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* [SPARK-4387][PySpark] Refactoring python profiling code to make it extensibleYandu Oppacher2015-01-281-15/+0
| | | | | | | | | | | | | | | | | | | | | | | | This PR is based on #3255 , fix conflicts and code style. Closes #3255. Author: Yandu Oppacher <yandu.oppacher@jadedpixel.com> Author: Davies Liu <davies@databricks.com> Closes #3901 from davies/refactor-python-profile-code and squashes the following commits: b4a9306 [Davies Liu] fix tests 4b79ce8 [Davies Liu] add docstring for profiler_cls 2700e47 [Davies Liu] use BasicProfiler as default 349e341 [Davies Liu] more refactor 6a5d4df [Davies Liu] refactor and fix tests 31bf6b6 [Davies Liu] fix code style 0864b5d [Yandu Oppacher] Remove unused method 76a6c37 [Yandu Oppacher] Added a profile collector to accumulate the profilers per stage 9eefc36 [Yandu Oppacher] Fix doc 9ace076 [Yandu Oppacher] Refactor of profiler, and moved tests around 8739aff [Yandu Oppacher] Code review fixes 9bda3ec [Yandu Oppacher] Refactor profiler code
* [SPARK-3478] [PySpark] Profile the Python tasksDavies Liu2014-09-301-0/+15
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch add profiling support for PySpark, it will show the profiling results before the driver exits, here is one example: ``` ============================================================ Profile of RDD<id=3> ============================================================ 5146507 function calls (5146487 primitive calls) in 71.094 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 5144576 68.331 0.000 68.331 0.000 statcounter.py:44(merge) 20 2.735 0.137 71.071 3.554 statcounter.py:33(__init__) 20 0.017 0.001 0.017 0.001 {cPickle.dumps} 1024 0.003 0.000 0.003 0.000 t.py:16(<lambda>) 20 0.001 0.000 0.001 0.000 {reduce} 21 0.001 0.000 0.001 0.000 {cPickle.loads} 20 0.001 0.000 0.001 0.000 copy_reg.py:95(_slotnames) 41 0.001 0.000 0.001 0.000 serializers.py:461(read_int) 40 0.001 0.000 0.002 0.000 serializers.py:179(_batched) 62 0.000 0.000 0.000 0.000 {method 'read' of 'file' objects} 20 0.000 0.000 71.072 3.554 rdd.py:863(<lambda>) 20 0.000 0.000 0.001 0.000 serializers.py:198(load_stream) 40/20 0.000 0.000 71.072 3.554 rdd.py:2093(pipeline_func) 41 0.000 0.000 0.002 0.000 serializers.py:130(load_stream) 40 0.000 0.000 71.072 1.777 rdd.py:304(func) 20 0.000 0.000 71.094 3.555 worker.py:82(process) ``` Also, use can show profile result manually by `sc.show_profiles()` or dump it into disk by `sc.dump_profiles(path)`, such as ```python >>> sc._conf.set("spark.python.profile", "true") >>> rdd = sc.parallelize(range(100)).map(str) >>> rdd.count() 100 >>> sc.show_profiles() ============================================================ Profile of RDD<id=1> ============================================================ 284 function calls (276 primitive calls) in 0.001 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 4 0.000 0.000 0.000 0.000 serializers.py:198(load_stream) 4 0.000 0.000 0.000 0.000 {reduce} 12/4 0.000 0.000 0.001 0.000 rdd.py:2092(pipeline_func) 4 0.000 0.000 0.000 0.000 {cPickle.loads} 4 0.000 0.000 0.000 0.000 {cPickle.dumps} 104 0.000 0.000 0.000 0.000 rdd.py:852(<genexpr>) 8 0.000 0.000 0.000 0.000 serializers.py:461(read_int) 12 0.000 0.000 0.000 0.000 rdd.py:303(func) ``` The profiling is disabled by default, can be enabled by "spark.python.profile=true". Also, users can dump the results into disks automatically for future analysis, by "spark.python.profile.dump=path_to_dump" This is bugfix of #2351 cc JoshRosen Author: Davies Liu <davies.liu@gmail.com> Closes #2556 from davies/profiler and squashes the following commits: e68df5a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 858e74c [Davies Liu] compatitable with python 2.6 7ef2aa0 [Davies Liu] bugfix, add tests for show_profiles and dump_profiles() 2b0daf2 [Davies Liu] fix docs 7a56c24 [Davies Liu] bugfix cba9463 [Davies Liu] move show_profiles and dump_profiles to SparkContext fb9565b [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 116d52a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 09d02c3 [Davies Liu] Merge branch 'master' into profiler c23865c [Davies Liu] Merge branch 'master' into profiler 15d6f18 [Davies Liu] add docs for two configs dadee1a [Davies Liu] add docs string and clear profiles after show or dump 4f8309d [Davies Liu] address comment, add tests 0a5b6eb [Davies Liu] fix Python UDF 4b20494 [Davies Liu] add profile for python
* Revert "[SPARK-3478] [PySpark] Profile the Python tasks"Josh Rosen2014-09-261-15/+0
| | | | This reverts commit 1aa549ba9839565274a12c52fa1075b424f138a6.
