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* [SPARK-16289][SQL] Implement posexplode table generating functionDongjoon Hyun2016-06-301-0/+21
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR implements `posexplode` table generating function. Currently, master branch raises the following exception for `map` argument. It's different from Hive. **Before** ```scala scala> sql("select posexplode(map('a', 1, 'b', 2))").show org.apache.spark.sql.AnalysisException: No handler for Hive UDF ... posexplode() takes an array as a parameter; line 1 pos 7 ``` **After** ```scala scala> sql("select posexplode(map('a', 1, 'b', 2))").show +---+---+-----+ |pos|key|value| +---+---+-----+ | 0| a| 1| | 1| b| 2| +---+---+-----+ ``` For `array` argument, `after` is the same with `before`. ``` scala> sql("select posexplode(array(1, 2, 3))").show +---+---+ |pos|col| +---+---+ | 0| 1| | 1| 2| | 2| 3| +---+---+ ``` ## How was this patch tested? Pass the Jenkins tests with newly added testcases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13971 from dongjoon-hyun/SPARK-16289.
* [SPARK-15820][PYSPARK][SQL] Add Catalog.refreshTable into python APIWeichenXu2016-06-301-0/+5
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add Catalog.refreshTable API into python interface for Spark-SQL. ## How was this patch tested? Existing test. Author: WeichenXu <WeichenXu123@outlook.com> Closes #13558 from WeichenXu123/update_python_sql_interface_refreshTable.
* [TRIVIAL] [PYSPARK] Clean up orc compression option as wellhyukjinkwon2016-06-291-2/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR corrects ORC compression option for PySpark as well. I think this was missed mistakenly in https://github.com/apache/spark/pull/13948. ## How was this patch tested? N/A Author: hyukjinkwon <gurwls223@gmail.com> Closes #13963 from HyukjinKwon/minor-orc-compress.
* [SPARK-16236][SQL][FOLLOWUP] Add Path Option back to Load API in DataFrameReadergatorsmile2016-06-291-1/+3
| | | | | | | | | | | | | | #### What changes were proposed in this pull request? In Python API, we have the same issue. Thanks for identifying this issue, zsxwing ! Below is an example: ```Python spark.read.format('json').load('python/test_support/sql/people.json') ``` #### How was this patch tested? Existing test cases cover the changes by this PR Author: gatorsmile <gatorsmile@gmail.com> Closes #13965 from gatorsmile/optionPaths.
* [SPARK-16266][SQL][STREAING] Moved DataStreamReader/Writer from pyspark.sql ↵Tathagata Das2016-06-286-499/+511
| | | | | | | | | | | | | | | | | | to pyspark.sql.streaming ## What changes were proposed in this pull request? - Moved DataStreamReader/Writer from pyspark.sql to pyspark.sql.streaming to make them consistent with scala packaging - Exposed the necessary classes in sql.streaming package so that they appear in the docs - Added pyspark.sql.streaming module to the docs ## How was this patch tested? - updated unit tests. - generated docs for testing visibility of pyspark.sql.streaming classes. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #13955 from tdas/SPARK-16266.
* [SPARK-16268][PYSPARK] SQLContext should import DataStreamReaderShixiong Zhu2016-06-281-2/+9
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fixed the following error: ``` >>> sqlContext.readStream Traceback (most recent call last): File "<stdin>", line 1, in <module> File "...", line 442, in readStream return DataStreamReader(self._wrapped) NameError: global name 'DataStreamReader' is not defined ``` ## How was this patch tested? The added test. Author: Shixiong Zhu <shixiong@databricks.com> Closes #13958 from zsxwing/fix-import.
* [MINOR][DOCS][STRUCTURED STREAMING] Minor doc fixes around `DataFrameWriter` ↵Burak Yavuz2016-06-281-2/+2
| | | | | | | | | | | | and `DataStreamWriter` ## What changes were proposed in this pull request? Fixes a couple old references to `DataFrameWriter.startStream` to `DataStreamWriter.start Author: Burak Yavuz <brkyvz@gmail.com> Closes #13952 from brkyvz/minor-doc-fix.
* [SPARK-16175] [PYSPARK] handle None for UDTDavies Liu2016-06-282-2/+16
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Scala UDT will bypass all the null and will not pass them into serialize() and deserialize() of UDT, this PR update the Python UDT to do this as well. ## How was this patch tested? Added tests. Author: Davies Liu <davies@databricks.com> Closes #13878 from davies/udt_null.
