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* [SPARK-6294] [PySpark] fix take of PythonRDD in JVM (branch 1.2)Davies 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 mengxr Author: Davies Liu <davies@databricks.com> Closes #5003 from davies/fix_take2 and squashes the following commits: 2f2f893 [Davies Liu] fix take of PythonRDD in JVM
* [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 (cherry picked from commit da505e59274d1c838653c1109db65ad374e65304) Signed-off-by: Joseph K. Bradley <joseph@databricks.com>
* [SPARK-5722] [SQL] [PySpark] infer int as LongType in Python (for 1.2 branch)Davies Liu2015-02-231-1/+22
| | | | | | | | | | | | | | This PR change to use LongType for int in Python, when inferSchema(), because IntegerType in SQL is not enough for int in Python (which is 64-bit on 64-bit machines). Closes #4521 cc dondrake marmbrus Author: Davies Liu <davies@databricks.com> Closes #4681 from davies/long2 and squashes the following commits: 05ef1c8 [Davies Liu] infer LongType for int in Python
* [SPARK-5361]Multiple Java RDD <-> Python RDD conversions not working correctlyWinston Chen2015-02-161-0/+19
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This is found through reading RDD from `sc.newAPIHadoopRDD` and writing it back using `rdd.saveAsNewAPIHadoopFile` in pyspark. It turns out that whenever there are multiple RDD conversions from JavaRDD to PythonRDD then back to JavaRDD, the exception below happens: ``` 15/01/16 10:28:31 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 7) java.lang.ClassCastException: [Ljava.lang.Object; cannot be cast to java.util.ArrayList at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:157) at org.apache.spark.api.python.SerDeUtil$$anonfun$pythonToJava$1$$anonfun$apply$1.apply(SerDeUtil.scala:153) at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308) ``` The test case code below reproduces it: ``` from pyspark.rdd import RDD dl = [ (u'2', {u'director': u'David Lean'}), (u'7', {u'director': u'Andrew Dominik'}) ] dl_rdd = sc.parallelize(dl) tmp = dl_rdd._to_java_object_rdd() tmp2 = sc._jvm.SerDe.javaToPython(tmp) t = RDD(tmp2, sc) t.count() tmp = t._to_java_object_rdd() tmp2 = sc._jvm.SerDe.javaToPython(tmp) t = RDD(tmp2, sc) t.count() # it blows up here during the 2nd time of conversion ``` Author: Winston Chen <wchen@quid.com> Closes #4146 from wingchen/master and squashes the following commits: 903df7d [Winston Chen] SPARK-5361, update to toSeq based on the PR 5d90a83 [Winston Chen] SPARK-5361, make python pretty, so to pass PEP 8 checks 126be6b [Winston Chen] SPARK-5361, add in test case 4cf1187 [Winston Chen] SPARK-5361, add in test case 9f1a097 [Winston Chen] add in tuple handling while converting form python RDD back to JavaRDD (cherry picked from commit 453d7999b88be87bda30d9e73038eb484ee063bd) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
* [SPARK-4841] fix zip with textFile()Davies Liu2014-12-171-0/+9
| | | | | | | | | | | | | | | | | UTF8Deserializer can not be used in BatchedSerializer, so always use PickleSerializer() when change batchSize in zip(). Also, if two RDD have the same batch size already, they did not need re-serialize any more. Author: Davies Liu <davies@databricks.com> Closes #3706 from davies/fix_4841 and squashes the following commits: 20ce3a3 [Davies Liu] fix bug in _reserialize() e3ebf7c [Davies Liu] add comment 379d2c8 [Davies Liu] fix zip with textFile() (cherry picked from commit c246b95dd2f565043db429c38c6cc029a0b870c1) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
* [SPARK-4548] []SPARK-4517] improve performance of python broadcastDavies Liu2014-11-241-14/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Re-implement the Python broadcast using file: 1) serialize the python object using cPickle, write into disks. 2) Create a wrapper in JVM (for the dumped file), it read data from during serialization 3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors 4) During deserialization, writing the data into disk. 5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access. It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor). Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2): name | 1.1 | 1.2 with this patch | improvement ---------|--------|---------|-------- python-broadcast-w-bytes | 25.20 | 9.33 | 170.13% | python-broadcast-w-set | 4.13 | 4.50 | -8.35% | Testing with 100 tasks (16 CPUs): name | 1.1 | 1.2 with this patch | improvement ---------|--------|---------|-------- python-broadcast-w-bytes | 38.16 | 8.40 | 353.98% python-broadcast-w-set | 23.29 | 9.59 | 142.80% Author: Davies Liu <davies@databricks.com> Closes #3417 from davies/pybroadcast and squashes the following commits: 50a58e0 [Davies Liu] address comments b98de1d [Davies Liu] disable gc while unpickle e5ee6b9 [Davies Liu] support large string 09303b8 [Davies Liu] read all data into memory dde02dd [Davies Liu] improve performance of python broadcast (cherry picked from commit 6cf507685efd01df77d663145ae08e48c7f92948) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
