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After this merged, the work for other transformers/estimators will be easy, then we can list and distribute the tasks to the community.\n\ncc mengxr jkbradley\n\nAuthor: Yanbo Liang <[email protected]>\nAuthor: Joseph K. Bradley <[email protected]>\n\nCloses #10469 from yanboliang/spark-11939.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/e51b6eaa9e9c007e194d858195291b2b9fb27322"},{"sha":"e4c1162b6b3dbc8fc95cfe75c6e0bc2915575fb2","author":{"email":"[email protected]","name":"zhuol"},"message":"[SPARK-10873] Support column sort and search for History Server.\n\n[SPARK-10873] Support column sort and search for History Server using jQuery DataTable and REST API. Before this commit, the history server was generated hard-coded html and can not support search, also, the sorting was disabled if there is any application that has more than one attempt. 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External javascirpt and css files for datatables, RowsGroup and jquery plugins are added with licenses clarified.\n\nSnapshots for how it looks like now:\n\nHistory page view:\n![historypage](https://cloud.githubusercontent.com/assets/11683054/12184383/89bad774-b55a-11e5-84e4-b0276172976f.png)\n\nSearch:\n![search](https://cloud.githubusercontent.com/assets/11683054/12184385/8d3b94b0-b55a-11e5-869a-cc0ef0a4242a.png)\n\nSort by started time:\n![sort-by-started-time](https://cloud.githubusercontent.com/assets/11683054/12184387/8f757c3c-b55a-11e5-98c8-577936366566.png)\n\nAuthor: zhuol <[email protected]>\n\nCloses #10648 from zhuoliu/10873.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/e4c1162b6b3dbc8fc95cfe75c6e0bc2915575fb2"},{"sha":"c5f745ede01831b59c57effa7de88c648b82c13d","author":{"email":"[email protected]","name":"Wenchen Fan"},"message":"[SPARK-13072] [SQL] simplify and improve murmur3 hash expression codegen\n\nsimplify(remove several unnecessary local variables) the generated code of hash expression, and avoid null check if possible.\n\ngenerated code comparison for `hash(int, double, string, array<string>)`:\n**before:**\n```\n public UnsafeRow apply(InternalRow i) {\n /* hash(input[0, int],input[1, double],input[2, string],input[3, array<int>],42) */\n int value1 = 42;\n /* input[0, int] */\n int value3 = i.getInt(0);\n if (!false) {\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashInt(value3, value1);\n }\n /* input[1, double] */\n double value5 = i.getDouble(1);\n if (!false) {\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashLong(Double.doubleToLongBits(value5), value1);\n }\n /* input[2, string] */\n boolean isNull6 = i.isNullAt(2);\n UTF8String value7 = isNull6 ? null : (i.getUTF8String(2));\n if (!isNull6) {\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashUnsafeBytes(value7.getBaseObject(), value7.getBaseOffset(), value7.numBytes(), value1);\n }\n /* input[3, array<int>] */\n boolean isNull8 = i.isNullAt(3);\n ArrayData value9 = isNull8 ? null : (i.getArray(3));\n if (!isNull8) {\n int result10 = value1;\n for (int index11 = 0; index11 < value9.numElements(); index11++) {\n if (!value9.isNullAt(index11)) {\n final int element12 = value9.getInt(index11);\n result10 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashInt(element12, result10);\n }\n }\n value1 = result10;\n }\n }\n```\n**after:**\n```\n public UnsafeRow apply(InternalRow i) {\n /* hash(input[0, int],input[1, double],input[2, string],input[3, array<int>],42) */\n int value1 = 42;\n /* input[0, int] */\n int value3 = i.getInt(0);\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashInt(value3, value1);\n /* input[1, double] */\n double value5 = i.getDouble(1);\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashLong(Double.doubleToLongBits(value5), value1);\n /* input[2, string] */\n boolean isNull6 = i.isNullAt(2);\n UTF8String value7 = isNull6 ? null : (i.getUTF8String(2));\n\n