+++reduce+++</cite>+++ function:
[source,clojure]
----
(r/reduce #(+ %1 (score-item %2)) 0 [12 13 5 6]) 12.192292814470767
----
So far, so identical. If we wanted to calculate individual scores and then filter out those below a certain threshold the code would behave a little differently:
[source,clojure]
----
(->>[12 13 5 6]
(map score-item)
(filter #(> % 3))) (3.5849625007211565 3.700439718141092)
(->> [12 13 5 6]
(r/map score-item)
(r/filter #(> % 3))) #object[clojure.core.reducers$folder$reify__19192 0x5d0edf21 "clojure.core.reducers$folder$reify__19192@5d0edf21"]
----
Instead of giving us a vector of scores the reducers version returns a reducer which can pass into +++<cite>+++reduce+++</cite>+++ or +++<cite>+++fold+++</cite>+++ if we want an accumulated result or +++<cite>+++into+++</cite>+++ if we want to output a collection. In this case we want the latter:
[source,clojure]
----
(->> [12 13 5 6]
(r/map score-item)
(r/filter #(> % 3))
(into [])) (3.5849625007211565 3.700439718141092)
----
With a measly 4 item collection I don't think the reducers are going to provide much speed improvement here but we'd need to use the +++<cite>+++http://clojure.org/reference/reducers#_using_reducers[fold]+++</cite>+++ function if we want processing of the collection to be done in parallel.
One for next time! | null | null | [
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] | clojure-first-steps-with-reducers | https://markhneedham.com/blog/2016/01/24/clojure-first-steps-with-reducers |
false | 2016-06-18 07:38:04 | Python: Regex - matching foreign characters/unicode letters | [
"python"
] | [
"Python"
] | I've been back in the land of screen scrapping this week extracting data from the http://gameofthrones.wikia.com/wiki[Game of Thrones wiki] and needed to write a regular expression to pull out characters and actors.
Here are some examples of the format of the data: ~~~text Peter Dinklage as Tyrion Lannister Daniel Naprous as Oznak zo Pahl(credited as Stunt Performer) Filip LoziΔ as Young Nobleman Morgan C. Jones as a Braavosi captain Adewale Akinnuoye-Agbaje as Malko ~~~
So the pattern is: ~~~text +++<actor>+++as +++<character>+++~~~
optionally followed by some other text that we're not interested in.
The output I want to get is: ~~~text Peter Dinklage, Tyrion Lannister Daniel Naprous, Oznak zo Pahl Filip LoziΔ, Young Nobleman Morgan C. Jones, a Braavosi captain Adewale Akinnuoye-Agbaje, Malko ~~~
I started using the 'split' command on the word 'as' but that broke down when I realised some of the characters had the letters 'as' in the middle of their name. So regex it is!
This was my first attempt: ~~~python import re strings = [ "Peter Dinklage as Tyrion Lannister", "Filip LoziΔ as Young Nobleman", "Daniel Naprous as Oznak zo Pahl(credited as Stunt Performer)", "Morgan C. Jones as a Braavosi captain", "Adewale Akinnuoye-Agbaje as Malko" ] regex = "([A-Za-z\-'\. ]*) as ([A-Za-z\-'\. ]*)" for string in strings: print string match = re.match( regex, string) if match is not None: print match.groups() else: print "FAIL" print "" ~~~ ~~~text Peter Dinklage as Tyrion Lannister ('Peter Dinklage', 'Tyrion Lannister') Filip LoziΔ as Young Nobleman FAIL Daniel Naprous as Oznak zo Pahl(credited as Stunt Performer) ('Daniel Naprous', 'Oznak zo Pahl') Morgan C. Jones as a Braavosi captain ('Morgan C. Jones', 'a Braavosi captain') Adewale Akinnuoye-Agbaje as Malko ('Adewale Akinnuoye-Agbaje', 'Malko') ~~~
It works for 4 of the 5 scenarios but now for Filip LoziΔ. The 'Δ' character causes the issue so we need to be able to match foreign characters which the current charset I defined in the regex doesn't capture.
I came across http://stackoverflow.com/questions/3009993/regex-what-would-be-regex-for-matching-foreign-characters[this Stack Overflow post] which said that in some regex libraries you can use '\p\{L}' to match all letters. I gave that a try: ~~~python regex = "([\p\{L}\-'\. ]*) as ([\p\{L}\-'\. ]*)" ~~~
And then re-ran the script: ~~~text Peter Dinklage as Tyrion Lannister FAIL Daniel Naprous as Oznak zo Pahl(credited as Stunt Performer) FAIL Filip LoziΔ as Young Nobleman FAIL Morgan C. Jones as a Braavosi captain FAIL Adewale Akinnuoye-Agbaje as Malko FAIL ~~~
Hmmm, not sure if I did it wrong or if that isn't available in Python. I'll assume the latter but feel free to correct me in the comments and I'll update the post.
I went search again and found http://stackoverflow.com/questions/8923949/matching-only-a-unicode-letter-in-python-re[this post] which suggested another approach:
____
You can construct a new character class: [{caret}\W\d_] instead of \w. Translated into English, it means "Any character that is not a non-alphanumeric character ([{caret}\W] is the same as \w), but that is also not a digit and not an underscore".
____
Let's try plugging that in: ~~~python regex = "([A-Za-z\-'\.{caret}\W\d_ ]*) as ([A-Za-z\-'\.{caret}\W\d_ ]*)" ~~~ ~~~text Peter Dinklage as Tyrion Lannister ('Peter Dinklage', 'Tyrion Lannister') Daniel Naprous as Oznak zo Pahl(credited as Stunt Performer) ('Daniel Naprous as Oznak zo Pahl(credited', 'Stunt Performer)') Filip LoziΔ as Young Nobleman ('Filip Lozi\xc4\x87', 'Young Nobleman') Morgan C. Jones as a Braavosi captain ('Morgan C. Jones', 'a Braavosi captain') Adewale Akinnuoye-Agbaje as Malko ('Adewale Akinnuoye-Agbaje', 'Malko') ~~~
So that's fixed Filip but now Daniel Naprous is being incorrectly parsed.
For Attempt #4 I decided to try excluding what I don't want instead: ~~~python regex = "([{caret}0-9\(]*) as ([{caret}0-9\(]*)" ~~~ ~~~text Peter Dinklage as Tyrion Lannister ('Peter Dinklage', 'Tyrion Lannister') Daniel Naprous as Oznak zo Pahl(credited as Stunt Performer) ('Daniel Naprous', 'Oznak zo Pahl') Filip LoziΔ as Young Nobleman ('Filip Lozi\xc4\x87', 'Young Nobleman') Morgan C. Jones as a Braavosi captain ('Morgan C. Jones', 'a Braavosi captain') Adewale Akinnuoye-Agbaje as Malko ('Adewale Akinnuoye-Agbaje', 'Malko') ~~~
That does the job but has exposed my lack of regex skillz. If you know a better way let me know in the comments.+++</character>++++++</actor>+++ | null | null | [
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] | python-regex-matching-foreign-charactersunicode-letters | https://markhneedham.com/blog/2016/06/18/python-regex-matching-foreign-charactersunicode-letters |
false | 2016-06-19 07:22:57 | Unix: Split string using separator | [
"unix"
] | [
"Shell Scripting"
] | I recently found myself needing to iterate over a bunch of '/' separated strings on the command line and extract just the text after the last '/'.
e.g. an example of one of the strings
[source,text]
----
A/B/C
----
I wanted to write some code that could split on '/' and then pick the 3rd item in the resulting collection.
One way of doing this is to echo the string and then pipe it through cut:
[source,bash]
----
$ string="A/B/C"
$ echo ${string} | cut -d"/" -f3
C
----
or awk:
[source,bash]
----
$ echo ${string} | awk -F"/" '{ print $3}'
C
----
I don't like having to echo the string - it feels a bit odd so I wanted to see if there was a way to do the parsing more 'inline'.
