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* [SPARK-19872] [PYTHON] Use the correct deserializer for RDD construction for ↵hyukjinkwon2017-03-151-0/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | coalesce/repartition ## What changes were proposed in this pull request? This PR proposes to use the correct deserializer, `BatchedSerializer` for RDD construction for coalesce/repartition when the shuffle is enabled. Currently, it is passing `UTF8Deserializer` as is not `BatchedSerializer` from the copied one. with the file, `text.txt` below: ``` a b d e f g h i j k l ``` - Before ```python >>> sc.textFile('text.txt').repartition(1).collect() ``` ``` UTF8Deserializer(True) Traceback (most recent call last): File "<stdin>", line 1, in <module> File ".../spark/python/pyspark/rdd.py", line 811, in collect return list(_load_from_socket(port, self._jrdd_deserializer)) File ".../spark/python/pyspark/serializers.py", line 549, in load_stream yield self.loads(stream) File ".../spark/python/pyspark/serializers.py", line 544, in loads return s.decode("utf-8") if self.use_unicode else s File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/encodings/utf_8.py", line 16, in decode return codecs.utf_8_decode(input, errors, True) UnicodeDecodeError: 'utf8' codec can't decode byte 0x80 in position 0: invalid start byte ``` - After ```python >>> sc.textFile('text.txt').repartition(1).collect() ``` ``` [u'a', u'b', u'', u'd', u'e', u'f', u'g', u'h', u'i', u'j', u'k', u'l', u''] ``` ## How was this patch tested? Unit test in `python/pyspark/tests.py`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #17282 from HyukjinKwon/SPARK-19872.
* [SPARK-19348][PYTHON] PySpark keyword_only decorator is not thread-safeBryan Cutler2017-03-031-0/+39
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The `keyword_only` decorator in PySpark is not thread-safe. It writes kwargs to a static class variable in the decorator, which is then retrieved later in the class method as `_input_kwargs`. If multiple threads are constructing the same class with different kwargs, it becomes a race condition to read from the static class variable before it's overwritten. See [SPARK-19348](https://issues.apache.org/jira/browse/SPARK-19348) for reproduction code. This change will write the kwargs to a member variable so that multiple threads can operate on separate instances without the race condition. It does not protect against multiple threads operating on a single instance, but that is better left to the user to synchronize. ## How was this patch tested? Added new unit tests for using the keyword_only decorator and a regression test that verifies `_input_kwargs` can be overwritten from different class instances. Author: Bryan Cutler <cutlerb@gmail.com> Closes #16782 from BryanCutler/pyspark-keyword_only-threadsafe-SPARK-19348.
* [SPARK-19660][CORE][SQL] Replace the configuration property names that are ↵Yuming Wang2017-02-281-23/+24
| | | | | | | | | | | | | | | | | | | | | | deprecated in the version of Hadoop 2.6 ## What changes were proposed in this pull request? Replace all the Hadoop deprecated configuration property names according to [DeprecatedProperties](https://hadoop.apache.org/docs/r2.6.0/hadoop-project-dist/hadoop-common/DeprecatedProperties.html). except: https://github.com/apache/spark/blob/v2.1.0/python/pyspark/sql/tests.py#L1533 https://github.com/apache/spark/blob/v2.1.0/sql/core/src/test/scala/org/apache/spark/sql/SQLQuerySuite.scala#L987 https://github.com/apache/spark/blob/v2.1.0/sql/core/src/main/scala/org/apache/spark/sql/execution/command/SetCommand.scala#L45 https://github.com/apache/spark/blob/v2.1.0/sql/core/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala#L614 ## How was this patch tested? Existing tests Author: Yuming Wang <wgyumg@gmail.com> Closes #16990 from wangyum/HadoopDeprecatedProperties.
* [SPARK-19307][PYSPARK] Make sure user conf is propagated to SparkContext.Marcelo Vanzin2017-01-251-0/+20
| | | | | | | | | | | | The code was failing to propagate the user conf in the case where the JVM was already initialized, which happens when a user submits a python script via spark-submit. Tested with new unit test and by running a python script in a real cluster. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #16682 from vanzin/SPARK-19307.
* [SPARK-18576][PYTHON] Add basic TaskContext information to PySparkHolden Karau2016-12-201-0/+65
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Adds basic TaskContext information to PySpark. ## How was this patch tested? New unit tests to `tests.py` & existing unit tests. Author: Holden Karau <holden@us.ibm.com> Closes #16211 from holdenk/SPARK-18576-pyspark-taskcontext.
* [SPARK-18281] [SQL] [PYSPARK] Remove timeout for reading data through socket ↵Liang-Chi Hsieh2016-12-201-0/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | for local iterator ## What changes were proposed in this pull request? There is a timeout failure when using `rdd.toLocalIterator()` or `df.toLocalIterator()` for a PySpark RDD and DataFrame: df = spark.createDataFrame([[1],[2],[3]]) it = df.toLocalIterator() row = next(it) df2 = df.repartition(1000) # create many empty partitions which increase materialization time so causing timeout it2 = df2.toLocalIterator() row = next(it2) The cause of this issue is, we open a socket to serve the data from JVM side. We set timeout for connection and reading through the socket in Python side. In Python we use a generator to read the data, so we only begin to connect the socket once we start to ask data from it. If we don't consume it immediately, there is connection timeout. In the other side, the materialization time for RDD partitions is unpredictable. So we can't set a timeout for reading data through the socket. Otherwise, it is very possibly to fail. ## How was this patch tested? Added tests into PySpark. Please review http://spark.apache.org/contributing.html before opening a pull request. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #16263 from viirya/fix-pyspark-localiterator.
* [SPARK-16589] [PYTHON] Chained cartesian produces incorrect number of recordsAndrew Ray2016-12-081-0/+18
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Fixes a bug in the python implementation of rdd cartesian product related to batching that showed up in repeated cartesian products with seemingly random results. The root cause being multiple iterators pulling from the same stream in the wrong order because of logic that ignored batching. `CartesianDeserializer` and `PairDeserializer` were changed to implement `_load_stream_without_unbatching` and borrow the one line implementation of `load_stream` from `BatchedSerializer`. The default implementation of `_load_stream_without_unbatching` was changed to give consistent results (always an iterable) so that it could be used without additional checks. `PairDeserializer` no longer extends `CartesianDeserializer` as it was not really proper. If wanted a new common super class could be added. Both `CartesianDeserializer` and `PairDeserializer` now only extend `Serializer` (which has no `dump_stream` implementation) since they are only meant for *de*serialization. ## How was this patch tested? Additional unit tests (sourced from #14248) plus one for testing a cartesian with zip. Author: Andrew Ray <ray.andrew@gmail.com> Closes #16121 from aray/fix-cartesian.