* [SPARK-16259][PYSPARK] cleanup options in DataFrame read/write APIDavies Liu2016-06-281-99/+20
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? There are some duplicated code for options in DataFrame reader/writer API, this PR clean them up, it also fix a bug for `escapeQuotes` of csv(). ## How was this patch tested? Existing tests. Author: Davies Liu <davies@databricks.com> Closes #13948 from davies/csv_options.
* [SPARK-16224] [SQL] [PYSPARK] SparkSession builder's configs need to be set ↵Yin Huai2016-06-284-1/+59
| | | | | | | | | | | | | | to the existing Scala SparkContext's SparkConf ## What changes were proposed in this pull request? When we create a SparkSession at the Python side, it is possible that a SparkContext has been created. For this case, we need to set configs of the SparkSession builder to the Scala SparkContext's SparkConf (we need to do so because conf changes on a active Python SparkContext will not be propagated to the JVM side). Otherwise, we may create a wrong SparkSession (e.g. Hive support is not enabled even if enableHiveSupport is called). ## How was this patch tested? New tests and manual tests. Author: Yin Huai <yhuai@databricks.com> Closes #13931 from yhuai/SPARK-16224.
* [SPARK-16242][MLLIB][PYSPARK] Conversion between old/new matrix columns in a ↵Yanbo Liang2016-06-281-0/+80
| | | | | | | | | | | | | | DataFrame (Python) ## What changes were proposed in this pull request? This PR implements python wrappers for #13888 to convert old/new matrix columns in a DataFrame. ## How was this patch tested? Doctest in python. Author: Yanbo Liang <ybliang8@gmail.com> Closes #13935 from yanboliang/spark-16242.
* [SPARK-16128][SQL] Allow setting length of characters to be truncated to, in ↵Prashant Sharma2016-06-281-3/+15
| | | | | | | | | | | | | | | | | | Dataset.show function. ## What changes were proposed in this pull request? Allowing truncate to a specific number of character is convenient at times, especially while operating from the REPL. Sometimes those last few characters make all the difference, and showing everything brings in whole lot of noise. ## How was this patch tested? Existing tests. + 1 new test in DataFrameSuite. For SparkR and pyspark, existing tests and manual testing. Author: Prashant Sharma <prashsh1@in.ibm.com> Author: Prashant Sharma <prashant@apache.org> Closes #13839 from ScrapCodes/add_truncateTo_DF.show.
* [SPARK-16220][SQL] Revert Change to Bring Back SHOW FUNCTIONS FunctionalityBill Chambers2016-06-271-1/+11
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? - Fix tests regarding show functions functionality - Revert `catalog.ListFunctions` and `SHOW FUNCTIONS` to return to `Spark 1.X` functionality. Cherry picked changes from this PR: https://github.com/apache/spark/pull/13413/files ## How was this patch tested? Unit tests. Author: Bill Chambers <bill@databricks.com> Author: Bill Chambers <wchambers@ischool.berkeley.edu> Closes #13916 from anabranch/master.