if (!isNull6) {\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashUnsafeBytes(value7.getBaseObject(), value7.getBaseOffset(), value7.numBytes(), value1);\n }\n\n /* input[3, array<int>] */\n boolean isNull8 = i.isNullAt(3);\n ArrayData value9 = isNull8 ? null : (i.getArray(3));\n if (!isNull8) {\n for (int index10 = 0; index10 < value9.numElements(); index10++) {\n final int element11 = value9.getInt(index10);\n value1 = org.apache.spark.unsafe.hash.Murmur3_x86_32.hashInt(element11, value1);\n }\n }\n\n rowWriter14.write(0, value1);\n return result12;\n }\n```\n\nAuthor: Wenchen Fan <[email protected]>\n\nCloses #10974 from cloud-fan/codegen.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/c5f745ede01831b59c57effa7de88c648b82c13d"},{"sha":"5f686cc8b74ea9e36f56c31f14df90d134fd9343","author":{"email":"[email protected]","name":"gatorsmile"},"message":"[SPARK-12656] [SQL] Implement Intersect with Left-semi Join\n\nOur current Intersect physical operator simply delegates to RDD.intersect. 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Left-semi Join could help outer-join elimination in Optimizer, as shown in the PR: https://github.com/apache/spark/pull/10566\n\nAuthor: gatorsmile <[email protected]>\nAuthor: xiaoli <[email protected]>\nAuthor: Xiao Li <[email protected]>\n\nCloses #10630 from gatorsmile/IntersectBySemiJoin.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/5f686cc8b74ea9e36f56c31f14df90d134fd9343"},{"sha":"2b027e9a386fe4009f61ad03b169335af5a9a5c6","author":{"email":"[email protected]","name":"Cheng Lian"},"message":"[SPARK-12818] Polishes spark-sketch module\n\nFixes various minor code and Javadoc styling issues.\n\nAuthor: Cheng Lian <[email protected]>\n\nCloses #10985 from liancheng/sketch-polishing.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/2b027e9a386fe4009f61ad03b169335af5a9a5c6"},{"sha":"e38b0baa38c6894335f187eaa4c8ea5c02d4563b","author":{"email":"[email protected]","name":"Andrew Or"},"message":"[SPARK-13055] SQLHistoryListener throws ClassCastException\n\nThis is an existing issue uncovered recently by #10835. 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To fix this, just block until all events are actually processed, i.e. until the listener queue is empty.\n\nhttps://amplab.cs.berkeley.edu/jenkins/job/spark-master-test-sbt-hadoop-2.7/79/testReport/junit/org.apache.spark.util.collection/ExternalAppendOnlyMapSuite/spilling/\n\nAuthor: Andrew Or <[email protected]>\n\nCloses #10990 from andrewor14/accum-suite-less-flaky.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/e6ceac49a311faf3413acda57a6612fe806adf90"},{"sha":"70e69fc4dd619654f5d24b8b84f6a94f7705c59b","author":{"email":"[email protected]","name":"Andrew Or"},"message":"[SPARK-13088] Fix DAG viz in latest version of chrome\n\nApparently chrome removed `SVGElement.prototype.getTransformToElement`, which is used by our JS library dagre-d3 when creating edges. The real diff can be found here: https://github.com/andrewor14/dagre-d3/commit/7d6c0002e4c74b82a02c5917876576f71e215590, which is taken from the fix in the main repo: https://github.com/cpettitt/dagre-d3/commit/1ef067f1c6ad2e0980f6f0ca471bce998784b7b2\n\nUpstream issue: https://github.com/cpettitt/dagre-d3/issues/202\n\nAuthor: Andrew Or <[email protected]>\n\nCloses #10986 from andrewor14/fix-dag-viz.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/70e69fc4dd619654f5d24b8b84f6a94f7705c59b"},{"sha":"12252d1da90fa7d2dffa3a7c249ecc8821dee130","author":{"email":"[email protected]","name":"Andrew Or"},"message":"[SPARK-13071] Coalescing HadoopRDD overwrites existing input metrics\n\nThis issue is causing tests to fail consistently in master with Hadoop 2.6 / 2.7. This is because for Hadoop 2.5+ we overwrite existing values of `InputMetrics#bytesRead` in each call to `HadoopRDD#compute`. In the case of coalesce, e.g.