* [SPARK-18361][PYSPARK] Expose RDD localCheckpoint in PySparkGabriel Huang2016-11-211-0/+17
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Expose RDD's localCheckpoint() and associated functions in PySpark. ## How was this patch tested? I added a UnitTest in python/pyspark/tests.py which passes. I certify that this is my original work, and I license it to the project under the project's open source license. Gabriel HUANG Developer at Cardabel (http://cardabel.com/) Author: Gabriel Huang <gabi.xiaohuang@gmail.com> Closes #15811 from gabrielhuang/pyspark-localcheckpoint.
* [SPARK-17817][PYSPARK] PySpark RDD Repartitioning Results in Highly Skewed ↵Liang-Chi Hsieh2016-10-111-0/+10
| | | | | | | | | | | | | | | | | | | | | | | | | | | Partition Sizes ## What changes were proposed in this pull request? Quoted from JIRA description: Calling repartition on a PySpark RDD to increase the number of partitions results in highly skewed partition sizes, with most having 0 rows. The repartition method should evenly spread out the rows across the partitions, and this behavior is correctly seen on the Scala side. Please reference the following code for a reproducible example of this issue: num_partitions = 20000 a = sc.parallelize(range(int(1e6)), 2) # start with 2 even partitions l = a.repartition(num_partitions).glom().map(len).collect() # get length of each partition min(l), max(l), sum(l)/len(l), len(l) # skewed! In Scala's `repartition` code, we will distribute elements evenly across output partitions. However, the RDD from Python is serialized as a single binary data, so the distribution fails. We need to convert the RDD in Python to java object before repartitioning. ## How was this patch tested? Jenkins tests. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #15389 from viirya/pyspark-rdd-repartition.
* [SPARK-17585][PYSPARK][CORE] PySpark SparkContext.addFile supports adding ↵Yanbo Liang2016-09-211-5/+15
| | | | | | | | | | | | | | files recursively ## What changes were proposed in this pull request? Users would like to add a directory as dependency in some cases, they can use ```SparkContext.addFile``` with argument ```recursive=true``` to recursively add all files under the directory by using Scala. But Python users can only add file not directory, we should also make it supported. ## How was this patch tested? Unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15140 from yanboliang/spark-17585.
* [SPARK-16224] [SQL] [PYSPARK] SparkSession builder's configs need to be set ↵Yin Huai2016-06-281-0/+8
| | | | | | | | | | | | | | 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-15433] [PYSPARK] PySpark core test should not use SerDe from ↵Liang-Chi Hsieh2016-05-241-2/+2
| | | | | | | | | | | | | | | PythonMLLibAPI ## What changes were proposed in this pull request? Currently PySpark core test uses the `SerDe` from `PythonMLLibAPI` which includes many MLlib things. It should use `SerDeUtil` instead. ## How was this patch tested? Existing tests. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Closes #13214 from viirya/pycore-use-serdeutil.
* [SPARK-13687][PYTHON] Cleanup PySpark parallelize temporary filesHolden Karau2016-04-101-0/+7
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Eagerly cleanup PySpark's temporary parallelize cleanup files rather than waiting for shut down. ## How was this patch tested? Unit tests Author: Holden Karau <holden@us.ibm.com> Closes #12233 from holdenk/SPARK-13687-cleanup-pyspark-temporary-files.
* [SPARK-14418][PYSPARK] fix unpersist of Broadcast in PythonDavies Liu2016-04-061-0/+15
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently, Broaccast.unpersist() will remove the file of broadcast, which should be the behavior of destroy(). This PR added destroy() for Broadcast in Python, to match the sematics in Scala. ## How was this patch tested? Added regression tests. Author: Davies Liu <davies@databricks.com> Closes #12189 from davies/py_unpersist.
* [SPARK-14368][PYSPARK] Support python.spark.worker.memory with upper-case unit.Yong Tang2016-04-051-0/+12
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This fix tries to address the issue in PySpark where `spark.python.worker.memory` could only be configured with a lower case unit (`k`, `m`, `g`, `t`). This fix allows the upper case unit (`K`, `M`, `G`, `T`) to be used as well. This is to conform to the JVM memory string as is specified in the documentation . ## How was this patch tested? This fix adds additional test to cover the changes. Author: Yong Tang <yong.tang.github@outlook.com> Closes #12163 from yongtang/SPARK-14368.
* [SPARK-13697] [PYSPARK] Fix the missing module name of ↵Shixiong Zhu2016-03-061-0/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | TransformFunctionSerializer.loads ## What changes were proposed in this pull request? Set the function's module name to `__main__` if it's missing in `TransformFunctionSerializer.loads`. ## How was this patch tested? Manually test in the shell. Before this patch: ``` >>> from pyspark.streaming import StreamingContext >>> from pyspark.streaming.util import TransformFunction >>> ssc = StreamingContext(sc, 1) >>> func = TransformFunction(sc, lambda x: x, sc.serializer) >>> func.rdd_wrapper(lambda x: x) TransformFunction(<function <lambda> at 0x106ac8b18>) >>> bytes = bytearray(ssc._transformerSerializer.serializer.dumps((func.func, func.rdd_wrap_func, func.deserializers))) >>> func2 = ssc._transformerSerializer.loads(bytes) >>> print(func2.func.__module__) None >>> print(func2.rdd_wrap_func.__module__) None >>> ``` After this patch: ``` >>> from pyspark.streaming import StreamingContext >>> from pyspark.streaming.util import TransformFunction >>> ssc = StreamingContext(sc, 1) >>> func = TransformFunction(sc, lambda x: x, sc.serializer) >>> func.rdd_wrapper(lambda x: x) TransformFunction(<function <lambda> at 0x108bf1b90>) >>> bytes = bytearray(ssc._transformerSerializer.serializer.dumps((func.func, func.rdd_wrap_func, func.deserializers))) >>> func2 = ssc._transformerSerializer.loads(bytes) >>> print(func2.func.__module__) __main__ >>> print(func2.rdd_wrap_func.__module__) __main__ >>> ``` Author: Shixiong Zhu <shixiong@databricks.com> Closes #11535 from zsxwing/loads-module.