* [SPARK-3478] [PySpark] Profile the Python tasksDavies Liu2014-09-261-0/+15
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch add profiling support for PySpark, it will show the profiling results before the driver exits, here is one example: ``` ============================================================ Profile of RDD<id=3> ============================================================ 5146507 function calls (5146487 primitive calls) in 71.094 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 5144576 68.331 0.000 68.331 0.000 statcounter.py:44(merge) 20 2.735 0.137 71.071 3.554 statcounter.py:33(__init__) 20 0.017 0.001 0.017 0.001 {cPickle.dumps} 1024 0.003 0.000 0.003 0.000 t.py:16(<lambda>) 20 0.001 0.000 0.001 0.000 {reduce} 21 0.001 0.000 0.001 0.000 {cPickle.loads} 20 0.001 0.000 0.001 0.000 copy_reg.py:95(_slotnames) 41 0.001 0.000 0.001 0.000 serializers.py:461(read_int) 40 0.001 0.000 0.002 0.000 serializers.py:179(_batched) 62 0.000 0.000 0.000 0.000 {method 'read' of 'file' objects} 20 0.000 0.000 71.072 3.554 rdd.py:863(<lambda>) 20 0.000 0.000 0.001 0.000 serializers.py:198(load_stream) 40/20 0.000 0.000 71.072 3.554 rdd.py:2093(pipeline_func) 41 0.000 0.000 0.002 0.000 serializers.py:130(load_stream) 40 0.000 0.000 71.072 1.777 rdd.py:304(func) 20 0.000 0.000 71.094 3.555 worker.py:82(process) ``` Also, use can show profile result manually by `sc.show_profiles()` or dump it into disk by `sc.dump_profiles(path)`, such as ```python >>> sc._conf.set("spark.python.profile", "true") >>> rdd = sc.parallelize(range(100)).map(str) >>> rdd.count() 100 >>> sc.show_profiles() ============================================================ Profile of RDD<id=1> ============================================================ 284 function calls (276 primitive calls) in 0.001 seconds Ordered by: internal time, cumulative time ncalls tottime percall cumtime percall filename:lineno(function) 4 0.000 0.000 0.000 0.000 serializers.py:198(load_stream) 4 0.000 0.000 0.000 0.000 {reduce} 12/4 0.000 0.000 0.001 0.000 rdd.py:2092(pipeline_func) 4 0.000 0.000 0.000 0.000 {cPickle.loads} 4 0.000 0.000 0.000 0.000 {cPickle.dumps} 104 0.000 0.000 0.000 0.000 rdd.py:852(<genexpr>) 8 0.000 0.000 0.000 0.000 serializers.py:461(read_int) 12 0.000 0.000 0.000 0.000 rdd.py:303(func) ``` The profiling is disabled by default, can be enabled by "spark.python.profile=true". Also, users can dump the results into disks automatically for future analysis, by "spark.python.profile.dump=path_to_dump" Author: Davies Liu <davies.liu@gmail.com> Closes #2351 from davies/profiler and squashes the following commits: 7ef2aa0 [Davies Liu] bugfix, add tests for show_profiles and dump_profiles() 2b0daf2 [Davies Liu] fix docs 7a56c24 [Davies Liu] bugfix cba9463 [Davies Liu] move show_profiles and dump_profiles to SparkContext fb9565b [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 116d52a [Davies Liu] Merge branch 'master' of github.com:apache/spark into profiler 09d02c3 [Davies Liu] Merge branch 'master' into profiler c23865c [Davies Liu] Merge branch 'master' into profiler 15d6f18 [Davies Liu] add docs for two configs dadee1a [Davies Liu] add docs string and clear profiles after show or dump 4f8309d [Davies Liu] address comment, add tests 0a5b6eb [Davies Liu] fix Python UDF 4b20494 [Davies Liu] add profile for python
* [SPARK-3309] [PySpark] Put all public API in __all__Davies Liu2014-09-031-0/+3