\n```\nsc.textFile(..., 4).coalesce(2).count()\n```\nwe will call `compute` multiple times in the same task, overwriting `bytesRead` values from previous calls to `compute`.\n\nFor a regression test, see `InputOutputMetricsSuite.input metrics for old hadoop with coalesce`. I did not add a new regression test because it's impossible without significant refactoring; there's a lot of existing duplicate code in this corner of Spark.\n\nThis was caused by #10835.\n\nAuthor: Andrew Or <[email protected]>\n\nCloses #10973 from andrewor14/fix-input-metrics-coalesce.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/12252d1da90fa7d2dffa3a7c249ecc8821dee130"},{"sha":"e6a02c66d53f59ba2d5c1548494ae80a385f9f5c","author":{"email":"[email protected]","name":"Davies Liu"},"message":"[SPARK-12914] [SQL] generate aggregation with grouping keys\n\nThis PR add support for grouping keys for generated TungstenAggregate.\n\nSpilling and performance improvements for BytesToBytesMap will be done by followup PR.\n\nAuthor: Davies Liu <[email protected]>\n\nCloses #10855 from davies/gen_keys.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/e6a02c66d53f59ba2d5c1548494ae80a385f9f5c"},{"sha":"dab246f7e4664d36073ec49d9df8a11c5e998cdb","author":{"email":"[email protected]","name":"Wenchen Fan"},"message":"[SPARK-13098] [SQL] remove GenericInternalRowWithSchema\n\nThis class is only used for serialization of Python DataFrame. However, we don't require internal row there, so `GenericRowWithSchema` can also do the job.\n\nAuthor: Wenchen Fan <[email protected]>\n\nCloses #10992 from cloud-fan/python.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/dab246f7e4664d36073ec49d9df8a11c5e998cdb"},{"sha":"289373b28cd2546165187de2e6a9185a1257b1e7","author":{"email":"[email protected]","name":"Josh Rosen"},"message":"[SPARK-6363][BUILD] Make Scala 2.11 the default Scala version\n\nThis patch changes Spark's build to make Scala 2.11 the default Scala version. To be clear, this does not mean that Spark will stop supporting Scala 2.10: users will still be able to compile Spark for Scala 2.10 by following the instructions on the \"Building Spark\" page; however, it does mean that Scala 2.11 will be the default Scala version used by our CI builds (including pull request builds).\n\nThe Scala 2.11 compiler is faster than 2.10, so I think we'll be able to look forward to a slight speedup in our CI builds (it looks like it's about 2X faster for the Maven compile-only builds, for instance).\n\nAfter this patch is merged, I'll update Jenkins to add new compile-only jobs to ensure that Scala 2.10 compilation doesn't break.\n\nAuthor: Josh Rosen <[email protected]>\n\nCloses #10608 from JoshRosen/SPARK-6363.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/289373b28cd2546165187de2e6a9185a1257b1e7"},{"sha":"de283719980ae78b740e507e4d70c7ebbf6c5f74","author":{"email":"[email protected]","name":"wangyang"},"message":"[SPARK-13100][SQL] improving the performance of stringToDate method in DateTimeUtils.scala\n\n In jdk1.7 TimeZone.getTimeZone() is synchronized, so use an instance variable to hold an GMT TimeZone object instead of instantiate it every time.\n\nAuthor: wangyang <[email protected]>\n\nCloses #10994 from wangyang1992/datetimeUtil.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/de283719980ae78b740e507e4d70c7ebbf6c5f74"},{"sha":"a1303de0a0e9d0c80327977abf52a79e2aa95e1f","author":{"email":"[email protected]","name":"Cheng Lian"},"message":"[SPARK-13070][SQL] Better error message when Parquet schema merging fails\n\nMake sure we throw better error messages when Parquet schema merging fails.\n\nAuthor: Cheng Lian <[email protected]>\nAuthor: Liang-Chi Hsieh <[email protected]>\n\nCloses #10979 from viirya/schema-merging-failure-message.","distinct":false,"url":"https://api.github.com/repos/cloud-fan/spark/commits/a1303de0a0e9d0c80327977abf52a79e2aa95e1f"}]}
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