* [SPARK-11295][PYSPARK] Add packages to JUnit output for Python testsGábor Lipták2016-01-201-0/+1
| | | | | | | | | This is #9263 from gliptak (improving grouping/display of test case results) with a small fix of bisecting k-means unit test. Author: Gábor Lipták <gliptak@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #10850 from mengxr/SPARK-11295.
* Revert "[SPARK-11295] Add packages to JUnit output for Python tests"Xiangrui Meng2016-01-191-1/+0
| | | | This reverts commit c6f971b4aeca7265ab374fa46c5c452461d9b6a7.
* [SPARK-11295] Add packages to JUnit output for Python testsGábor Lipták2016-01-191-0/+1
| | | | | | | | | | SPARK-11295 Add packages to JUnit output for Python tests This improves grouping/display of test case results. Author: Gábor Lipták <gliptak@gmail.com> Closes #9263 from gliptak/SPARK-11295.
* [SPARK-7021] Add JUnit output for Python unit testsGábor Lipták2015-10-221-5/+14
| | | | | | | | WIP Author: Gábor Lipták <gliptak@gmail.com> Closes #8323 from gliptak/SPARK-7021.
* [SPARK-11114][PYSPARK] add getOrCreate for SparkContext/SQLContext in PythonDavies Liu2015-10-191-0/+4
| | | | | | | | Also added SQLContext.newSession() Author: Davies Liu <davies@databricks.com> Closes #9122 from davies/py_create.
* [SPARK-6919] [PYSPARK] Add asDict method to StatCounterErik Shilts2015-09-291-0/+20
| | | | | | | | | | | | Add method to easily convert a StatCounter instance into a Python dict https://issues.apache.org/jira/browse/SPARK-6919 Note: This is my original work and the existing Spark license applies. Author: Erik Shilts <erik.shilts@opower.com> Closes #5516 from eshilts/statcounter-asdict.
* [SPARK-10710] Remove ability to disable spilling in core and SQLJosh Rosen2015-09-191-12/+1
| | | | | | | | | | It does not make much sense to set `spark.shuffle.spill` or `spark.sql.planner.externalSort` to false: I believe that these configurations were initially added as "escape hatches" to guard against bugs in the external operators, but these operators are now mature and well-tested. In addition, these configurations are not handled in a consistent way anymore: SQL's Tungsten codepath ignores these configurations and will continue to use spilling operators. Similarly, Spark Core's `tungsten-sort` shuffle manager does not respect `spark.shuffle.spill=false`. This pull request removes these configurations, adds warnings at the appropriate places, and deletes a large amount of code which was only used in code paths that did not support spilling. Author: Josh Rosen <joshrosen@databricks.com> Closes #8831 from JoshRosen/remove-ability-to-disable-spilling.
* [SPARK-10542] [PYSPARK] fix serialize namedtupleDavies Liu2015-09-141-0/+5
| | | | | | Author: Davies Liu <davies@databricks.com> Closes #8707 from davies/fix_namedtuple.
* [SPARK-9244] Increase some memory defaultsMatei Zaharia2015-07-221-3/+3
| | | | | | | | | | | | | | | | | | | There are a few memory limits that people hit often and that we could make higher, especially now that memory sizes have grown. - spark.akka.frameSize: This defaults at 10 but is often hit for map output statuses in large shuffles. This memory is not fully allocated up-front, so we can just make this larger and still not affect jobs that never sent a status that large. We increase it to 128. - spark.executor.memory: Defaults at 512m, which is really small. We increase it to 1g. Author: Matei Zaharia <matei@databricks.com> Closes #7586 from mateiz/configs and squashes the following commits: ce0038a [Matei Zaharia] [SPARK-9244] Increase some memory defaults
* [SPARK-9021] [PYSPARK] Change RDD.aggregate() to do reduce(mapPartitions()) ↵Nicholas Hwang2015-07-191-12/+129
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | instead of mapPartitions.fold() I'm relatively new to Spark and functional programming, so forgive me if this pull request is just a result of my misunderstanding of how Spark should be used. Currently, if one happens to use a mutable object as `zeroValue` for `RDD.aggregate()`, possibly unexpected behavior can occur. This is because pyspark's current implementation of `RDD.aggregate()` does not serialize or make a copy of `zeroValue` before handing it off to `RDD.mapPartitions(...).fold(...)`. This results in a single reference to `zeroValue` being used for both `RDD.mapPartitions()` and `RDD.fold()` on each partition. This can result in strange accumulator values being fed into each partition's call to `RDD.fold()`, as the `zeroValue` may have been changed in-place during the `RDD.mapPartitions()` call. As an illustrative example, submit the following to `spark-submit`: ``` from pyspark import SparkConf, SparkContext import collections def updateCounter(acc, val): print 'update acc:', acc print 'update val:', val acc[val] += 1 return acc def comboCounter(acc1, acc2): print 'combo acc1:', acc1 print 'combo acc2:', acc2 acc1.update(acc2) return acc1 def main(): conf = SparkConf().setMaster("local").setAppName("Aggregate with Counter") sc = SparkContext(conf = conf) print '======= AGGREGATING with ONE PARTITION =======' print sc.parallelize(range(1,10), 1).aggregate(collections.Counter(), updateCounter, comboCounter) print '======= AGGREGATING with TWO PARTITIONS =======' print sc.parallelize(range(1,10), 2).aggregate(collections.Counter(), updateCounter, comboCounter) if __name__ == "__main__": main() ``` One probably expects this to output the following: ``` Counter({1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1}) ``` But it instead outputs this (regardless of the number of partitions): ``` Counter({1: 2, 2: 2, 3: 2, 4: 2, 5: 2, 6: 2, 7: 2, 8: 2, 9: 2}) ``` This is because (I believe) `zeroValue` gets passed correctly to each partition, but after `RDD.mapPartitions()` completes, the `zeroValue` object has been updated and is then passed to `RDD.fold()`, which results in all items being double-counted within each partition before being finally reduced at the calling node. I realize that this type of calculation is typically done by `RDD.mapPartitions(...).reduceByKey(...)