I came across http://stackoverflow.com/questions/918886/how-do-i-split-a-string-on-a-delimiter-in-bash[this post] which explains how to change the internal field separator (IFS) on the shell and then parse the string into an array using http://ss64.com/bash/read.html[read]. I gave it a try:
[source,bash]
----
$ IFS="/" read -ra ADDR <<< "${string}"; echo ${ADDR[2]}
C
----
Works! We can even refer to the last item in the array using -1 instead of it's absolute position:
[source,bash]
----
$ IFS="/" read -ra ADDR <<< "${string}"; echo ${ADDR[-1]}
C
----
I'd not come across this use of the 'read' function before. The key is the '-a' parameter. From the man page:
____
-a aname The words are assigned to sequential indices of the array variable aname, starting at 0. All elements are removed from aname before the assignment. Other name arguments are ignored.
____
So we're resetting the internal field separator and then reading the string into another variable as an array split on the '/' character.
Pretty neat although now it's longer than the original command and I'm sure I'll forget the syntax.
Further down the page is another suggestion which seems even harder to remember but is much shorter:
[source,bash]
----
$ echo ${string##*/}
C
----
This drops from the beginning of the string up until the last occurrence of '/' which is exactly what we want.
This way is the nicest and doesn't require any echoing if we just want to assign the result to a variable. The echo is only used here to see the output. | null | null | [
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] | unix-split-string-using-separator | https://markhneedham.com/blog/2016/06/19/unix-split-string-using-separator |
false | 2016-06-19 08:36:46 | Unix: Find all text below string in a file | [
"unix"
] | [
"Shell Scripting"
] | I recently wanted to parse some text out of a bunch of files so that I could do some sentiment analysis on it. Luckily the text I want is at the end of the file and doesn't have anything after it but there is text before it that I want to get rid.
The files look like this:
[source,text]
----
# text I don't care about
= Heading of the bit I care about
# text I care about
----
In other words I want to find the line that contains the Heading and then get all the text after that point.
I figured sed was the tool for the job but my knowledge of the syntax was a bit rusty. Luckily http://stackoverflow.com/questions/7103531/how-to-get-the-part-of-file-after-the-line-that-matches-grep-expression-first[this post] served as a refresher.
Effectively what we want to do is delete from the beginning of the file up until the line after the heading. We can do this with the following command:
[source,bash]
----
$ cat /tmp/foo.txt
# text I don't care about
= Heading of the bit I care about
# text I care about
----
[source,bash]
----
$ cat /tmp/foo.txt | sed '1,/Heading of the bit I care about/d'
# text I care about
----
That still leaves an extra empty line after the heading which is a bit annoying but easy enough to get rid of by passing another command to sed that strips empty lines:
[source,bash]
----
$ cat /tmp/foo.txt | sed -e '1,/Heading of the bit I care about/d' -e '/^\s*$/d'
# text I care about
----
The only difference here is that we're now passing the '-e' flag to allow us to specify multiple commands. If we just pass them sequentially then the 2nd one will be interpreted as the name of a file. | null | null | [
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] | unix-find-all-text-below-string-in-a-file | https://markhneedham.com/blog/2016/06/19/unix-find-all-text-below-string-in-a-file |
false | 2016-06-30 21:28:35 | Python: BeautifulSoup - Insert tag | [
"python"
] | [
"Python"
] | I've been scraping the Game of Thrones wiki in preparation http://www.meetup.com/Women-Who-Code-London/events/231014802/[for a meetup at Women Who Code next week] and while attempting to extract character allegiances I wanted to insert missing line breaks to separate different allegiances.
I initially tried http://stackoverflow.com/questions/14652706/python-beautifulsoup-add-tags-around-found-keyword[creating a line break] like this:
[source,python]
----
>>> from bs4 import BeautifulSoup
>>> tag = BeautifulSoup("<br />", "html.parser")
>>> tag
<br/>
----
It looks like it should work but later on in my script I check the 'name' attribute to work out whether I've got a line break and it doesn't return the value I expected it to:
[source,python]
----
>>> tag.name
u'[document]'
----
My script assumes it's going to return the string 'br' so I needed another way of creating the tag. The following does the trick:
[source,python]
----
>>> from bs4 import Tag
>>> tag = Tag(name = "br")
>>> tag
<br></br>
----
[source,python]
----
>>> tag.name
'br'
----
That's all for now, back to scraping for me! | null | null | [
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] | python-beautifulsoup-insert-tag | https://markhneedham.com/blog/2016/06/30/python-beautifulsoup-insert-tag |
false | 2016-06-01 05:53:38 | Unix parallel: Populating all the USB sticks | [
"shell-scripting-2"
] | [
"Shell Scripting"
] | The day before Graph Connect Europe 2016 we needed to create a bunch of USB sticks containing Neo4j and the training materials and eventually iterated our way to a half decent approach which made use of the https://www.gnu.org/software/parallel/parallel_tutorial.html[GNU parallel command] which I've always wanted to use!
But first I needed to get a USB hub so I could do lots of them at the same time. I bought the https://www.amazon.co.uk/gp/product/B00ID270ZU/ref=oh_aui_detailpage_o08_s00?ie=UTF8&psc=1[EasyAcc USB 3.0] but there are lots of other ones that do the same job.
Next I mouunted all the USB sticks and then renamed the volumes to be NEO4J1 \-> NEO4J7:
[source,bash]
----
for i in 1 2 3 4 5 6 7; do diskutil renameVolume "USB DISK" NEO4J${i}; done
----
I then created a bash function called 'duplicate' to do the copying work:
[source,bash]
----
function duplicate() {
i=${1}
echo ${i}
time rsync -avP --size-only --delete --exclude '.*' --omit-dir-times /Users/markneedham/Downloads/graph-connect-europe-2016/ /Volumes/NEO4J${i}/
}
----
We can now call this function in parallel like so:
[source,bash]
----
seq 1 7 | parallel duplicate
----
And that's it. We didn't get a 7x improvement in the throughput of USB creation from doing 7 in parallel but it took ~ 9 minutes to complete 7 compared to 5 minutes each. Presumably there's still some part of the copying that is sequential further down - https://en.wikipedia.org/wiki/Amdahl%27s_law[Amdahl's law] #ftw.
I want to go and find other things that I can use pipe into parallel now! | null | null | [
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] | unix-parallel-populating-all-the-usb-sticks | https://markhneedham.com/blog/2016/06/01/unix-parallel-populating-all-the-usb-sticks |
false | 2016-06-24 16:56:17 | Unix: Find files greater than date | [
"unix"
] | [
"Shell Scripting"
] | For the latter part of the week I've been running some tests against Neo4j which generate a bunch of log files and I wanted to filter those files based on the time they were created to do some further analysis.
This is an example of what the directory listing looks like:
[source,text]
----
$ ls -alh foo/database-agent-*
-rw-r--r-- 1 markneedham wheel 2.5K 23 Jun 14:00 foo/database-agent-mac17f73-1-logs-archive-201606231300176.tar.gz
-rw-r--r-- 1 markneedham wheel 8.6K 23 Jun 11:49 foo/database-agent-mac19b6b-1-logs-archive-201606231049507.tar.gz
-rw-r--r-- 1 markneedham wheel 8.6K 23 Jun 11:49 foo/database-agent-mac1f427-1-logs-archive-201606231049507.tar.gz
-rw-r--r-- 1 markneedham wheel 2.5K 23 Jun 14:00 foo/database-agent-mac29389-1-logs-archive-201606231300176.tar.gz
-rw-r--r-- 1 markneedham wheel 11K 23 Jun 13:44 foo/database-agent-mac3533f-1-logs-archive-201606231244152.tar.gz
-rw-r--r-- 1 markneedham wheel 4.8K 23 Jun 14:00 foo/database-agent-mac35563-1-logs-archive-201606231300176.tar.gz
-rw-r--r-- 1 markneedham wheel 3.8K 23 Jun 13:44 foo/database-agent-mac35f7e-1-logs-archive-201606231244165.tar.gz
-rw-r--r-- 1 markneedham wheel 4.8K 23 Jun 14:00 foo/database-agent-mac40798-1-logs-archive-201606231300176.tar.gz
-rw-r--r-- 1 markneedham wheel 12K 23 Jun 13:44 foo/database-agent-mac490bf-1-logs-archive-201606231244151.tar.gz
-rw-r--r-- 1 markneedham wheel 2.5K 23 Jun 14:00 foo/database-agent-mac5f094-1-logs-archive-201606231300189.tar.gz
-rw-r--r-- 1 markneedham wheel 5.8K 23 Jun 14:00 foo/database-agent-mac636b8-1-logs-archive-201606231300176.tar.gz
-rw-r--r-- 1 markneedham wheel 9.5K 23 Jun 11:49 foo/database-agent-mac7e165-1-logs-archive-201606231049507.tar.gz
-rw-r--r-- 1 markneedham wheel 2.7K 23 Jun 11:49 foo/database-agent-macab7f1-1-logs-archive-201606231049507.tar.gz
-rw-r--r-- 1 markneedham wheel 2.8K 23 Jun 13:44 foo/database-agent-macbb8e1-1-logs-archive-201606231244151.tar.gz
-rw-r--r-- 1 markneedham wheel 3.1K 23 Jun 11:49 foo/database-agent-macbcbe8-1-logs-archive-201606231049520.tar.gz
-rw-r--r-- 1 markneedham wheel 13K 23 Jun 13:44 foo/database-agent-macc8177-1-logs-archive-201606231244152.tar.gz
-rw-r--r-- 1 markneedham wheel 3.8K 23 Jun 13:44 foo/database-agent-maccd92c-1-logs-archive-201606231244151.tar.gz
-rw-r--r-- 1 markneedham wheel 3.9K 23 Jun 13:44 foo/database-agent-macdf24f-1-logs-archive-201606231244165.tar.gz
-rw-r--r-- 1 markneedham wheel 3.1K 23 Jun 11:49 foo/database-agent-mace075e-1-logs-archive-201606231049520.tar.gz
-rw-r--r-- 1 markneedham wheel 3.1K 23 Jun 11:49 foo/database-agent-mace8859-1-logs-archive-201606231049507.tar.gz
----
I wanted to split the files in half so that I could have the ones created before and after 12pm on the 23rd June.