| | | | | | | | | | | | | | Put all public API in __all__, also put them all in pyspark.__init__.py, then we can got all the documents for public API by `pydoc pyspark`. It also can be used by other programs (such as Sphinx or Epydoc) to generate only documents for public APIs. Author: Davies Liu <davies.liu@gmail.com> Closes #2205 from davies/public and squashes the following commits: c6c5567 [Davies Liu] fix message f7b35be [Davies Liu] put SchemeRDD, Row in pyspark.sql module 7e3016a [Davies Liu] add __all__ in mllib 6281b48 [Davies Liu] fix doc for SchemaRDD 6caab21 [Davies Liu] add public interfaces into pyspark.__init__.py
* [SPARK-2627] [PySpark] have the build enforce PEP 8 automaticallyNicholas Chammas2014-08-061-0/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | As described in [SPARK-2627](https://issues.apache.org/jira/browse/SPARK-2627), we'd like Python code to automatically be checked for PEP 8 compliance by Jenkins. This pull request aims to do that. Notes: * We may need to install [`pep8`](https://pypi.python.org/pypi/pep8) on the build server. * I'm expecting tests to fail now that PEP 8 compliance is being checked as part of the build. I'm fine with cleaning up any remaining PEP 8 violations as part of this pull request. * I did not understand why the RAT and scalastyle reports are saved to text files. I did the same for the PEP 8 check, but only so that the console output style can match those for the RAT and scalastyle checks. The PEP 8 report is removed right after the check is complete. * Updates to the ["Contributing to Spark"](https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark) guide will be submitted elsewhere, as I don't believe that text is part of the Spark repo. Author: Nicholas Chammas <nicholas.chammas@gmail.com> Author: nchammas <nicholas.chammas@gmail.com> Closes #1744 from nchammas/master and squashes the following commits: 274b238 [Nicholas Chammas] [SPARK-2627] [PySpark] minor indentation changes 983d963 [nchammas] Merge pull request #5 from apache/master 1db5314 [nchammas] Merge pull request #4 from apache/master 0e0245f [Nicholas Chammas] [SPARK-2627] undo erroneous whitespace fixes bf30942 [Nicholas Chammas] [SPARK-2627] PEP8: comment spacing 6db9a44 [nchammas] Merge pull request #3 from apache/master 7b4750e [Nicholas Chammas] merge upstream changes 91b7584 [Nicholas Chammas] [SPARK-2627] undo unnecessary line breaks 44e3e56 [Nicholas Chammas] [SPARK-2627] use tox.ini to exclude files b09fae2 [Nicholas Chammas] don't wrap comments unnecessarily bfb9f9f [Nicholas Chammas] [SPARK-2627] keep up with the PEP 8 fixes 9da347f [nchammas] Merge pull request #2 from apache/master aa5b4b5 [Nicholas Chammas] [SPARK-2627] follow Spark bash style for if blocks d0a83b9 [Nicholas Chammas] [SPARK-2627] check that pep8 downloaded fine dffb5dd [Nicholas Chammas] [SPARK-2627] download pep8 at runtime a1ce7ae [Nicholas Chammas] [SPARK-2627] space out test report sections 21da538 [Nicholas Chammas] [SPARK-2627] it's PEP 8, not PEP8 6f4900b [Nicholas Chammas] [SPARK-2627] more misc PEP 8 fixes fe57ed0 [Nicholas Chammas] removing merge conflict backups 9c01d4c [nchammas] Merge pull request #1 from apache/master 9a66cb0 [Nicholas Chammas] resolving merge conflicts a31ccc4 [Nicholas Chammas] [SPARK-2627] miscellaneous PEP 8 fixes beaa9ac [Nicholas Chammas] [SPARK-2627] fail check on non-zero status 723ed39 [Nicholas Chammas] always delete the report file 0541ebb [Nicholas Chammas] [SPARK-2627] call Python linter from run-tests 12440fa [Nicholas Chammas] [SPARK-2627] add Scala linter 61c07b9 [Nicholas Chammas] [SPARK-2627] add Python linter 75ad552 [Nicholas Chammas] make check output style consistent
* SPARK-2282: Reuse Socket for sending accumulator updates to PysparkAaron Davidson2014-07-311-7/+27