`, but hopefully this illustrates some potentially confusing behavior. I also noticed that other `RDD` methods use this `deepcopy` approach to creating unique copies of `zeroValue` (i.e., `RDD.aggregateByKey()` and `RDD.foldByKey()`), and that the Scala implementations do seem to serialize the `zeroValue` object appropriately to prevent this type of behavior. Author: Nicholas Hwang <moogling@gmail.com> Closes #7378 from njhwang/master and squashes the following commits: 659bb27 [Nicholas Hwang] Fixed RDD.aggregate() to perform a reduce operation on collected mapPartitions results, similar to how fold currently is implemented. This prevents an initial combOp being performed on each partition with zeroValue (which leads to unexpected behavior if zeroValue is a mutable object) before being combOp'ed with other partition results. 8d8d694 [Nicholas Hwang] Changed dict construction to be compatible with Python 2.6 (cannot use list comprehensions to make dicts) 56eb2ab [Nicholas Hwang] Fixed whitespace after colon to conform with PEP8 391de4a [Nicholas Hwang] Removed used of collections.Counter from RDD tests for Python 2.6 compatibility; used defaultdict(int) instead. Merged treeAggregate test with mutable zero value into aggregate test to reduce code duplication. 2fa4e4b [Nicholas Hwang] Merge branch 'master' of https://github.com/njhwang/spark ba528bd [Nicholas Hwang] Updated comments regarding protection of zeroValue from mutation in RDD.aggregate(). Added regression tests for aggregate(), fold(), aggregateByKey(), foldByKey(), and treeAggregate(), all with both 1 and 2 partition RDDs. Confirmed that aggregate() is the only problematic implementation as of commit 257236c3e17906098f801cbc2059e7a9054e8cab. Also replaced some parallelizations of ranges with xranges, per the documentation's recommendations of preferring xrange over range. 7820391 [Nicholas Hwang] Updated comments regarding protection of zeroValue from mutation in RDD.aggregate(). Added regression tests for aggregate(), fold(), aggregateByKey(), foldByKey(), and treeAggregate(), all with both 1 and 2 partition RDDs. Confirmed that aggregate() is the only problematic implementation as of commit 257236c3e17906098f801cbc2059e7a9054e8cab. 90d1544 [Nicholas Hwang] Made sure RDD.aggregate() makes a deepcopy of zeroValue for all partitions; this ensures that the mapPartitions call works with unique copies of zeroValue in each partition, and prevents a single reference to zeroValue being used for both map and fold calls on each partition (resulting in possibly unexpected behavior).
* [SPARK-8706] [PYSPARK] [PROJECT INFRA] Add pylint checks to PySparkMechCoder2015-07-151-1/+2
| | | | | | | | | | | | | | | | | | | | | This adds Pylint checks to PySpark. For now this lazy installs using easy_install to /dev/pylint (similar to the pep8 script). We still need to figure out what rules to be allowed. Author: MechCoder <manojkumarsivaraj334@gmail.com> Closes #7241 from MechCoder/pylint and squashes the following commits: 2fc7291 [MechCoder] Remove pylint test fail 6d883a2 [MechCoder] Silence warnings and make pylint tests fail to check if it works in jenkins f3a5e17 [MechCoder] undefined-variable ca8b749 [MechCoder] Minor changes 71629f8 [MechCoder] remove trailing whitespace 8498ff9 [MechCoder] Remove blacklisted arguments and pointless statements check 1dbd094 [MechCoder] Disable all checks for now 8b8aa8a [MechCoder] Add pylint configuration file 7871bb1 [MechCoder] [SPARK-8706] [PySpark] [Project infra] Add pylint checks to PySpark
* [SPARK-7735] [PYSPARK] Raise Exception on non-zero exit from pipe commandsScott Taylor2015-07-101-0/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This will allow problems with piped commands to be detected. This will also allow tasks to be retried where errors are rare (such as network problems in piped commands). Author: Scott Taylor <github@megatron.me.uk> Closes #6262 from megatron-me-uk/patch-2 and squashes the following commits: 04ae1d5 [Scott Taylor] Remove spurious empty line 98fa101 [Scott Taylor] fix blank line style error 574b564 [Scott Taylor] Merge pull request #2 from megatron-me-uk/patch-4 0c1e762 [Scott Taylor] Update rdd pipe method for checkCode ab9a2e1 [Scott Taylor] Update rdd pipe tests for checkCode eb4801c [Scott Taylor] fix fail_condition b0ac3a4 [Scott Taylor] Merge pull request #1 from megatron-me-uk/megatron-me-uk-patch-1 a307d13 [Scott Taylor] update rdd tests to test pipe modes 34fcdc3 [Scott Taylor] add optional argument 'mode' for rdd.pipe a0c0161 [Scott Taylor] fix generator issue 8a9ef9c [Scott Taylor] make check_return_code an iterator 0486ae3 [Scott Taylor] style fixes 8ed89a6 [Scott Taylor] Chain generators to prevent potential deadlock 4153b02 [Scott Taylor] fix list.sort returns None 491d3fc [Scott Taylor] Pass a function handle to assertRaises 3344a21 [Scott Taylor] wrap assertRaises with QuietTest 3ab8c7a [Scott Taylor] remove whitespace for style cc1a73d [Scott Taylor] fix style issues in pipe test 8db4073 [Scott Taylor] Add a test for rdd pipe functions 1b3dc4e [Scott Taylor] fix missing space around operator style 0974f98 [Scott Taylor] add space between words in multiline string 45f4977 [Scott Taylor] fix line too long style error 5745d85 [Scott Taylor] Remove space to fix style f552d49 [Scott Taylor] Catch non-zero exit from pipe commands
* [SPARK-8583] [SPARK-5482] [BUILD] Refactor python/run-tests to integrate ↵Josh Rosen2015-06-271-1/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | with dev/run-tests module system This patch refactors the `python/run-tests` script: - It's now written in Python instead of Bash. - The descriptions of the tests to run are now stored in `dev/run-tests`'s modules. This allows the pull request builder to skip Python tests suites that were not affected by the pull request's changes. For example, we can now skip the PySpark Streaming test cases when only SQL files are changed. - `python/run-tests` now supports command-line flags to make it easier to run individual test suites (this addresses SPARK-5482): ``` Usage: run-tests [options] Options: -h, --help show this help message and exit --python-executables=PYTHON_EXECUTABLES A comma-separated list of Python executables to test against (default: python2.6,python3.4,pypy) --modules=MODULES A comma-separated list of Python modules to test (default: pyspark-core,pyspark-ml,pyspark-mllib ,pyspark-sql,pyspark-streaming) ``` - `dev/run-tests` has been split into multiple files: the module definitions and test utility functions are now stored inside of a `dev/sparktestsupport` Python module, allowing them to be re-used from the Python test runner script. Author: Josh Rosen <joshrosen@databricks.com> Closes #6967 from JoshRosen/run-tests-python-modules and squashes the following commits: f578d6d [Josh Rosen] Fix print for Python 2.x 8233d61 [Josh Rosen] Add python/run-tests.py to Python lint checks 34c98d2 [Josh Rosen] Fix universal_newlines for Python 3 8f65ed0 [Josh Rosen] Fix handling of module in python/run-tests 37aff00 [Josh Rosen] Python 3 fix 27a389f [Josh Rosen] Skip MLLib tests for PyPy c364ccf [Josh Rosen] Use which() to convert PYSPARK_PYTHON to an absolute path before shelling out to run tests 568a3fd [Josh Rosen] Fix hashbang 3b852ae [Josh Rosen] Fall back to PYSPARK_PYTHON when sys.executable is None (fixes a test) f53db55 [Josh Rosen] Remove python2 flag, since the test runner script also works fine under Python 3 9c80469 [Josh Rosen] Fix passing of PYSPARK_PYTHON d33e525 [Josh Rosen] Merge remote-tracking branch 'origin/master' into run-tests-python-modules 4f8902c [Josh Rosen] Python lint fixes. 