I discovered that this type of filtering is actually http://serverfault.com/questions/122824/linux-using-find-to-locate-files-older-than-date[quite easy to do with the 'find' command]. So if I want to get the files after 12pm I could write the following:
[source,bash]
----
$ find foo -name database-agent* -newermt "Jun 23, 2016 12:00" -ls
121939705 8 -rw-r--r-- 1 markneedham wheel 2524 23 Jun 14:00 foo/database-agent-mac17f73-1-logs-archive-201606231300176.tar.gz
121939704 8 -rw-r--r-- 1 markneedham wheel 2511 23 Jun 14:00 foo/database-agent-mac29389-1-logs-archive-201606231300176.tar.gz
121934591 24 -rw-r--r-- 1 markneedham wheel 11294 23 Jun 13:44 foo/database-agent-mac3533f-1-logs-archive-201606231244152.tar.gz
121939707 16 -rw-r--r-- 1 markneedham wheel 4878 23 Jun 14:00 foo/database-agent-mac35563-1-logs-archive-201606231300176.tar.gz
121934612 8 -rw-r--r-- 1 markneedham wheel 3896 23 Jun 13:44 foo/database-agent-mac35f7e-1-logs-archive-201606231244165.tar.gz
121939708 16 -rw-r--r-- 1 markneedham wheel 4887 23 Jun 14:00 foo/database-agent-mac40798-1-logs-archive-201606231300176.tar.gz
121934589 24 -rw-r--r-- 1 markneedham wheel 12204 23 Jun 13:44 foo/database-agent-mac490bf-1-logs-archive-201606231244151.tar.gz
121939720 8 -rw-r--r-- 1 markneedham wheel 2510 23 Jun 14:00 foo/database-agent-mac5f094-1-logs-archive-201606231300189.tar.gz
121939706 16 -rw-r--r-- 1 markneedham wheel 5912 23 Jun 14:00 foo/database-agent-mac636b8-1-logs-archive-201606231300176.tar.gz
121934588 8 -rw-r--r-- 1 markneedham wheel 2895 23 Jun 13:44 foo/database-agent-macbb8e1-1-logs-archive-201606231244151.tar.gz
121934590 32 -rw-r--r-- 1 markneedham wheel 13427 23 Jun 13:44 foo/database-agent-macc8177-1-logs-archive-201606231244152.tar.gz
121934587 8 -rw-r--r-- 1 markneedham wheel 3882 23 Jun 13:44 foo/database-agent-maccd92c-1-logs-archive-201606231244151.tar.gz
121934611 8 -rw-r--r-- 1 markneedham wheel 3970 23 Jun 13:44 foo/database-agent-macdf24f-1-logs-archive-201606231244165.tar.gz
----
And to get the ones before 12pm:
[source,bash]
----
$ find foo -name database-agent* -not -newermt "Jun 23, 2016 12:00" -ls
121879391 24 -rw-r--r-- 1 markneedham wheel 8856 23 Jun 11:49 foo/database-agent-mac19b6b-1-logs-archive-201606231049507.tar.gz
121879394 24 -rw-r--r-- 1 markneedham wheel 8772 23 Jun 11:49 foo/database-agent-mac1f427-1-logs-archive-201606231049507.tar.gz
121879390 24 -rw-r--r-- 1 markneedham wheel 9702 23 Jun 11:49 foo/database-agent-mac7e165-1-logs-archive-201606231049507.tar.gz
121879393 8 -rw-r--r-- 1 markneedham wheel 2812 23 Jun 11:49 foo/database-agent-macab7f1-1-logs-archive-201606231049507.tar.gz
121879413 8 -rw-r--r-- 1 markneedham wheel 3144 23 Jun 11:49 foo/database-agent-macbcbe8-1-logs-archive-201606231049520.tar.gz
121879414 8 -rw-r--r-- 1 markneedham wheel 3131 23 Jun 11:49 foo/database-agent-mace075e-1-logs-archive-201606231049520.tar.gz
121879392 8 -rw-r--r-- 1 markneedham wheel 3130 23 Jun 11:49 foo/database-agent-mace8859-1-logs-archive-201606231049507.tar.gz
----
Or we could even find the ones last modified between 12pm and 2pm:
[source,bash]
----
$ find foo -name database-agent* -not -newermt "Jun 23, 2016 14:00" -newermt "Jun 23, 2016 12:00" -ls
121934591 24 -rw-r--r-- 1 markneedham wheel 11294 23 Jun 13:44 foo/database-agent-mac3533f-1-logs-archive-201606231244152.tar.gz
121934612 8 -rw-r--r-- 1 markneedham wheel 3896 23 Jun 13:44 foo/database-agent-mac35f7e-1-logs-archive-201606231244165.tar.gz
121934589 24 -rw-r--r-- 1 markneedham wheel 12204 23 Jun 13:44 foo/database-agent-mac490bf-1-logs-archive-201606231244151.tar.gz
121934588 8 -rw-r--r-- 1 markneedham wheel 2895 23 Jun 13:44 foo/database-agent-macbb8e1-1-logs-archive-201606231244151.tar.gz
121934590 32 -rw-r--r-- 1 markneedham wheel 13427 23 Jun 13:44 foo/database-agent-macc8177-1-logs-archive-201606231244152.tar.gz
121934587 8 -rw-r--r-- 1 markneedham wheel 3882 23 Jun 13:44 foo/database-agent-maccd92c-1-logs-archive-201606231244151.tar.gz
121934611 8 -rw-r--r-- 1 markneedham wheel 3970 23 Jun 13:44 foo/database-agent-macdf24f-1-logs-archive-201606231244165.tar.gz
----
Or we can filter by relative time e.g. to find the files last modified in the last 1 day, 5 hours:
[source,bash]
----
$ find foo -name database-agent* -mtime -1d5h -ls
121939705 8 -rw-r--r-- 1 markneedham wheel 2524 23 Jun 14:00 foo/database-agent-mac17f73-1-logs-archive-201606231300176.tar.gz
121939704 8 -rw-r--r-- 1 markneedham wheel 2511 23 Jun 14:00 foo/database-agent-mac29389-1-logs-archive-201606231300176.tar.gz
121934591 24 -rw-r--r-- 1 markneedham wheel 11294 23 Jun 13:44 foo/database-agent-mac3533f-1-logs-archive-201606231244152.tar.gz
121939707 16 -rw-r--r-- 1 markneedham wheel 4878 23 Jun 14:00 foo/database-agent-mac35563-1-logs-archive-201606231300176.tar.gz
121934612 8 -rw-r--r-- 1 markneedham wheel 3896 23 Jun 13:44 foo/database-agent-mac35f7e-1-logs-archive-201606231244165.tar.gz
121939708 16 -rw-r--r-- 1 markneedham wheel 4887 23 Jun 14:00 foo/database-agent-mac40798-1-logs-archive-201606231300176.tar.gz
121934589 24 -rw-r--r-- 1 markneedham wheel 12204 23 Jun 13:44 foo/database-agent-mac490bf-1-logs-archive-201606231244151.tar.gz
121939720 8 -rw-r--r-- 1 markneedham wheel 2510 23 Jun 14:00 foo/database-agent-mac5f094-1-logs-archive-201606231300189.tar.gz
121939706 16 -rw-r--r-- 1 markneedham wheel 5912 23 Jun 14:00 foo/database-agent-mac636b8-1-logs-archive-201606231300176.tar.gz
121934588 8 -rw-r--r-- 1 markneedham wheel 2895 23 Jun 13:44 foo/database-agent-macbb8e1-1-logs-archive-201606231244151.tar.gz
121934590 32 -rw-r--r-- 1 markneedham wheel 13427 23 Jun 13:44 foo/database-agent-macc8177-1-logs-archive-201606231244152.tar.gz
121934587 8 -rw-r--r-- 1 markneedham wheel 3882 23 Jun 13:44 foo/database-agent-maccd92c-1-logs-archive-201606231244151.tar.gz