| | | | | | | | | | | | | | | | Prior to this change, every PySpark task completion opened a new socket to the accumulator server, passed its updates through, and then quit. I'm not entirely sure why PySpark always sends accumulator updates, but regardless this causes a very rapid buildup of ephemeral TCP connections that remain in the TCP_WAIT state for around a minute before being cleaned up. Rather than trying to allow these sockets to be cleaned up faster, this patch simply reuses the connection between tasks completions (since they're fed updates in a single-threaded manner by the DAGScheduler anyway). The only tricky part here was making sure that the AccumulatorServer was able to shutdown in a timely manner (i.e., stop polling for new data), and this was accomplished via minor feats of magic. I have confirmed that this patch eliminates the buildup of ephemeral sockets due to the accumulator updates. However, I did note that there were still significant sockets being created against the PySpark daemon port, but my machine was not able to create enough sockets fast enough to fail. This may not be the last time we've seen this issue, though. Author: Aaron Davidson <aaron@databricks.com> Closes #1503 from aarondav/accum and squashes the following commits: b3e12f7 [Aaron Davidson] SPARK-2282: Reuse Socket for sending accumulator updates to Pyspark
* Add custom serializer support to PySpark.Josh Rosen2013-11-101-2/+4
| | | | | | | | | For now, this only adds MarshalSerializer, but it lays the groundwork for other supporting custom serializers. Many of these mechanisms can also be used to support deserialization of different data formats sent by Java, such as data encoded by MsgPack. This also fixes a bug in SparkContext.union().
* Add an add() method to pyspark accumulators.Ewen Cheslack-Postava2013-10-191-1/+12
| | | | | | | | | | | | | | | | | | | | | | | | Add a regular method for adding a term to accumulators in pyspark. Currently if you have a non-global accumulator, adding to it is awkward. The += operator can't be used for non-global accumulators captured via closure because it's involves an assignment. The only way to do it is using __iadd__ directly. Adding this method lets you write code like this: def main(): sc = SparkContext() accum = sc.accumulator(0) rdd = sc.parallelize([1,2,3]) def f(x): accum.add(x) rdd.foreach(f) print accum.value where using accum += x instead would have caused UnboundLocalError exceptions in workers. Currently it would have to be written as accum.__iadd__(x).
* Add Apache license headers and LICENSE and NOTICE filesMatei Zaharia2013-07-161-0/+17
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* Remove unnecessary doctest __main__ methods.Josh Rosen2013-02-031-9/+0
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* Remove use of abc.ABCMeta due to cloudpickle issue.Josh Rosen2013-01-231-7/+4
| | | | | | | | | cloudpickle runs into issues while pickling subclasses of AccumulatorParam, which may be related to this Python issue: http://bugs.python.org/issue7689 This seems hard to fix and the ABCMeta wasn't necessary, so I removed it.
* Make AccumulatorParam an abstract base class.Josh Rosen2013-01-211-3/+26
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* Add __repr__ to Accumulator; fix bug in sc.accumulatorJosh Rosen2013-01-201-1/+10
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* Add a class comment to AccumulatorMatei Zaharia2013-01-201-0/+12
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* Added accumulators to PySparkMatei Zaharia2013-01-201-0/+166
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