8f3244c [Josh Rosen] Use universal_newlines to fix dev/run-tests doctest failures on Python 3. f542ac5 [Josh Rosen] Fix lint check for Python 3 fff4d09 [Josh Rosen] Add dev/sparktestsupport to pep8 checks 2efd594 [Josh Rosen] Update dev/run-tests to use new Python test runner flags b2ab027 [Josh Rosen] Add command-line options for running individual suites in python/run-tests caeb040 [Josh Rosen] Fixes to PySpark test module definitions d6a77d3 [Josh Rosen] Fix the tests of dev/run-tests def2d8a [Josh Rosen] Two minor fixes aec0b8f [Josh Rosen] Actually get the Kafka stuff to run properly 04015b9 [Josh Rosen] First attempt at getting PySpark Kafka test to work in new runner script 4c97136 [Josh Rosen] PYTHONPATH fixes dcc9c09 [Josh Rosen] Fix time division 32660fc [Josh Rosen] Initial cut at Python test runner refactoring 311c6a9 [Josh Rosen] Move shell utility functions to own module. 1bdeb87 [Josh Rosen] Move module definitions to separate file.
* [SPARK-8202] [PYSPARK] fix infinite loop during external sort in PySparkDavies Liu2015-06-181-1/+4
| | | | | | | | | | | | | | | | | The batch size during external sort will grow up to max 10000, then shrink down to zero, causing infinite loop. Given the assumption that the items usually have similar size, so we don't need to adjust the batch size after first spill. cc JoshRosen rxin angelini Author: Davies Liu <davies@databricks.com> Closes #6714 from davies/batch_size and squashes the following commits: b170dfb [Davies Liu] update test b9be832 [Davies Liu] Merge branch 'batch_size' of github.com:davies/spark into batch_size 6ade745 [Davies Liu] update test 5c21777 [Davies Liu] Update shuffle.py e746aec [Davies Liu] fix batch size during sort
* [SPARK-8373] [PYSPARK] Add emptyRDD to pyspark and fix the issue when ↵zsxwing2015-06-171-0/+8
| | | | | | | | | | | | | calling sum on an empty RDD This PR fixes the sum issue and also adds `emptyRDD` so that it's easy to create a test case. Author: zsxwing <zsxwing@gmail.com> Closes #6826 from zsxwing/python-emptyRDD and squashes the following commits: b36993f [zsxwing] Update the return type to JavaRDD[T] 71df047 [zsxwing] Add emptyRDD to pyspark and fix the issue when calling sum on an empty RDD
* [SPARK-7711] Add a startTime property to match the corresponding one in ScalaHolden Karau2015-05-211-0/+4
| | | | | | | | | | Author: Holden Karau <holden@pigscanfly.ca> Closes #6275 from holdenk/SPARK-771-startTime-is-missing-from-pyspark and squashes the following commits: 06662dc [Holden Karau] add mising blank line for style checks 7a87410 [Holden Karau] add back missing newline 7a7876b [Holden Karau] Add a startTime property to match the corresponding one in the Scala SparkContext
* [SPARK-7150] SparkContext.range() and SQLContext.range()Daoyuan Wang2015-05-181-0/+5
| | | | | | | | | | | | | | | | | | | | | | This PR is based on #6081, thanks adrian-wang. Closes #6081 Author: Daoyuan Wang <daoyuan.wang@intel.com> Author: Davies Liu <davies@databricks.com> Closes #6230 from davies/range and squashes the following commits: d3ce5fe [Davies Liu] add tests 789eda5 [Davies Liu] add range() in Python 4590208 [Davies Liu] Merge commit 'refs/pull/6081/head' of github.com:apache/spark into range cbf5200 [Daoyuan Wang] let's add python support in a separate PR f45e3b2 [Daoyuan Wang] remove redundant toLong 617da76 [Daoyuan Wang] fix safe marge for corner cases 867c417 [Daoyuan Wang] fix 13dbe84 [Daoyuan Wang] update bd998ba [Daoyuan Wang] update comments d3a0c1b [Daoyuan Wang] add range api()
* [SPARK-6216] [PYSPARK] check python version of worker with driverDavies Liu2015-05-181-3/+3
| | | | | | | | | | | | This PR revert #5404, change to pass the version of python in driver into JVM, check it in worker before deserializing closure, then it can works with different major version of Python. Author: Davies Liu <davies@databricks.com> Closes #6203 from davies/py_version and squashes the following commits: b8fb76e [Davies Liu] fix test 6ce5096 [Davies Liu] use string for version 47c6278 [Davies Liu] check python version of worker with driver
* [SPARK-7438] [SPARK CORE] Fixed validation of relativeSD in countApproxDistinctVinod K C2015-05-091-1/+0
| | | | | | | | | | | | Author: Vinod K C <vinod.kc@huawei.com> Closes #5974 from vinodkc/fix_countApproxDistinct_Validation and squashes the following commits: 3a3d59c [Vinod K C] Reverted removal of validation relativeSD<0.000017 799976e [Vinod K C] Removed testcase to assert IAE when relativeSD>3.7 8ddbfae [Vinod K C] Remove blank line b1b00a3 [Vinod K C] Removed relativeSD validation from python API,RDD.scala will do validation 122d378 [Vinod K C] Fixed validation of relativeSD in countApproxDistinct
* [SPARK-6953] [PySpark] speed up python testsReynold Xin2015-04-211-35/+61
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR try to speed up some python tests: ``` tests.py 144s -> 103s -41s mllib/classification.py 24s -> 17s -7s mllib/regression.py 27s -> 15s -12s mllib/tree.py 27s -> 13s -14s mllib/tests.py 64s -> 31s -33s streaming/tests.py 185s -> 84s -101s ``` Considering python3, the total saving will be 558s (almost 10 minutes) (core, and streaming run three times, mllib runs twice). During testing, it will show used time for each test file: ``` Run core tests ... Running test: pyspark/rdd.py ... ok (22s) Running test: pyspark/context.py ... ok (16s) Running test: pyspark/conf.py ... ok (4s) Running test: pyspark/broadcast.py ... ok (4s) Running test: pyspark/accumulators.py ... ok (4s) Running test: pyspark/serializers.py ... ok (6s) Running test: pyspark/profiler.py ... ok (5s) Running test: pyspark/shuffle.py ... ok (1s) Running test: pyspark/tests.py ... ok (103s) 144s ``` Author: Reynold Xin <rxin@databricks.com> Author: Xiangrui Meng <meng@databricks.com> Closes #5605 from rxin/python-tests-speed and squashes the following commits: d08542d [Reynold Xin] Merge pull request #14 from mengxr/SPARK-6953 89321ee [Xiangrui Meng] fix seed in tests 3ad2387 [Reynold Xin] Merge pull request #5427 from davies/python_tests