* [SPARK-16179][PYSPARK] fix bugs for Python udf in generateDavies Liu2016-06-241-0/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fix the bug when Python UDF is used in explode (generator), GenerateExec requires that all the attributes in expressions should be resolvable from children when creating, we should replace the children first, then replace it's expressions. ``` >>> df.select(explode(f(*df))).show() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/vlad/dev/spark/python/pyspark/sql/dataframe.py", line 286, in show print(self._jdf.showString(n, truncate)) File "/home/vlad/dev/spark/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__ File "/home/vlad/dev/spark/python/pyspark/sql/utils.py", line 63, in deco return f(*a, **kw) File "/home/vlad/dev/spark/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py", line 312, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling o52.showString. : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: makeCopy, tree: Generate explode(<lambda>(_1#0L)), false, false, [col#15L] +- Scan ExistingRDD[_1#0L] at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:50) at org.apache.spark.sql.catalyst.trees.TreeNode.makeCopy(TreeNode.scala:387) at org.apache.spark.sql.execution.SparkPlan.makeCopy(SparkPlan.scala:69) at org.apache.spark.sql.execution.SparkPlan.makeCopy(SparkPlan.scala:45) at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:177) at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressions(QueryPlan.scala:144) at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.org$apache$spark$sql$execution$python$ExtractPythonUDFs$$extract(ExtractPythonUDFs.scala:153) at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:114) at org.apache.spark.sql.execution.python.ExtractPythonUDFs$$anonfun$apply$2.applyOrElse(ExtractPythonUDFs.scala:113) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:301) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformUp$1.apply(TreeNode.scala:301) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69) at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:300) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:298) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:298) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:321) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:319) at org.apache.spark.sql.catalyst.trees.TreeNode.transformUp(TreeNode.scala:298) at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:113) at org.apache.spark.sql.execution.python.ExtractPythonUDFs$.apply(ExtractPythonUDFs.scala:93) at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:95) at org.apache.spark.sql.execution.QueryExecution$$anonfun$prepareForExecution$1.apply(QueryExecution.scala:95) at scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124) at scala.collection.immutable.List.foldLeft(List.scala:84) at org.apache.spark.sql.execution.QueryExecution.prepareForExecution(QueryExecution.scala:95) at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:85) at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:85) at org.apache.spark.sql.Dataset.withTypedCallback(Dataset.scala:2557) at org.apache.spark.sql.Dataset.head(Dataset.scala:1923) at org.apache.spark.sql.Dataset.take(Dataset.scala:2138) at org.apache.spark.sql.Dataset.showString(Dataset.scala:239) 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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:280) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:211) at java.lang.Thread.run(Thread.java:745) Caused by: java.lang.reflect.InvocationTargetException at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:423) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$makeCopy$1$$anonfun$apply$13.apply(TreeNode.scala:413) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$makeCopy$1$$anonfun$apply$13.apply(TreeNode.scala:413) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$makeCopy$1.apply(TreeNode.scala:412) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$makeCopy$1.apply(TreeNode.scala:387) at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:49) ... 42 more Caused by: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: pythonUDF0#20 at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:50) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:88) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:87) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:279) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:279) at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:69) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:278) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:284) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:284) at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:321) at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:179) at org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:319) at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:284) at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:268) at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:87) at org.apache.spark.sql.execution.GenerateExec.<init>(GenerateExec.scala:63) ... 52 more Caused by: java.lang.RuntimeException: Couldn't find pythonUDF0#20 in [_1#0L] at scala.sys.package$.error(package.scala:27) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:94) at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:88) at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:49) ... 67 more ``` ## How was this patch tested? Added regression tests. Author: Davies Liu <davies@databricks.com> Closes #13883 from davies/udf_in_generate.
* [SPARK-16077] [PYSPARK] catch the exception from pickle.whichmodule()Davies Liu2016-06-241-2/+12
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In the case that we don't know which module a object came from, will call pickle.whichmodule() to go throught all the loaded modules to find the object, which could fail because some modules, for example, six, see https://bitbucket.org/gutworth/six/issues/63/importing-six-breaks-pickling We should ignore the exception here, use `__main__` as the module name (it means we can't find the module). ## How was this patch tested? Manual tested. Can't have a unit test for this. Author: Davies Liu <davies@databricks.com> Closes #13788 from davies/whichmodule.
* [SPARK-16125][YARN] Fix not test yarn cluster mode correctly in YarnClusterSuitepeng.zhang2016-06-241-4/+0
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Since SPARK-13220(Deprecate "yarn-client" and "yarn-cluster"), YarnClusterSuite doesn't test "yarn cluster" mode correctly. This pull request fixes it. ## How was this patch tested? Unit test (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: peng.zhang <peng.zhang@xiaomi.com> Closes #13836 from renozhang/SPARK-16125-test-yarn-cluster-mode.
* [SPARK-16127][ML][PYPSARK] Audit @Since annotations related to ml.linalgNick Pentreath2016-06-222-6/+10
| | | | | | | | | | | | [SPARK-14615](https://issues.apache.org/jira/browse/SPARK-14615) and #12627 changed `spark.ml` pipelines to use the new `ml.linalg` classes for `Vector`/`Matrix`. Some `Since` annotations for public methods/vals have not been updated accordingly to be `2.0.0`. This PR updates them. ## How was this patch tested? Existing unit tests. Author: Nick Pentreath <nickp@za.ibm.com> Closes #13840 from MLnick/SPARK-16127-ml-linalg-since.