121934611 8 -rw-r--r-- 1 markneedham wheel 3970 23 Jun 13:44 foo/database-agent-macdf24f-1-logs-archive-201606231244165.tar.gz
----
Or the ones modified more than 1 day, 5 hours ago:
[source,bash]
----
$ find foo -name database-agent* -mtime +1d5h -ls
121879391 24 -rw-r--r-- 1 markneedham wheel 8856 23 Jun 11:49 foo/database-agent-mac19b6b-1-logs-archive-201606231049507.tar.gz
121879394 24 -rw-r--r-- 1 markneedham wheel 8772 23 Jun 11:49 foo/database-agent-mac1f427-1-logs-archive-201606231049507.tar.gz
121879390 24 -rw-r--r-- 1 markneedham wheel 9702 23 Jun 11:49 foo/database-agent-mac7e165-1-logs-archive-201606231049507.tar.gz
121879393 8 -rw-r--r-- 1 markneedham wheel 2812 23 Jun 11:49 foo/database-agent-macab7f1-1-logs-archive-201606231049507.tar.gz
121879413 8 -rw-r--r-- 1 markneedham wheel 3144 23 Jun 11:49 foo/database-agent-macbcbe8-1-logs-archive-201606231049520.tar.gz
121879414 8 -rw-r--r-- 1 markneedham wheel 3131 23 Jun 11:49 foo/database-agent-mace075e-1-logs-archive-201606231049520.tar.gz
121879392 8 -rw-r--r-- 1 markneedham wheel 3130 23 Jun 11:49 foo/database-agent-mace8859-1-logs-archive-201606231049507.tar.gz
----
There are lots of other flags you can pass to find but these ones did exactly what I wanted! | null | null | [
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] | unix-find-files-greater-than-date | https://markhneedham.com/blog/2016/06/24/unix-find-files-greater-than-date |
false | 2016-12-04 12:37:49 | Kubernetes: Simulating a network partition | [
"neo4j",
"kubernetes"
] | [
"neo4j",
"Kubernetes"
] | A couple of weeks ago I wrote http://www.markhneedham.com/blog/2016/11/25/kubernetes-spinning-up-a-neo4j-3-1-causal-cluster/[a post explaining how to create a Neo4j causal cluster using Kubernetes] and \... the I wanted to work out how to simulate a network partition which would put the leader on the minority side and force an election.
We've done this on our internal tooling on AWS using the +++<cite>+++https://en.wikipedia.org/wiki/Iptables[iptables]+++</cite>+++ command but unfortunately that isn't available in my container, which only has the utilities provided by https://busybox.net/about.html[BusyBox].
Luckily one of these is +++<cite>+++route+++</cite>+++ command which will allow us to achieve the same thing.
To recap, I have 3 Neo4j pods up and running:
[source,bash]
----
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
neo4j-0 1/1 Running 0 6h
neo4j-1 1/1 Running 0 6h
neo4j-2 1/1 Running 0 6h
----
And we can check that the +++<cite>+++route+++</cite>+++ command is available:
[source,bash]
----
$ kubectl exec neo4j-0 -- ls -alh /sbin/route
lrwxrwxrwx 1 root root 12 Oct 18 18:58 /sbin/route -> /bin/busybox
----
Let's have a look what role each server is currently playing:
[source,bash]
----
$ kubectl exec neo4j-0 -- bin/cypher-shell "CALL dbms.cluster.role()"
role
"FOLLOWER"
Bye!
----
[source,bash]
----
$ kubectl exec neo4j-1 -- bin/cypher-shell "CALL dbms.cluster.role()"
role
"FOLLOWER"
Bye!
----
[source,bash]
----
$ kubectl exec neo4j-2 -- bin/cypher-shell "CALL dbms.cluster.role()"
role
"LEADER"
Bye!
----
Slight aside: I'm able to call +++<cite>+++cypher-shell+++</cite>+++ without a user and password because I've disable authorisation by putting the following in +++<cite>+++conf/neo4j.conf+++</cite>+++:
[source,text]
----
dbms.connector.bolt.enabled=true
----
Back to the network partitioning\...we need to partition away +++<cite>+++neo4j-2+++</cite>+++ from the other two servers which we can do by running the following commands:
[source,bash]
----
$ kubectl exec neo4j-2 -- route add -host neo4j-0.neo4j.default.svc.cluster.local reject && \
kubectl exec neo4j-2 -- route add -host neo4j-1.neo4j.default.svc.cluster.local reject && \
kubectl exec neo4j-0 -- route add -host neo4j-2.neo4j.default.svc.cluster.local reject && \
kubectl exec neo4j-1 -- route add -host neo4j-2.neo4j.default.svc.cluster.local reject
----
If we look at the logs of neo4j-2 we can see that it's stepped down after being disconnected from the other two servers:
[source,text]
----
$ kubectl exec neo4j-2 -- cat logs/debug.log
...
2016-12-04 11:30:10.186+0000 INFO [o.n.c.c.c.RaftMachine] Moving to FOLLOWER state after not receiving heartbeat responses in this election timeout period. Heartbeats received: []
...
----
Who's taken over as leader?
[source,bash]
----
$ kubectl exec neo4j-0 -- bin/cypher-shell "CALL dbms.cluster.role()"
role
"LEADER"
Bye!
----
[source,bash]
----
$ kubectl exec neo4j-1 -- bin/cypher-shell "CALL dbms.cluster.role()"
role
"FOLLOWER"
Bye!
----
[source,bash]
----
$ kubectl exec neo4j-2 -- bin/cypher-shell "CALL dbms.cluster.role()"
role
"FOLLOWER"
Bye!
----
Looks like neo4j-0! Let's put some data into the database:
[source,bash]
----
$ kubectl exec neo4j-0 -- bin/cypher-shell "CREATE (:Person {name: 'Mark'})"
Added 1 nodes, Set 1 properties, Added 1 labels
Bye!
----
Let's check if that node made it to the other two servers. We'd expect it to be on neo4j-1 but not on neo4j-2:
[source,bash]
----
$ kubectl exec neo4j-1 -- bin/cypher-shell "MATCH (p:Person) RETURN p"
p
(:Person {name: "Mark"})
Bye!
----
[source,bash]
----
$ kubectl exec neo4j-2 -- bin/cypher-shell "MATCH (p:Person) RETURN p"
Bye!
----
On neo4j-2 we'll repeatedly see these types of entries in the log as its election timeout triggers but fails to get any responses to the vote requests it sends out:
[source,text]
----
$ kubectl exec neo4j-2 -- cat logs/debug.log
...
2016-12-04 11:32:56.735+0000 INFO [o.n.c.c.c.RaftMachine] Election timeout triggered
2016-12-04 11:32:56.736+0000 INFO [o.n.c.c.c.RaftMachine] Election started with vote request: Vote.Request from MemberId{ca9b954c} {term=11521, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467} and members: [MemberId{484178c4}, MemberId{0acdb8dd}, MemberId{ca9b954c}]
...