* [SPARK-4897] [PySpark] Python 3 supportDavies Liu2015-04-161-152/+175
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR update PySpark to support Python 3 (tested with 3.4). Known issue: unpickle array from Pyrolite is broken in Python 3, those tests are skipped. TODO: ec2/spark-ec2.py is not fully tested with python3. Author: Davies Liu <davies@databricks.com> Author: twneale <twneale@gmail.com> Author: Josh Rosen <joshrosen@databricks.com> Closes #5173 from davies/python3 and squashes the following commits: d7d6323 [Davies Liu] fix tests 6c52a98 [Davies Liu] fix mllib test 99e334f [Davies Liu] update timeout b716610 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 cafd5ec [Davies Liu] adddress comments from @mengxr bf225d7 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 179fc8d [Davies Liu] tuning flaky tests 8c8b957 [Davies Liu] fix ResourceWarning in Python 3 5c57c95 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 4006829 [Davies Liu] fix test 2fc0066 [Davies Liu] add python3 path 71535e9 [Davies Liu] fix xrange and divide 5a55ab4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 125f12c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 ed498c8 [Davies Liu] fix compatibility with python 3 820e649 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 e8ce8c9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 ad7c374 [Davies Liu] fix mllib test and warning ef1fc2f [Davies Liu] fix tests 4eee14a [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 20112ff [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 59bb492 [Davies Liu] fix tests 1da268c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 ca0fdd3 [Davies Liu] fix code style 9563a15 [Davies Liu] add imap back for python 2 0b1ec04 [Davies Liu] make python examples work with Python 3 d2fd566 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 a716d34 [Davies Liu] test with python 3.4 f1700e8 [Davies Liu] fix test in python3 671b1db [Davies Liu] fix test in python3 692ff47 [Davies Liu] fix flaky test 7b9699f [Davies Liu] invalidate import cache for Python 3.3+ 9c58497 [Davies Liu] fix kill worker 309bfbf [Davies Liu] keep compatibility 5707476 [Davies Liu] cleanup, fix hash of string in 3.3+ 8662d5b [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3 f53e1f0 [Davies Liu] fix tests 70b6b73 [Davies Liu] compile ec2/spark_ec2.py in python 3 a39167e [Davies Liu] support customize class in __main__ 814c77b [Davies Liu] run unittests with python 3 7f4476e [Davies Liu] mllib tests passed d737924 [Davies Liu] pass ml tests 375ea17 [Davies Liu] SQL tests pass 6cc42a9 [Davies Liu] rename 431a8de [Davies Liu] streaming tests pass 78901a7 [Davies Liu] fix hash of serializer in Python 3 24b2f2e [Davies Liu] pass all RDD tests 35f48fe [Davies Liu] run future again 1eebac2 [Davies Liu] fix conflict in ec2/spark_ec2.py 6e3c21d [Davies Liu] make cloudpickle work with Python3 2fb2db3 [Josh Rosen] Guard more changes behind sys.version; still doesn't run 1aa5e8f [twneale] Turned out `pickle.DictionaryType is dict` == True, so swapped it out 7354371 [twneale] buffer --> memoryview I'm not super sure if this a valid change, but the 2.7 docs recommend using memoryview over buffer where possible, so hoping it'll work. b69ccdf [twneale] Uses the pure python pickle._Pickler instead of c-extension _pickle.Pickler. It appears pyspark 2.7 uses the pure python pickler as well, so this shouldn't degrade pickling performance (?). f40d925 [twneale] xrange --> range e104215 [twneale] Replaces 2.7 types.InstsanceType with 3.4 `object`....could be horribly wrong depending on how types.InstanceType is used elsewhere in the package--see http://bugs.python.org/issue8206 79de9d0 [twneale] Replaces python2.7 `file` with 3.4 _io.TextIOWrapper 2adb42d [Josh Rosen] Fix up some import differences between Python 2 and 3 854be27 [Josh Rosen] Run `futurize` on Python code: 7c5b4ce [Josh Rosen] Remove Python 3 check in shell.py.
* [SPARK-6886] [PySpark] fix big closure with shuffleDavies Liu2015-04-151-4/+2
| | | | | | | | | | | | | | Currently, the created broadcast object will have same life cycle as RDD in Python. For multistage jobs, an PythonRDD will be created in JVM and the RDD in Python may be GCed, then the broadcast will be destroyed in JVM before the PythonRDD. This PR change to use PythonRDD to track the lifecycle of the broadcast object. It also have a refactor about getNumPartitions() to avoid unnecessary creation of PythonRDD, which could be heavy. cc JoshRosen Author: Davies Liu <davies@databricks.com> Closes #5496 from davies/big_closure and squashes the following commits: 9a0ea4c [Davies Liu] fix big closure with shuffle
* [SPARK-6216] [PySpark] check the python version in workerDavies Liu2015-04-101-0/+16
| | | | | | | | | Author: Davies Liu <davies@databricks.com> Closes #5404 from davies/check_version and squashes the following commits: e559248 [Davies Liu] add tests ec33b5f [Davies Liu] check the python version in worker
* [SPARK-5969][PySpark] Fix descending pyspark.rdd.sortByKey.Milan Straka2015-04-101-0/+11
| | | | | | | | | | | | | | | | The samples should always be sorted in ascending order, because bisect.bisect_left is used on it. The reverse order of the result is already achieved in rangePartitioner by reversing the found index. The current implementation also work, but always uses only two partitions -- the first one and the last one (because the bisect_left return returns either "beginning" or "end" for a descending sequence). Author: Milan Straka <fox@ucw.cz> This patch had conflicts when merged, resolved by Committer: Josh Rosen <joshrosen@databricks.com> Closes #4761 from foxik/fix-descending-sort and squashes the following commits: 95896b5 [Milan Straka] Add regression test for SPARK-5969. 5757490 [Milan Straka] Fix descending pyspark.rdd.sortByKey.