* [SPARK-15162][SPARK-15164][PYSPARK][DOCS][ML] update some pydocsHolden Karau2016-06-222-2/+37
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Mark ml.classification algorithms as experimental to match Scala algorithms, update PyDoc for for thresholds on `LogisticRegression` to have same level of info as Scala, and enable mathjax for PyDoc. ## How was this patch tested? Built docs locally & PySpark SQL tests Author: Holden Karau <holden@us.ibm.com> Closes #12938 from holdenk/SPARK-15162-SPARK-15164-update-some-pydocs.
* [SPARK-15741][PYSPARK][ML] Pyspark cleanup of set default seed to NoneBryan Cutler2016-06-214-7/+7
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Several places set the seed Param default value to None which will translate to a zero value on the Scala side. This is unnecessary because a default fixed value already exists and if a test depends on a zero valued seed, then it should explicitly set it to zero instead of relying on this translation. These cases can be safely removed except for the ALS doc test, which has been changed to set the seed value to zero. ## How was this patch tested? Ran PySpark tests locally Author: Bryan Cutler <cutlerb@gmail.com> Closes #13672 from BryanCutler/pyspark-cleanup-setDefault-seed-SPARK-15741.
* [SPARK-16086] [SQL] [PYSPARK] create Row without any fieldsDavies Liu2016-06-212-6/+12
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR allows us to create a Row without any fields. ## How was this patch tested? Added a test for empty row and udf without arguments. Author: Davies Liu <davies@databricks.com> Closes #13812 from davies/no_argus.
* [SPARK-13792][SQL] Addendum: Fix Python APIReynold Xin2016-06-211-21/+33
| | | | | | | | | | | | ## What changes were proposed in this pull request? This is a follow-up to https://github.com/apache/spark/pull/13795 to properly set CSV options in Python API. As part of this, I also make the Python option setting for both CSV and JSON more robust against positional errors. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #13800 from rxin/SPARK-13792-2.
* [SPARK-10258][DOC][ML] Add @Since annotations to ml.featureNick Pentreath2016-06-211-5/+5
| | | | | | | | | | | | | | This PR adds missing `Since` annotations to `ml.feature` package. Closes #8505. ## How was this patch tested? Existing tests. Author: Nick Pentreath <nickp@za.ibm.com> Closes #13641 from MLnick/add-since-annotations.
* Revert "[SPARK-16086] [SQL] fix Python UDF without arguments (for 1.6)"Xiangrui Meng2016-06-212-8/+6
| | | | This reverts commit a46553cbacf0e4012df89fe55385dec5beaa680a.
* [SPARK-13792][SQL] Limit logging of bad records in CSV data sourceReynold Xin2016-06-201-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This pull request adds a new option (maxMalformedLogPerPartition) in CSV reader to limit the maximum of logging message Spark generates per partition for malformed records. The error log looks something like ``` 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: Dropping malformed line: adsf,1,4 16/06/20 18:50:14 WARN CSVRelation: More than 10 malformed records have been found on this partition. Malformed records from now on will not be logged. ``` Closes #12173 ## How was this patch tested? Manually tested. Author: Reynold Xin <rxin@databricks.com> Closes #13795 from rxin/SPARK-13792.
* [SPARK-16086] [SQL] fix Python UDF without arguments (for 1.6)Davies Liu2016-06-202-6/+8
| | | | | | | | | | | | | Fix the bug for Python UDF that does not have any arguments. Added regression tests. Author: Davies Liu <davies.liu@gmail.com> Closes #13793 from davies/fix_no_arguments. (cherry picked from commit abe36c53d126bb580e408a45245fd8e81806869c) Signed-off-by: Davies Liu <davies.liu@gmail.com>
* [SPARK-16079][PYSPARK][ML] Added missing import for ↵Bryan Cutler2016-06-202-2/+6
| | | | | | | | | | | | | | | | DecisionTreeRegressionModel used in GBTClassificationModel ## What changes were proposed in this pull request? Fixed missing import for DecisionTreeRegressionModel used in GBTClassificationModel trees method. ## How was this patch tested? Local tests Author: Bryan Cutler <cutlerb@gmail.com> Closes #13787 from BryanCutler/pyspark-GBTClassificationModel-import-SPARK-16079.