----
We can see those vote requests by looking at the +++<cite>+++raft-messages.log+++</cite>+++ which can be enabled by setting the following property in +++<cite>+++conf/neo4j.conf+++</cite>+++:
[source,text]
----
causal_clustering.raft_messages_log_enable=true
----
[source,text]
----
$ kubectl exec neo4j-2 -- cat logs/raft-messages.log
...
11:33:42.101 -->MemberId{484178c4}: Request: Vote.Request from MemberId{ca9b954c} {term=11537, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467}
11:33:42.102 -->MemberId{0acdb8dd}: Request: Vote.Request from MemberId{ca9b954c} {term=11537, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467}
11:33:45.432 -->MemberId{484178c4}: Request: Vote.Request from MemberId{ca9b954c} {term=11538, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467}
11:33:45.433 -->MemberId{0acdb8dd}: Request: Vote.Request from MemberId{ca9b954c} {term=11538, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467}
11:33:48.362 -->MemberId{484178c4}: Request: Vote.Request from MemberId{ca9b954c} {term=11539, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467}
11:33:48.362 -->MemberId{0acdb8dd}: Request: Vote.Request from MemberId{ca9b954c} {term=11539, candidate=MemberId{ca9b954c}, lastAppended=68, lastLogTerm=11467}
...
----
To 'heal' the network partition we just need to delete all the commands we ran earlier:
[source,bash]
----
$ kubectl exec neo4j-2 -- route delete neo4j-0.neo4j.default.svc.cluster.local reject && \
kubectl exec neo4j-2 -- route delete neo4j-1.neo4j.default.svc.cluster.local reject && \
kubectl exec neo4j-0 -- route delete neo4j-2.neo4j.default.svc.cluster.local reject && \
kubectl exec neo4j-1 -- route delete neo4j-2.neo4j.default.svc.cluster.local reject
----
Now let's check that neo4j-2 now has the node that we created earlier:
[source,bash]
----
$ kubectl exec neo4j-2 -- bin/cypher-shell "MATCH (p:Person) RETURN p"
p
(:Person {name: "Mark"})
Bye!
----
That's all for now! | null | null | [
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] | kubernetes-simulating-a-network-partition | https://markhneedham.com/blog/2016/12/04/kubernetes-simulating-a-network-partition |
false | 2016-12-21 07:11:50 | Docker: Unknown - Unable to query docker version: x509: certificate is valid for | [
"docker"
] | [
"Docker"
] | I was playing around with Docker locally and somehow ended up with this error when I tried to list my https://docs.docker.com/machine/overview/[docker machines]:
[source,bash]
----
$ docker-machine ls
NAME ACTIVE DRIVER STATE URL SWARM DOCKER ERRORS
default - virtualbox Running tcp://192.168.99.101:2376 Unknown Unable to query docker version: Get https://192.168.99.101:2376/v1.15/version: x509: certificate is valid for 192.168.99.100, not 192.168.99.101
----
My Google Fu was weak I couldn't find any suggestions for what this might mean so I tried shutting it down and starting it again! </>
On the restart I actually got some helpful advice: ~~~bash $ docker-machine stop Stopping "default"\... Machine "default" was stopped. ~~~ ~~~bash $ docker-machine start Starting "default"\... (default) Check network to re-create if needed\... (default) Waiting for an IP\... Machine "default" was started. Waiting for SSH to be available\... Detecting the provisioner\... Started machines may have new IP addresses. You may need to re-run the `docker-machine env` command. ~~~
So I tried that: ~~~bash $ docker-machine env Error checking TLS connection: Error checking and/or regenerating the certs: There was an error validating certificates for host "192.168.99.101:2376": x509: certificate is valid for 192.168.99.100, not 192.168.99.101 You can attempt to regenerate them using 'docker-machine regenerate-certs [name]'. Be advised that this will trigger a Docker daemon restart which will stop running containers. ~~~
And then regenerates my certificates: ~~~bash $ docker-machine regenerate-certs Regenerate TLS machine certs? Warning: this is irreversible. (y/n): y Regenerating TLS certificates Waiting for SSH to be available\... Detecting the provisioner\... Copying certs to the local machine directory\... Copying certs to the remote machine\... Setting Docker configuration on the remote daemon\... ~~~
And now everything is happy again! ~~~bash $ docker-machine ls NAME ACTIVE DRIVER STATE URL SWARM DOCKER ERRORS default - virtualbox Running tcp://192.168.99.101:2376 v1.9.0 ~~~ | null | null | [
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] | docker-unknown-unable-to-query-docker-version-x509-certificate-is-valid-for | https://markhneedham.com/blog/2016/12/21/docker-unknown-unable-to-query-docker-version-x509-certificate-is-valid-for |
false | 2016-12-24 10:45:42 | Go: First attempt at channels | [
"go",
"golang"
] | [
"Go"
] | In a http://www.markhneedham.com/blog/2016/12/23/neo4j-graphing-the-thoughtworks-technology-radar/[previous blog post] I mentioned that I wanted to extract blips from The ThoughtWorks Radar into a CSV file and I thought this would be a good mini project for me to practice using Go.
In particular I wanted to try using https://tour.golang.org/concurrency/2[channels] and this seemed like a good chance to do that.
</p>
I watched a talk by Rob Pike on https://talks.golang.org/2012/waza.slide#22[designing concurrent applications] where he uses the following https://talks.golang.org/2012/waza.slide#10[definition of concurrency]:</p>
____
Concurrency is a way to structure a program by breaking it into pieces that can be executed independently.
____
He then demonstrates this with the following diagram:
image::{{<siteurl>}}/uploads/2016/12/2016-12-23_19-52-30.png[2016 12 23 19 52 30,413]
I broke the scraping application down into four parts:
. Find the links of blips to download \->
. Download the blips \->
. Scrape the data from each page \->
. Write the data into a CSV file
I don't think we gain much by parallelising steps 1) or 4) but steps 2) and 3) seem easily parallelisable. Therefore we'll use a single goroutine for steps 1) and 4) and multiple goroutines for steps 2) and 3).
We'll create two channels:
* +++<cite>+++filesToScrape+++</cite>+++
* +++<cite>+++filesScraped+++</cite>+++
And they will interact with our components like this:
* 2) will write the path of the downloaded files into +++<cite>+++filesToScape+++</cite>+++
* 3) will read from +++<cite>+++filesToScrape+++</cite>+++ and write the scraped content into +++<cite>+++filesScraped+++</cite>+++
* 4) will read from +++<cite>+++filesScraped+++</cite>+++ and put that information into a CSV file.
I decided to write a completely serial version of the scraping application first so that I could compare it to the parallel version. I had the following common code:
+++<cite>+++scrape/scrape.go+++</cite>+++
[source,go]
----
package scrape
import (
"github.com/PuerkitoBio/goquery"
"os"
"bufio"
"fmt"
"log"
"strings"
"net/http"
"io"
)
func checkError(err error) {
if err != nil {
fmt.Println(err)
log.Fatal(err)
}
}
type Blip struct {
Link string
Title string
}
func (blip Blip) Download() File {
parts := strings.Split(blip.Link, "/")
fileName := "rawData/items/" + parts[len(parts) - 1]
if _, err := os.Stat(fileName); os.IsNotExist(err) {
resp, err := http.Get("http://www.thoughtworks.com" + blip.Link)
checkError(err)
body := resp.Body
file, err := os.Create(fileName)
checkError(err)
io.Copy(bufio.NewWriter(file), body)
file.Close()
body.Close()
}
return File{Title: blip.Title, Path: fileName }
}
type File struct {
Title string
Path string
}
func (fileToScrape File ) Scrape() ScrapedFile {
file, err := os.Open(fileToScrape.Path)
checkError(err)
doc, err := goquery.NewDocumentFromReader(bufio.NewReader(file))
checkError(err)
file.Close()
var entries []map[string]string
doc.Find("div.blip-timeline-item").Each(func(i int, s *goquery.Selection) {
entry := make(map[string]string, 0)
entry["time"] = s.Find("div.blip-timeline-item__time").First().Text()
entry["outcome"] = strings.Trim(s.Find("div.blip-timeline-item__ring span").First().Text(), " ")
entry["description"] = s.Find("div.blip-timeline-item__lead").First().Text()
entries = append(entries, entry)
})
return ScrapedFile{File:fileToScrape, Entries:entries}
}
type ScrapedFile struct {
File File
Entries []map[string]string
}
func FindBlips(pathToRadar string) []Blip {
blips := make([]Blip, 0)
file, err := os.Open(pathToRadar)
checkError(err)
doc, err := goquery.NewDocumentFromReader(bufio.NewReader(file))
checkError(err)
doc.Find(".blip").Each(func(i int, s *goquery.Selection) {
item := s.Find("a")
title := item.Text()
link, _ := item.Attr("href")
blips = append(blips, Blip{Title: title, Link: link })
})
return blips
}
----
Note that we're using the +++<cite>+++https://github.com/PuerkitoBio/goquery[goquery]+++</cite>+++ library to scrape the HTML files that we download.