* [SPARK-3074] [PySpark] support groupByKey() with single huge keyDavies Liu2015-04-091-4/+46
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch change groupByKey() to use external sort based approach, so it can support single huge key. For example, it can group by a dataset including one hot key with 40 millions values (strings), using 500M memory for Python worker, finished in about 2 minutes. (it will need 6G memory in hash based approach). During groupByKey(), it will do in-memory groupBy first. If the dataset can not fit in memory, then data will be partitioned by hash. If one partition still can not fit in memory, it will switch to sort based groupBy(). Author: Davies Liu <davies.liu@gmail.com> Author: Davies Liu <davies@databricks.com> Closes #1977 from davies/groupby and squashes the following commits: af3713a [Davies Liu] make sure it's iterator 67772dd [Davies Liu] fix tests e78c15c [Davies Liu] address comments 0b0fde8 [Davies Liu] address comments 0dcf320 [Davies Liu] address comments, rollback changes in ResultIterable e3b8eab [Davies Liu] fix narrow dependency 2a1857a [Davies Liu] typo d2f053b [Davies Liu] add repr for FlattedValuesSerializer c6a2f8d [Davies Liu] address comments 9e2df24 [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby 2b9c261 [Davies Liu] fix typo in comments 70aadcd [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby a14b4bd [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby ab5515b [Davies Liu] Merge branch 'master' into groupby 651f891 [Davies Liu] simplify GroupByKey 1578f2e [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby 1f69f93 [Davies Liu] fix tests 0d3395f [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby 341f1e0 [Davies Liu] add comments, refactor 47918b8 [Davies Liu] remove unused code 6540948 [Davies Liu] address comments: 17f4ec6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into groupby 4d4bc86 [Davies Liu] bugfix 8ef965e [Davies Liu] Merge branch 'master' into groupby fbc504a [Davies Liu] Merge branch 'master' into groupby 779ed03 [Davies Liu] fix merge conflict 2c1d05b [Davies Liu] refactor, minor turning b48cda5 [Davies Liu] Merge branch 'master' into groupby 85138e6 [Davies Liu] Merge branch 'master' into groupby acd8e1b [Davies Liu] fix memory when groupByKey().count() 905b233 [Davies Liu] Merge branch 'sort' into groupby 1f075ed [Davies Liu] Merge branch 'master' into sort 4b07d39 [Davies Liu] compress the data while spilling 0a081c6 [Davies Liu] Merge branch 'master' into groupby f157fe7 [Davies Liu] Merge branch 'sort' into groupby eb53ca6 [Davies Liu] Merge branch 'master' into sort b2dc3bf [Davies Liu] Merge branch 'sort' into groupby 644abaf [Davies Liu] add license in LICENSE 19f7873 [Davies Liu] improve tests 11ba318 [Davies Liu] typo 085aef8 [Davies Liu] Merge branch 'master' into groupby 3ee58e5 [Davies Liu] switch to sort based groupBy, based on size of data 1ea0669 [Davies Liu] choose sort based groupByKey() automatically b40bae7 [Davies Liu] bugfix efa23df [Davies Liu] refactor, add spark.shuffle.sort=False 250be4e [Davies Liu] flatten the combined values when dumping into disks d05060d [Davies Liu] group the same key before shuffle, reduce the comparison during sorting 083d842 [Davies Liu] sorted based groupByKey() 55602ee [Davies Liu] use external sort in sortBy() and sortByKey()
* [SPARK-6294] fix hang when call take() in JVM on PythonRDDDavies Liu2015-03-121-0/+5
| | | | | | | | | | | | | | The Thread.interrupt() can not terminate the thread in some cases, so we should not wait for the writerThread of PythonRDD. This PR also ignore some exception during clean up. cc JoshRosen mengxr Author: Davies Liu <davies@databricks.com> Closes #4987 from davies/fix_take and squashes the following commits: 4488f1a [Davies Liu] fix hang when call take() in JVM on PythonRDD
* [SPARK-5973] [PySpark] fix zip with two RDDs with AutoBatchedSerializerDavies Liu2015-02-241-0/+6
| | | | | | | | | | Author: Davies Liu <davies@databricks.com> Closes #4745 from davies/fix_zip and squashes the following commits: 2124b2c [Davies Liu] Update tests.py b5c828f [Davies Liu] increase the number of records c1e40fd [Davies Liu] fix zip with two RDDs with AutoBatchedSerializer
* [SPARK-5811] Added documentation for maven coordinates and added Spark ↵Burak Yavuz2015-02-171-4/+65
| | | | | | | | | | | | | | | | | | | | | | | Packages support Documentation for maven coordinates + Spark Package support. Added pyspark tests for `--packages` Author: Burak Yavuz <brkyvz@gmail.com> Author: Davies Liu <davies@databricks.com> Closes #4662 from brkyvz/SPARK-5811 and squashes the following commits: 56ccccd [Burak Yavuz] fixed broken test 64cb8ee [Burak Yavuz] passed pep8 on local c07b81e [Burak Yavuz] fixed pep8 a8bd6b7 [Burak Yavuz] submit PR 4ef4046 [Burak Yavuz] ready for PR 8fb02e5 [Burak Yavuz] merged master 25c9b9f [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into python-jar 560d13b [Burak Yavuz] before PR 17d3f76 [Davies Liu] support .jar as python package a3eb717 [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into SPARK-5811 c60156d [Burak Yavuz] [SPARK-5811] Added documentation for maven coordinates
* [SPARK-5785] [PySpark] narrow dependency for cogroup/join in PySparkDavies Liu2015-02-171-1/+37
| | | | | | | | | | | | | | | | | | Currently, PySpark does not support narrow dependency during cogroup/join when the two RDDs have the partitioner, another unnecessary shuffle stage will come in. The Python implementation of cogroup/join is different than Scala one, it depends on union() and partitionBy(). This patch will try to use PartitionerAwareUnionRDD() in union(), when all the RDDs have the same partitioner. It also fix `reservePartitioner` in all the map() or mapPartitions(), then partitionBy() can skip the unnecessary shuffle stage. Author: Davies Liu <davies@databricks.com> Closes #4629 from davies/narrow and squashes the following commits: dffe34e [Davies Liu] improve test, check number of stages for join/cogroup 1ed3ba2 [Davies Liu] Merge branch 'master' of github.com:apache/spark into narrow 4d29932 [Davies Liu] address comment cc28d97 [Davies Liu] add unit tests 940245e [Davies Liu] address comments ff5a0a6 [Davies Liu] skip the partitionBy() on Python side eb26c62 [Davies Liu] narrow dependency in PySpark