* [SPARK-15973][PYSPARK] Fix GroupedData DocumentationJosh Howes2016-06-171-11/+11
| | | | | | | | | | | | | | | | | *This contribution is my original work and that I license the work to the project under the project's open source license.* ## What changes were proposed in this pull request? Documentation updates to PySpark's GroupedData ## How was this patch tested? Manual Tests Author: Josh Howes <josh.howes@gmail.com> Author: Josh Howes <josh.howes@maxpoint.com> Closes #13724 from josh-howes/bugfix/SPARK-15973.
* [SPARK-15803] [PYSPARK] Support with statement syntax for SparkSessionJeff Zhang2016-06-171-0/+16
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Support with statement syntax for SparkSession in pyspark ## How was this patch tested? Manually verify it. Although I can add unit test for it, it would affect other unit test because the SparkContext is stopped after the with statement. Author: Jeff Zhang <zjffdu@apache.org> Closes #13541 from zjffdu/SPARK-15803.
* [SPARK-16035][PYSPARK] Fix SparseVector parser assertion for end parenthesisandreapasqua2016-06-171-1/+1
| | | | | | | | | | | ## What changes were proposed in this pull request? The check on the end parenthesis of the expression to parse was using the wrong variable. I corrected that. ## How was this patch tested? Manual test Author: andreapasqua <andrea@radius.com> Closes #13750 from andreapasqua/sparse-vector-parser-assertion-fix.
* [SPARK-15946][MLLIB] Conversion between old/new vector columns in a ↵Xiangrui Meng2016-06-171-0/+82
| | | | | | | | | | | | | | | | | | DataFrame (Python) ## What changes were proposed in this pull request? This PR implements python wrappers for #13662 to convert old/new vector columns in a DataFrame. ## How was this patch tested? doctest in Python cc: yanboliang Author: Xiangrui Meng <meng@databricks.com> Closes #13731 from mengxr/SPARK-15946.
* [SPARK-15981][SQL][STREAMING] Fixed bug and added tests in DataStreamReader ↵Tathagata Das2016-06-161-122/+136
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Python API ## What changes were proposed in this pull request? - Fixed bug in Python API of DataStreamReader. Because a single path was being converted to a array before calling Java DataStreamReader method (which takes a string only), it gave the following error. ``` File "/Users/tdas/Projects/Spark/spark/python/pyspark/sql/readwriter.py", line 947, in pyspark.sql.readwriter.DataStreamReader.json Failed example: json_sdf = spark.readStream.json(os.path.join(tempfile.mkdtemp(), 'data'), schema = sdf_schema) Exception raised: Traceback (most recent call last): File "/System/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/doctest.py", line 1253, in __run compileflags, 1) in test.globs File "<doctest pyspark.sql.readwriter.DataStreamReader.json[0]>", line 1, in <module> json_sdf = spark.readStream.json(os.path.join(tempfile.mkdtemp(), 'data'), schema = sdf_schema) File "/Users/tdas/Projects/Spark/spark/python/pyspark/sql/readwriter.py", line 963, in json return self._df(self._jreader.json(path)) File "/Users/tdas/Projects/Spark/spark/python/lib/py4j-0.10.1-src.zip/py4j/java_gateway.py", line 933, in __call__ answer, self.gateway_client, self.target_id, self.name) File "/Users/tdas/Projects/Spark/spark/python/pyspark/sql/utils.py", line 63, in deco return f(*a, **kw) File "/Users/tdas/Projects/Spark/spark/python/lib/py4j-0.10.1-src.zip/py4j/protocol.py", line 316, in get_return_value format(target_id, ".", name, value)) Py4JError: An error occurred while calling o121.json. Trace: py4j.Py4JException: Method json([class java.util.ArrayList]) does not exist at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:318) at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:326) at py4j.Gateway.invoke(Gateway.java:272) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:211) at java.lang.Thread.run(Thread.java:744) ``` - Reduced code duplication between DataStreamReader and DataFrameWriter - Added missing Python doctests ## How was this patch tested? New tests Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #13703 from tdas/SPARK-15981.