A +++<cite>+++Blip+++</cite>+++ is used to represent an item that appears on the radar e.g. https://www.thoughtworks.com/radar/platforms/net-core[.NET Core]. A +++<cite>+++File+++</cite>+++ is a representation of that blip on my local file system and a +++<cite>+++ScrapedFile+++</cite>+++ contains the local representation of a blip and has an array containing every appearance the blip has made in radars over time.
Let's have a look at the single threaded version of the scraper:
+++<cite>+++cmd/single/main.go+++</cite>+++
[source,go]
----
package main
import (
"fmt"
"encoding/csv"
"os"
"github.com/mneedham/neo4j-thoughtworks-radar/scrape"
)
func main() {
var filesCompleted chan scrape.ScrapedFile = make(chan scrape.ScrapedFile)
defer close(filesCompleted)
blips := scrape.FindBlips("rawData/twRadar.html")
var filesToScrape []scrape.File
for _, blip := range blips {
filesToScrape = append(filesToScrape, blip.Download())
}
var filesScraped []scrape.ScrapedFile
for _, file := range filesToScrape {
filesScraped = append(filesScraped, file.Scrape())
}
blipsCsvFile, _ := os.Create("import/blipsSingle.csv")
writer := csv.NewWriter(blipsCsvFile)
defer blipsCsvFile.Close()
writer.Write([]string{"technology", "date", "suggestion" })
for _, scrapedFile := range filesScraped {
fmt.Println(scrapedFile.File.Title)
for _, blip := range scrapedFile.Entries {
writer.Write([]string{scrapedFile.File.Title, blip["time"], blip["outcome"] })
}
}
writer.Flush()
}
----
+++<cite>+++rawData/twRadar.html+++</cite>+++ is a local copy of the https://www.thoughtworks.com/radar/a-z[A-Z page] which contains all the blips. This version is reasonably simple: we create an array containing all the blips, scrape them into another array, and then that array into a CSV file. And if we run it:
[source,bash]
----
$ time go run cmd/single/main.go
real 3m10.354s
user 0m1.140s
sys 0m0.586s
$ head -n10 import/blipsSingle.csv
technology,date,suggestion
.NET Core,Nov 2016,Assess
.NET Core,Nov 2015,Assess
.NET Core,May 2015,Assess
A single CI instance for all teams,Nov 2016,Hold
A single CI instance for all teams,Apr 2016,Hold
Acceptance test of journeys,Mar 2012,Trial
Acceptance test of journeys,Jul 2011,Trial
Acceptance test of journeys,Jan 2011,Trial
Accumulate-only data,Nov 2015,Assess
----
It takes a few minutes and most of the time will be taken in the +++<cite>+++blip.Download()+++</cite>+++ function - work which is easily parallelisable. Let's have a look at the parallel version where goroutines use channels to communicate with each other:
+++<cite>+++cmd/parallel/main.go+++</cite>+++
[source,go]
----
package main
import (
"os"
"encoding/csv"
"github.com/mneedham/neo4j-thoughtworks-radar/scrape"
)
func main() {
var filesToScrape chan scrape.File = make(chan scrape.File)
var filesScraped chan scrape.ScrapedFile = make(chan scrape.ScrapedFile)
defer close(filesToScrape)
defer close(filesScraped)
blips := scrape.FindBlips("rawData/twRadar.html")
for _, blip := range blips {
go func(blip scrape.Blip) { filesToScrape <- blip.Download() }(blip)
}
for i := 0; i < len(blips); i++ {
select {
case file := <-filesToScrape:
go func(file scrape.File) { filesScraped <- file.Scrape() }(file)
}
}
blipsCsvFile, _ := os.Create("import/blips.csv")
writer := csv.NewWriter(blipsCsvFile)
defer blipsCsvFile.Close()
writer.Write([]string{"technology", "date", "suggestion" })
for i := 0; i < len(blips); i++ {
select {
case scrapedFile := <-filesScraped:
for _, blip := range scrapedFile.Entries {
writer.Write([]string{scrapedFile.File.Title, blip["time"], blip["outcome"] })
}
}
}
writer.Flush()
}
----
Let's remove the files we just downloaded and give this version a try.
[source,bash]
----
$ rm rawData/items/*
$ time go run cmd/parallel/main.go
real 0m6.689s
user 0m2.544s
sys 0m0.904s
$ head -n10 import/blips.csv
technology,date,suggestion
Zucchini,Oct 2012,Assess
Reactive Extensions for .Net,May 2013,Assess
Manual infrastructure management,Mar 2012,Hold
Manual infrastructure management,Jul 2011,Hold
JavaScript micro frameworks,Oct 2012,Trial
JavaScript micro frameworks,Mar 2012,Trial
NPM for all the things,Apr 2016,Trial
NPM for all the things,Nov 2015,Trial
PowerShell,Mar 2012,Trial
----
So we're down from 190 seconds to 7 seconds, pretty cool! One interesting thing is that the order of the values in the CSV file will be different since the goroutines won't necessarily come back in the same order that they were launched. We do end up with the same number of values:
[source,bash]
----
$ wc -l import/blips.csv
1361 import/blips.csv
$ wc -l import/blipsSingle.csv
1361 import/blipsSingle.csv
----
And we can check that the contents are identical:
[source,bash]
----
$ cat import/blipsSingle.csv | sort > /tmp/blipsSingle.csv
$ cat import/blips.csv | sort > /tmp/blips.csv
$ diff /tmp/blips.csv /tmp/blipsSingle.csv
----
The code in this post is all on https://github.com/mneedham/neo4j-thoughtworks-radar[github]. I'm sure I've made some mistakes/there are ways that this could be done better so do let me know in the comments or I'm https://twitter.com/markhneedham[@markhneedham] on twitter. | null | null | [
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] | go-first-attempt-at-channels | https://markhneedham.com/blog/2016/12/24/go-first-attempt-at-channels |
false | 2016-12-23 14:30:09 | Go: Templating with the Gin Web Framework | [
"go",
"golang"
] | [
"Go"
] | I spent a bit of time over the last week building a little internal web application using Go and the https://github.com/gin-gonic/gin[Gin Web Framework] and it took me a while to get the hang of the templating language so I thought I'd write up some examples.
Before we get started, I've got my GOPATH set to the following path:
[source,bash]
----
$ echo $GOPATH
/Users/markneedham/projects/gocode
----
And the project containing the examples sits inside the src directory:
[source,bash]
----
$ pwd
/Users/markneedham/projects/gocode/src/github.com/mneedham/golang-gin-templating-demo
----
Let's first install Gin:
[source,bash]
----
$ go get gopkg.in/gin-gonic/gin.v1
----
It gets installed here:
[source,bash]
----
$ ls -lh $GOPATH/src/gopkg.in
total 0
drwxr-xr-x 3 markneedham staff 102B 23 Dec 10:55 gin-gonic
----
Now let's create a main function to launch our web application:
+++<cite>+++demo.go+++</cite>+++
[source,go]
----
package main
import (
"github.com/gin-gonic/gin"
"net/http"
)
func main() {
router := gin.Default()
router.LoadHTMLGlob("templates/*")
// our handlers will go here
router.Run("0.0.0.0:9090")
}
----
We're launching our application on port 9090 and the templates live in the +++<cite>+++templates+++</cite>+++ directory which is located relative to the file containing the main function:
[source,bash]
----
$ ls -lh
total 8
-rw-r--r-- 1 markneedham staff 570B 23 Dec 13:34 demo.go
drwxr-xr-x 4 markneedham staff 136B 23 Dec 13:34 templates
----
== Arrays
Let's create a route which will display the values of an array in an unordered list:
[source,go]
----
router.GET("/array", func(c *gin.Context) {
var values []int
for i := 0; i < 5; i++ {
values = append(values, i)
}
c.HTML(http.StatusOK, "array.tmpl", gin.H{"values": values})
})
----
[source,html]
----
<ul>
{{ range .values }}
<li>{{ . }}</li>
{{ end }}
</ul>
----
And now we'll cURL our application to see what we get back:
[source,bash]
----
$ curl http://localhost:9090/array
<ul>
<li>0</li>
<li>1</li>
<li>2</li>
<li>3</li>
<li>4</li>
</ul>
----
What about if we have an array of structs instead of just strings?