* [SPARK-4172] [PySpark] Progress API in PythonDavies Liu2015-02-171-0/+31
| | | | | | | | | | | | | | | | | This patch bring the pull based progress API into Python, also a example in Python. Author: Davies Liu <davies@databricks.com> Closes #3027 from davies/progress_api and squashes the following commits: b1ba984 [Davies Liu] fix style d3b9253 [Davies Liu] add tests, mute the exception after stop 4297327 [Davies Liu] Merge branch 'master' of github.com:apache/spark into progress_api 969fa9d [Davies Liu] Merge branch 'master' of github.com:apache/spark into progress_api 25590c9 [Davies Liu] update with Java API 360de2d [Davies Liu] Merge branch 'master' of github.com:apache/spark into progress_api c0f1021 [Davies Liu] Merge branch 'master' of github.com:apache/spark into progress_api 023afb3 [Davies Liu] add Python API and example for progress API
* [SPARK-5554] [SQL] [PySpark] add more tests for DataFrame Python APIDavies Liu2015-02-031-261/+0
| | | | | | | | | | | | | | | | | | | Add more tests and docs for DataFrame Python API, improve test coverage, fix bugs. Author: Davies Liu <davies@databricks.com> Closes #4331 from davies/fix_df and squashes the following commits: dd9919f [Davies Liu] fix tests 467332c [Davies Liu] support string in cast() 83c92fe [Davies Liu] address comments c052f6f [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_df 8dd19a9 [Davies Liu] fix tests in python 2.6 35ccb9f [Davies Liu] fix build 78ebcfa [Davies Liu] add sql_test.py in run_tests 9ab78b4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_df 6040ba7 [Davies Liu] fix docs 3ab2661 [Davies Liu] add more tests for DataFrame
* [SPARK-5154] [PySpark] [Streaming] Kafka streaming support in PythonDavies Liu2015-02-021-1/+9
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR brings the Python API for Spark Streaming Kafka data source. ``` class KafkaUtils(__builtin__.object) | Static methods defined here: | | createStream(ssc, zkQuorum, groupId, topics, storageLevel=StorageLevel(True, True, False, False, 2), keyDecoder=<function utf8_decoder>, valueDecoder=<function utf8_decoder>) | Create an input stream that pulls messages from a Kafka Broker. | | :param ssc: StreamingContext object | :param zkQuorum: Zookeeper quorum (hostname:port,hostname:port,..). | :param groupId: The group id for this consumer. | :param topics: Dict of (topic_name -> numPartitions) to consume. | Each partition is consumed in its own thread. | :param storageLevel: RDD storage level. | :param keyDecoder: A function used to decode key | :param valueDecoder: A function used to decode value | :return: A DStream object ``` run the example: ``` bin/spark-submit --driver-class-path external/kafka-assembly/target/scala-*/spark-streaming-kafka-assembly-*.jar examples/src/main/python/streaming/kafka_wordcount.py localhost:2181 test ``` Author: Davies Liu <davies@databricks.com> Author: Tathagata Das <tdas@databricks.com> Closes #3715 from davies/kafka and squashes the following commits: d93bfe0 [Davies Liu] Update make-distribution.sh 4280d04 [Davies Liu] address comments e6d0427 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka f257071 [Davies Liu] add tests for null in RDD 23b039a [Davies Liu] address comments 9af51c4 [Davies Liu] Merge branch 'kafka' of github.com:davies/spark into kafka a74da87 [Davies Liu] address comments dc1eed0 [Davies Liu] Update kafka_wordcount.py 31e2317 [Davies Liu] Update kafka_wordcount.py 370ba61 [Davies Liu] Update kafka.py 97386b3 [Davies Liu] address comment 2c567a5 [Davies Liu] update logging and comment 33730d1 [Davies Liu] Merge branch 'master' of github.com:apache/spark into kafka adeeb38 [Davies Liu] Merge pull request #3 from tdas/kafka-python-api aea8953 [Tathagata Das] Kafka-assembly for Python API eea16a7 [Davies Liu] refactor f6ce899 [Davies Liu] add example and fix bugs 98c8d17 [Davies Liu] fix python style 5697a01 [Davies Liu] bypass decoder in scala 048dbe6 [Davies Liu] fix python style 75d485e [Davies Liu] add mqtt 07923c4 [Davies Liu] support kafka in Python
* [SQL] Improve DataFrame API error reportingReynold Xin2015-02-021-2/+4
| | | | | | | | | | | | | | | | | | 1. Throw UnsupportedOperationException if a Column is not computable. 2. Perform eager analysis on DataFrame so we can catch errors when they happen (not when an action is run). Author: Reynold Xin <rxin@databricks.com> Author: Davies Liu <davies@databricks.com> Closes #4296 from rxin/col-computability and squashes the following commits: 6527b86 [Reynold Xin] Merge pull request #8 from davies/col-computability fd92bc7 [Reynold Xin] Merge branch 'master' into col-computability f79034c [Davies Liu] fix python tests 5afe1ff [Reynold Xin] Fix scala test. 17f6bae [Reynold Xin] Various fixes. b932e86 [Reynold Xin] Added eager analysis for error reporting. e6f00b8 [Reynold Xin] [SQL][API] ComputableColumn vs IncomputableColumn
* [SPARK-5464] Fix help() for Python DataFrame instancesJosh Rosen2015-01-291-0/+10
| | | | | | | | | | This fixes an exception that prevented users from calling `help()` on Python DataFrame instances. Author: Josh Rosen <joshrosen@databricks.com> Closes #4278 from JoshRosen/SPARK-5464-python-dataframe-help-command and squashes the following commits: 08f95f7 [Josh Rosen] Fix exception when calling help() on Python DataFrame instances
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