* [SPARK-15888] [SQL] fix Python UDF with aggregateDavies Liu2016-06-151-1/+9
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? After we move the ExtractPythonUDF rule into physical plan, Python UDF can't work on top of aggregate anymore, because they can't be evaluated before aggregate, should be evaluated after aggregate. This PR add another rule to extract these kind of Python UDF from logical aggregate, create a Project on top of Aggregate. ## How was this patch tested? Added regression tests. The plan of added test query looks like this: ``` == Parsed Logical Plan == 'Project [<lambda>('k, 's) AS t#26] +- Aggregate [<lambda>(key#5L)], [<lambda>(key#5L) AS k#17, sum(cast(<lambda>(value#6) as bigint)) AS s#22L] +- LogicalRDD [key#5L, value#6] == Analyzed Logical Plan == t: int Project [<lambda>(k#17, s#22L) AS t#26] +- Aggregate [<lambda>(key#5L)], [<lambda>(key#5L) AS k#17, sum(cast(<lambda>(value#6) as bigint)) AS s#22L] +- LogicalRDD [key#5L, value#6] == Optimized Logical Plan == Project [<lambda>(agg#29, agg#30L) AS t#26] +- Aggregate [<lambda>(key#5L)], [<lambda>(key#5L) AS agg#29, sum(cast(<lambda>(value#6) as bigint)) AS agg#30L] +- LogicalRDD [key#5L, value#6] == Physical Plan == *Project [pythonUDF0#37 AS t#26] +- BatchEvalPython [<lambda>(agg#29, agg#30L)], [agg#29, agg#30L, pythonUDF0#37] +- *HashAggregate(key=[<lambda>(key#5L)#31], functions=[sum(cast(<lambda>(value#6) as bigint))], output=[agg#29,agg#30L]) +- Exchange hashpartitioning(<lambda>(key#5L)#31, 200) +- *HashAggregate(key=[pythonUDF0#34 AS <lambda>(key#5L)#31], functions=[partial_sum(cast(pythonUDF1#35 as bigint))], output=[<lambda>(key#5L)#31,sum#33L]) +- BatchEvalPython [<lambda>(key#5L), <lambda>(value#6)], [key#5L, value#6, pythonUDF0#34, pythonUDF1#35] +- Scan ExistingRDD[key#5L,value#6] ``` Author: Davies Liu <davies@databricks.com> Closes #13682 from davies/fix_py_udf.
* [SPARK-15953][WIP][STREAMING] Renamed ContinuousQuery to StreamingQueryTathagata Das2016-06-157-100/+99
| | | | | | | | | | Renamed for simplicity, so that its obvious that its related to streaming. Existing unit tests. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #13673 from tdas/SPARK-15953.
* [SPARK-15935][PYSPARK] Fix a wrong format tag in the error messageShixiong Zhu2016-06-141-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? A follow up PR for #13655 to fix a wrong format tag. ## How was this patch tested? Jenkins unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #13665 from zsxwing/fix.
* [SPARK-15933][SQL][STREAMING] Refactored DF reader-writer to use readStream ↵Tathagata Das2016-06-146-168/+570
| | | | | | | | | | | | | | | | and writeStream for streaming DFs ## What changes were proposed in this pull request? Currently, the DataFrameReader/Writer has method that are needed for streaming and non-streaming DFs. This is quite awkward because each method in them through runtime exception for one case or the other. So rather having half the methods throw runtime exceptions, its just better to have a different reader/writer API for streams. - [x] Python API!! ## How was this patch tested? Existing unit tests + two sets of unit tests for DataFrameReader/Writer and DataStreamReader/Writer. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #13653 from tdas/SPARK-15933.
* [SPARK-15935][PYSPARK] Enable test for sql/streaming.py and fix these testsShixiong Zhu2016-06-143-20/+54
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR just enables tests for sql/streaming.py and also fixes the failures. ## How was this patch tested? Existing unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #13655 from zsxwing/python-streaming-test.
* [SPARK-15663][SQL] SparkSession.catalog.listFunctions shouldn't include the ↵Sandeep Singh2016-06-131-11/+1
| | | | | | | | | | | | | | list of built-in functions ## What changes were proposed in this pull request? SparkSession.catalog.listFunctions currently returns all functions, including the list of built-in functions. This makes the method not as useful because anytime it is run the result set contains over 100 built-in functions. ## How was this patch tested? CatalogSuite Author: Sandeep Singh <sandeep@techaddict.me> Closes #13413 from techaddict/SPARK-15663.