[source,go]
----
import "strconv"
type Foo struct {
value1 int
value2 string
}
router.GET("/arrayStruct", func(c *gin.Context) {
var values []Foo
for i := 0; i < 5; i++ {
values = append(values, Foo{Value1: i, Value2: "value " + strconv.Itoa(i)})
}
c.HTML(http.StatusOK, "arrayStruct.tmpl", gin.H{"values": values})
})
----
[source,html]
----
<ul>
{{ range .values }}
<li>{{ .Value1 }} -> {{ .Value2 }}</li>
{{ end }}
</ul>
----
cURL time:
[source,bash]
----
$ curl http://localhost:9090/arrayStruct
<ul>
<li>0 -> value 0</li>
<li>1 -> value 1</li>
<li>2 -> value 2</li>
<li>3 -> value 3</li>
<li>4 -> value 4</li>
</ul>
----
== Maps
Now let's do the same for maps.
[source,go]
----
router.GET("/map", func(c *gin.Context) {
values := make(map[string]string)
values["language"] = "Go"
values["version"] = "1.7.4"
c.HTML(http.StatusOK, "map.tmpl", gin.H{"myMap": values})
})
----
[source,html]
----
<ul>
{{ range .myMap }}
<li>{{ . }}</li>
{{ end }}
</ul>
----
And cURL it:
[source,bash]
----
$ curl http://localhost:9090/map
<ul>
<li>Go</li>
<li>1.7.4</li>
</ul>
----
What if we want to see the keys as well?
[source,go]
----
router.GET("/mapKeys", func(c *gin.Context) {
values := make(map[string]string)
values["language"] = "Go"
values["version"] = "1.7.4"
c.HTML(http.StatusOK, "mapKeys.tmpl", gin.H{"myMap": values})
})
----
[source,html]
----
<ul>
{{ range $key, $value := .myMap }}
<li>{{ $key }} -> {{ $value }}</li>
{{ end }}
</ul>
----
[source,bash]
----
$ curl http://localhost:9090/mapKeys
<ul>
<li>language -> Go</li>
<li>version -> 1.7.4</li>
</ul>
----
And finally, what if we want to select specific values from the map?
[source,go]
----
router.GET("/mapSelectKeys", func(c *gin.Context) {
values := make(map[string]string)
values["language"] = "Go"
values["version"] = "1.7.4"
c.HTML(http.StatusOK, "mapSelectKeys.tmpl", gin.H{"myMap": values})
})
----
[source,html]
----
<ul>
<li>Language: {{ .myMap.language }}</li>
<li>Version: {{ .myMap.version }}</li>
</ul>
----
[source,bash]
----
$ curl http://localhost:9090/mapSelectKeys
<ul>
<li>Language: Go</li>
<li>Version: 1.7.4</li>
</ul>
----
I've found the https://gohugo.io/templates/go-templates/[Hugo Go Template Primer] helpful for figuring this out so that's a good reference if you get stuck. You can find a https://github.com/mneedham/golang-gin-templating-demo/blob/master/demo.go[go file containing all the examples on github] if you want to use that as a starting point. | null | null | [
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] | go-templating-with-the-gin-web-framework | https://markhneedham.com/blog/2016/12/23/go-templating-with-the-gin-web-framework |
false | 2016-12-23 18:24:12 | Go: cannot execute binary file: Exec format error | [
"go",
"golang"
] | [
"Go"
] | In an earlier blog post I mentioned that I'd been http://www.markhneedham.com/blog/2016/12/23/go-templating-with-the-gin-web-framework/[building an internal application] to learn a bit of Go and I wanted to deploy it to AWS.
Since the application was only going to live for a couple of days I didn't want to spend a long time build up anything fancy so my plan was just to build the executable, SSH it to my AWS instance, and then run it.
My initial (somewhat naive) approach was to just build the project on my Mac and upload and run it:
[source,bash]
----
$ go build
$ scp myapp ubuntu@aws...
$ ssh ubuntu@aws...
$ ./myapp
-bash: ./myapp: cannot execute binary file: Exec format error
----
That didn't go so well! By reading http://askubuntu.com/questions/648555/bash-program-cannot-execute-binary-file-exec-format-error[Ask Ubuntu] and https://dave.cheney.net/2015/03/03/cross-compilation-just-got-a-whole-lot-better-in-go-1-5[Dave Cheney's blog post on cross compilation] I realised that I just needed to set the appropriate environment variables before running +++<cite>+++go build+++</cite>+++.
The following did the trick:
[source,bash]
----
env GOOS=linux GOARCH=amd64 GOARM=7 go build
----
And that's it! I'm sure there's more sophisticated ways of doing this that I'll come to learn about but for now this worked for me. | null | null | [
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] | go-cannot-execute-binary-file-exec-format-error | https://markhneedham.com/blog/2016/12/23/go-cannot-execute-binary-file-exec-format-error |
false | 2016-12-23 17:40:45 | Neo4j: Graphing the ThoughtWorks Technology Radar | [
"neo4j"
] | [
"neo4j"
] | For a bit of Christmas holiday fun I thought it'd be cool to create a graph of the different blips on the https://www.thoughtworks.com/radar/a-z[ThoughtWorks Technology Radar] and how the recommendations have changed over time.
I wrote a script to extract each blip (e.g. https://www.thoughtworks.com/radar/platforms/net-core[.NET Core]) and the recommendation made in each radar that it appeared in. I ended up with https://github.com/mneedham/neo4j-thoughtworks-radar/blob/master/import/blips.csv[a CSV file]:
[source,text]
----
|----------------------------------------------+----------+-------------|
| technology | date | suggestion |
|----------------------------------------------+----------+-------------|
| AppHarbor | Mar 2012 | Trial |
| Accumulate-only data | Nov 2015 | Assess |
| Accumulate-only data | May 2015 | Assess |
| Accumulate-only data | Jan 2015 | Assess |
| Buying solutions you can only afford one of | Mar 2012 | Hold |
|----------------------------------------------+----------+-------------|
----
I then wrote a Cypher script to create the following graph model:
image::{{<siteurl>}}/uploads/2016/12/2016-12-23_16-52-08.png[2016 12 23 16 52 08,598]
[source,cypher]
----
WITH ["Hold", "Assess", "Trial", "Adopt"] AS positions
UNWIND RANGE (0, size(positions) - 2) AS index
WITH positions[index] AS pos1, positions[index + 1] AS pos2
MERGE (position1:Position {value: pos1})
MERGE (position2:Position {value: pos2})
MERGE (position1)-[:NEXT]->(position2);
load csv with headers from "file:///blips.csv" AS row
MATCH (position:Position {value: row.suggestion })
MERGE (tech:Technology {name: row.technology })
MERGE (date:Date {value: row.date})
MERGE (recommendation:Recommendation {
id: tech.name + "_" + date.value + "_" + position.value})
MERGE (recommendation)-[:ON_DATE]->(date)
MERGE (recommendation)-[:POSITION]->(position)
MERGE (recommendation)-[:TECHNOLOGY]->(tech);
match (date:Date)
SET date.timestamp = apoc.date.parse(date.value, "ms", "MMM yyyy");
MATCH (date:Date)
WITH date
ORDER BY date.timestamp
WITH COLLECT(date) AS dates
UNWIND range(0, size(dates)-2) AS index
WITH dates[index] as month1, dates[index+1] AS month2
MERGE (month1)-[:NEXT]->(month2);
MATCH (tech)<-[:TECHNOLOGY]-(reco:Recommendation)-[:ON_DATE]->(date)
WITH tech, reco, date
ORDER BY tech.name, date.timestamp
WITH tech, COLLECT(reco) AS recos
UNWIND range(0, size(recos)-2) AS index
WITH recos[index] AS reco1, recos[index+1] AS reco2
MERGE (reco1)-[:NEXT]->(reco2);
----
Note that I installed the https://github.com/neo4j-contrib/neo4j-apoc-procedures[APOC procedures library] so that I could convert the string representation of a date into a timestamp using the +++<cite>+++apoc.date.parse+++</cite>+++ function. The +++<cite>+++blips.csv+++</cite>+++ file needs to go in the import directory of Neo4j.