* [SPARK-15364][ML][PYSPARK] Implement PySpark picklers for ml.Vector and ↵Liang-Chi Hsieh2016-06-1314-16/+154
| | | | | | | | | | | | | | | ml.Matrix under spark.ml.python ## What changes were proposed in this pull request? Now we have PySpark picklers for new and old vector/matrix, individually. However, they are all implemented under `PythonMLlibAPI`. To separate spark.mllib from spark.ml, we should implement the picklers of new vector/matrix under `spark.ml.python` instead. ## How was this patch tested? Existing tests. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Closes #13219 from viirya/pyspark-pickler-ml.
* [SPARK-15898][SQL] DataFrameReader.text should return DataFrameWenchen Fan2016-06-121-4/+4
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? We want to maintain API compatibility for DataFrameReader.text, and will introduce a new API called DataFrameReader.textFile which returns Dataset[String]. affected PRs: https://github.com/apache/spark/pull/11731 https://github.com/apache/spark/pull/13104 https://github.com/apache/spark/pull/13184 ## How was this patch tested? N/A Author: Wenchen Fan <wenchen@databricks.com> Closes #13604 from cloud-fan/revert.
* [SPARK-15840][SQL] Add two missing options in documentation and some option ↵hyukjinkwon2016-06-111-13/+27
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | related changes ## What changes were proposed in this pull request? This PR 1. Adds the documentations for some missing options, `inferSchema` and `mergeSchema` for Python and Scala. 2. Fiixes `[[DataFrame]]` to ```:class:`DataFrame` ``` so that this can be shown - from ![2016-06-09 9 31 16](https://cloud.githubusercontent.com/assets/6477701/15929721/8b864734-2e89-11e6-83f6-207527de4ac9.png) - to (with class link) ![2016-06-09 9 31 00](https://cloud.githubusercontent.com/assets/6477701/15929717/8a03d728-2e89-11e6-8a3f-08294964db22.png) (Please refer [the latest documentation](https://people.apache.org/~pwendell/spark-nightly/spark-master-docs/latest/api/python/pyspark.sql.html)) 3. Moves `mergeSchema` option to `ParquetOptions` with removing unused options, `metastoreSchema` and `metastoreTableName`. They are not used anymore. They were removed in https://github.com/apache/spark/commit/e720dda42e806229ccfd970055c7b8a93eb447bf and there are no use cases as below: ```bash grep -r -e METASTORE_SCHEMA -e \"metastoreSchema\" -e \"metastoreTableName\" -e METASTORE_TABLE_NAME . ``` ``` ./sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala: private[sql] val METASTORE_SCHEMA = "metastoreSchema" ./sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFileFormat.scala: private[sql] val METASTORE_TABLE_NAME = "metastoreTableName" ./sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala: ParquetFileFormat.METASTORE_TABLE_NAME -> TableIdentifier( ``` It only sets `metastoreTableName` in the last case but does not use the table name. 4. Sets the correct default values (in the documentation) for `compression` option for ORC(`snappy`, see [OrcOptions.scala#L33-L42](https://github.com/apache/spark/blob/3ded5bc4db2badc9ff49554e73421021d854306b/sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcOptions.scala#L33-L42)) and Parquet(`the value specified in SQLConf`, see [ParquetOptions.scala#L38-L47](https://github.com/apache/spark/blob/3ded5bc4db2badc9ff49554e73421021d854306b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetOptions.scala#L38-L47)) and `columnNameOfCorruptRecord` for JSON(`the value specified in SQLConf`, see [JsonFileFormat.scala#L53-L55](https://github.com/apache/spark/blob/4538443e276597530a27c6922e48503677b13956/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JsonFileFormat.scala#L53-L55) and [JsonFileFormat.scala#L105-L106](https://github.com/apache/spark/blob/4538443e276597530a27c6922e48503677b13956/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/json/JsonFileFormat.scala#L105-L106)). ## How was this patch tested? Existing tests should cover this. Author: hyukjinkwon <gurwls223@gmail.com> Author: Hyukjin Kwon <gurwls223@gmail.com> Closes #13576 from HyukjinKwon/SPARK-15840.
* [SPARK-15585][SQL] Add doc for turning off quotationsTakeshi YAMAMURO2016-06-111-2/+4
| | | | | | | | | | | | ## What changes were proposed in this pull request? This pr is to add doc for turning off quotations because this behavior is different from `com.databricks.spark.csv`. ## How was this patch tested? Check behavior to put an empty string in csv options. Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #13616 from maropu/SPARK-15585-2.
* [SPARK-15738][PYSPARK][ML] Adding Pyspark ml RFormula __str__ method similar ↵Bryan Cutler2016-06-101-0/+12
| | | | | | | | | | | | | | to Scala API ## What changes were proposed in this pull request? Adding __str__ to RFormula and model that will show the set formula param and resolved formula. This is currently present in the Scala API, found missing in PySpark during Spark 2.0 coverage review. ## How was this patch tested? run pyspark-ml tests locally Author: Bryan Cutler <cutlerb@gmail.com> Closes #13481 from BryanCutler/pyspark-ml-rformula_str-SPARK-15738.
* [SPARK-15837][ML][PYSPARK] Word2vec python add maxsentence parameterWeichenXu2016-06-101-5/+24
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Word2vec python add maxsentence parameter. ## How was this patch tested? Existing test. Author: WeichenXu <WeichenXu123@outlook.com> Closes #13578 from WeichenXu123/word2vec_python_add_maxsentence.
* [SPARK-15823][PYSPARK][ML] Add @property for 'accuracy' in MulticlassMetricsZheng RuiFeng2016-06-101-5/+2
| | | | | | | | | | | | ## What changes were proposed in this pull request? `accuracy` should be decorated with `property` to keep step with other methods in `pyspark.MulticlassMetrics`, like `weightedPrecision`, `weightedRecall`, etc ## How was this patch tested? manual tests Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #13560 from zhengruifeng/add_accuracy_property.
* [SPARK-15788][PYSPARK][ML] PySpark IDFModel missing "idf" propertyJeff Zhang2016-06-091-0/+10
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? add method idf to IDF in pyspark ## How was this patch tested? add unit test Author: Jeff Zhang <zjffdu@apache.org> Closes #13540 from zjffdu/SPARK-15788.
* [SPARK-14900][ML][PYSPARK] Add accuracy and deprecate precison,recall,f1Zheng RuiFeng2016-06-061-0/+18
| | | | | | | | | | | | | ## What changes were proposed in this pull request? 1, add accuracy for MulticlassMetrics 2, deprecate overall precision,recall,f1 and recommend accuracy usage ## How was this patch tested? manual tests in pyspark shell Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #13511 from zhengruifeng/deprecate_py_precisonrecall.
* [SPARK-15771][ML][EXAMPLES] Use 'accuracy' rather than 'precision' in many ↵Yanbo Liang2016-06-061-1/+1
| | | | | | | | | | | | | | | | | | ML examples ## What changes were proposed in this pull request? Since [SPARK-15617](https://issues.apache.org/jira/browse/SPARK-15617) deprecated ```precision``` in ```MulticlassClassificationEvaluator```, many ML examples broken. ```python pyspark.sql.utils.IllegalArgumentException: u'MulticlassClassificationEvaluator_4c3bb1d73d8cc0cedae6 parameter metricName given invalid value precision.' ``` We should use ```accuracy``` to replace ```precision``` in these examples. ## How was this patch tested? Offline tests. Author: Yanbo Liang <ybliang8@gmail.com> Closes #13519 from yanboliang/spark-15771.
* [MINOR] Fix Typos 'an -> a'Zheng RuiFeng2016-06-069-12/+12
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? `an -> a` Use cmds like `find . -name '*.R' | xargs -i sh -c "grep -in ' an [^aeiou]' {} && echo {}"` to generate candidates, and review them one by one. ## How was this patch tested? manual tests Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #13515 from zhengruifeng/an_a.
* Revert "[SPARK-15585][SQL] Fix NULL handling along with a spark-csv behaivour"Reynold Xin2016-06-051-39/+42
| | | | This reverts commit b7e8d1cb3ce932ba4a784be59744af8a8ef027ce.
* [SPARK-15585][SQL] Fix NULL handling along with a spark-csv behaivourTakeshi YAMAMURO2016-06-051-42/+39
| | | | | | | | | | | | | ## What changes were proposed in this pull request? This pr fixes the behaviour of `format("csv").option("quote", null)` along with one of spark-csv. Also, it explicitly sets default values for CSV options in python. ## How was this patch tested? Added tests in CSVSuite. Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #13372 from maropu/SPARK-15585.
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