Now we're reading to write some queries.
The Technology Radar has 4 positions that can be taken for a given technology: Hold, Assess, Trial, and Adopt:
* Hold: Process with Caution
* Assess: Worth exploring with the goal of understanding how it will affect your enterprise.
* Trial: Worth pursuing. It is important to understand how to build up this capability. Enterprises should try this technology on a project that can handle the risk.
* Adopt: We feel strongly that the industry should be adopting these items. We use them when appropriate on our projects.
I was curious whether there had ever been a technology where the advice was initially to 'Hold' but had later changed to 'Assess'. I wrote the following query to find out:
[source,cypher]
----
MATCH (pos1:Position {value:"Hold"})<-[:POSITION]-(reco)-[:TECHNOLOGY]->(tech),
(pos2:Position {value:"Assess"})<-[:POSITION]-(otherReco)-[:TECHNOLOGY]->(tech),
(reco)-[:ON_DATE]->(recoDate),
(otherReco)-[:ON_DATE]->(otherRecoDate)
WHERE (reco)-[:NEXT]->(otherReco)
RETURN tech.name AS technology, otherRecoDate.value AS dateOfChange;
ββββββββββββββ€βββββββββββββββ
β"technology"β"dateOfChange"β
ββββββββββββββͺβββββββββββββββ‘
β"Azure" β"Aug 2010" β
ββββββββββββββ΄βββββββββββββββ
----
Only https://www.thoughtworks.com/radar/platforms/azure[Azure]! The page doesn't have any explanation for the initial 'Hold' advice in April 2010 which was presumably just before 'the cloud' became prominent. What about the other way around? Are there any technologies where the suggestion was initially to 'Assess' but later to 'Hold'?
[source,cypher]
----
MATCH (pos1:Position {value:"Assess"})<-[:POSITION]-(reco)-[:TECHNOLOGY]->(tech),
(pos2:Position {value:"Hold"})<-[:POSITION]-(otherReco)-[:TECHNOLOGY]->(tech),
(reco)-[:ON_DATE]->(recoDate),
(otherReco)-[:ON_DATE]->(otherRecoDate)
WHERE (reco)-[:NEXT]->(otherReco)
RETURN tech.name AS technology, otherRecoDate.value AS dateOfChange;
βββββββββββββββββββββββββββββββββββββ€βββββββββββββββ
β"technology" β"dateOfChange"β
βββββββββββββββββββββββββββββββββββββͺβββββββββββββββ‘
β"RIA" β"Apr 2010" β
βββββββββββββββββββββββββββββββββββββΌβββββββββββββββ€
β"Backbone.js" β"Oct 2012" β
βββββββββββββββββββββββββββββββββββββΌβββββββββββββββ€
β"Pace-layered Application Strategy"β"Nov 2015" β
βββββββββββββββββββββββββββββββββββββΌβββββββββββββββ€
β"SPDY" β"May 2015" β
βββββββββββββββββββββββββββββββββββββΌβββββββββββββββ€
β"AngularJS" β"Nov 2016" β
βββββββββββββββββββββββββββββββββββββ΄βββββββββββββββ
----
A couple of these are Javascript libraries/frameworks so presumably the advice is now to use https://facebook.github.io/react/[React] instead. Let's check:
[source,cypher]
----
MATCH (t:Technology)<-[:TECHNOLOGY]-(reco)-[:ON_DATE]->(date), (reco)-[:POSITION]->(pos)
WHERE t.name contains "React.js"
RETURN pos.value, date.value
ORDER BY date.timestamp
βββββββββββββ€βββββββββββββ
β"pos.value"β"date.value"β
βββββββββββββͺβββββββββββββ‘
β"Assess" β"Jan 2015" β
βββββββββββββΌβββββββββββββ€
β"Trial" β"May 2015" β
βββββββββββββΌβββββββββββββ€
β"Trial" β"Nov 2015" β
βββββββββββββΌβββββββββββββ€
β"Adopt" β"Apr 2016" β
βββββββββββββΌβββββββββββββ€
β"Adopt" β"Nov 2016" β
βββββββββββββ΄βββββββββββββ
----
Ember is also popular:
[source,cypher]
----
MATCH (t:Technology)<-[:TECHNOLOGY]-(reco)-[:ON_DATE]->(date), (reco)-[:POSITION]->(pos)
WHERE t.name contains "Ember"
RETURN pos.value, date.value
ORDER BY date.timestamp
βββββββββββββ€βββββββββββββ
β"pos.value"β"date.value"β
βββββββββββββͺβββββββββββββ‘
β"Assess" β"May 2015" β
βββββββββββββΌβββββββββββββ€
β"Assess" β"Nov 2015" β
βββββββββββββΌβββββββββββββ€
β"Trial" β"Apr 2016" β
βββββββββββββΌβββββββββββββ€
β"Adopt" β"Nov 2016" β
βββββββββββββ΄βββββββββββββ
----
Let's go on a different tangent and look at how many technologies were introduced in the most recent radar?
[source,cypher]
----
MATCH (date:Date {value: "Nov 2016"})<-[:ON_DATE]-(reco)
WHERE NOT (reco)<-[:NEXT]-()
RETURN COUNT(*)
ββββββββββββ
β"COUNT(*)"β
ββββββββββββ‘
β"45" β
ββββββββββββ
----
Wow, 45 new things! How were they spread across the different positions?
[source,cypher]
----
MATCH (date:Date {value: "Nov 2016"})<-[:ON_DATE]-(reco)-[:TECHNOLOGY]->(tech),
(reco)-[:POSITION]->(position)
WHERE NOT (reco)<-[:NEXT]-()
WITH position, COUNT(*) AS count, COLLECT(tech.name) AS technologies
ORDER BY LENGTH((position)-[:NEXT*]->()) DESC
RETURN position.value, count, technologies
ββββββββββββββββββ€ββββββββ€βββββββββββββββββββββββββββββββββββββββββββββββ
β"position.value"β"count"β"technologies" β
ββββββββββββββββββͺββββββββͺβββββββββββββββββββββββββββββββββββββββββββββββ‘
β"Hold" β"1" β["Anemic REST"] β
ββββββββββββββββββΌββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββ€
β"Assess" β"28" β["Nuance Mix","Micro frontends","Three.js","Scβ
β β βikit-learn","WebRTC","ReSwift","Vue.js","Electβ
β β βron","Container security scanning","wit.ai","Dβ
β β βifferential privacy","Rapidoid","OpenVR","AWS β
β β βApplication Load Balancer","Tarantool","IndiaSβ
β β βtack","Ethereum","axios","Bottled Water","Cassβ
β β βandra carefully","ECMAScript 2017","FBSnapshotβ
β β βTestcase","Client-directed query","JuMP","Clojβ
β β βure.spec","HoloLens","Android-x86","Physical Wβ
β β βeb"] β
ββββββββββββββββββΌββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββ€
β"Trial" β"13" β["tmate","Lightweight Architecture Decision Reβ
β β βcords","APIs as a product","JSONassert","Unityβ
β β β beyond gaming","Galen","Enzyme","Quick and Niβ
β β βmble","Talisman","fastlane","Auth0","Pa11y","Pβ
β β βhoenix"] β
ββββββββββββββββββΌββββββββΌβββββββββββββββββββββββββββββββββββββββββββββββ€
β"Adopt" β"3" β["Grafana","Babel","Pipelines as code"] β
ββββββββββββββββββ΄ββββββββ΄βββββββββββββββββββββββββββββββββββββββββββββββ
----
Lots of new things to explore over the holidays! The CSV files, import script, and queries used in this post are all https://github.com/mneedham/neo4j-thoughtworks-radar[available on github] if you want to play around with them. | null | null | [
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] | neo4j-graphing-the-thoughtworks-technology-radar | https://markhneedham.com/blog/2016/12/23/neo4j-graphing-the-thoughtworks-technology-radar |
Subsets and Splits