* [SPARK-4578] fix asDict() with nested Row()Davies Liu2014-11-241-3/+4
| | | | | | | | | | | | | The Row object is created on the fly once the field is accessed, so we should access them by getattr() in asDict(0 Author: Davies Liu <davies@databricks.com> Closes #3434 from davies/fix_asDict and squashes the following commits: b20f1e7 [Davies Liu] fix asDict() with nested Row() (cherry picked from commit 050616b408c60eae02256913ceb645912dbff62e) Signed-off-by: Patrick Wendell <pwendell@gmail.com>
* [SPARK-3721] [PySpark] broadcast objects larger than 2GDavies Liu2014-11-181-2/+50
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch will bring support for broadcasting objects larger than 2G. pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]]. Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf. Author: Davies Liu <davies@databricks.com> Author: Davies Liu <davies.liu@gmail.com> Closes #2659 from davies/huge and squashes the following commits: 7b57a14 [Davies Liu] add more tests for broadcast 28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge a2f6a02 [Davies Liu] bug fix 4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 5875c73 [Davies Liu] address comments 10a349b [Davies Liu] address comments 0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 6182c8f [Davies Liu] Merge branch 'master' into huge d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 2514848 [Davies Liu] address comments fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 1c2d928 [Davies Liu] fix scala style 091b107 [Davies Liu] broadcast objects larger than 2G (cherry picked from commit 4a377aff2d36b64a65b54192a987aba44b8f78e0) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
* [SPARK-4304] [PySpark] Fix sort on empty RDDDavies Liu2014-11-071-0/+3
| | | | | | | | | | | | | | | | This PR fix sortBy()/sortByKey() on empty RDD. This should be back ported into 1.1/1.2 Author: Davies Liu <davies@databricks.com> Closes #3162 from davies/fix_sort and squashes the following commits: 84f64b7 [Davies Liu] add tests 52995b5 [Davies Liu] fix sortByKey() on empty RDD (cherry picked from commit 7779109796c90d789464ab0be35917f963bbe867) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
* [SPARK-4186] add binaryFiles and binaryRecords in PythonDavies Liu2014-11-061-0/+19
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | add binaryFiles() and binaryRecords() in Python ``` binaryFiles(self, path, minPartitions=None): :: Developer API :: Read a directory of binary files from HDFS, a local file system (available on all nodes), or any Hadoop-supported file system URI as a byte array. Each file is read as a single record and returned in a key-value pair, where the key is the path of each file, the value is the content of each file. Note: Small files are preferred, large file is also allowable, but may cause bad performance. binaryRecords(self, path, recordLength): Load data from a flat binary file, assuming each record is a set of numbers with the specified numerical format (see ByteBuffer), and the number of bytes per record is constant. :param path: Directory to the input data files :param recordLength: The length at which to split the records ``` Author: Davies Liu <davies@databricks.com> Closes #3078 from davies/binary and squashes the following commits: cd0bdbd [Davies Liu] Merge branch 'master' of github.com:apache/spark into binary 3aa349b [Davies Liu] add experimental notes 24e84b6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into binary 5ceaa8a [Davies Liu] Merge branch 'master' of github.com:apache/spark into binary 1900085 [Davies Liu] bugfix bb22442 [Davies Liu] add binaryFiles and binaryRecords in Python (cherry picked from commit b41a39e24038876359aeb7ce2bbbb4de2234e5f3) Signed-off-by: Matei Zaharia <matei@databricks.com>
* [SPARK-3886] [PySpark] simplify serializer, use AutoBatchedSerializer by ↵Davies Liu2014-11-031-54/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | default. This PR simplify serializer, always use batched serializer (AutoBatchedSerializer as default), even batch size is 1. Author: Davies Liu <davies@databricks.com> This patch had conflicts when merged, resolved by Committer: Josh Rosen <joshrosen@databricks.com> Closes #2920 from davies/fix_autobatch and squashes the following commits: e544ef9 [Davies Liu] revert unrelated change 6880b14 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 1d557fc [Davies Liu] fix tests 8180907 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 76abdce [Davies Liu] clean up 53fa60b [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch d7ac751 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 2cc2497 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch b4292ce [Davies Liu] fix bug in master d79744c [Davies Liu] recover hive tests be37ece [Davies Liu] refactor eb3938d [Davies Liu] refactor serializer in scala 8d77ef2 [Davies Liu] simplify serializer, use AutoBatchedSerializer by default. (cherry picked from commit e4f42631a68b473ce706429915f3f08042af2119) Signed-off-by: Josh Rosen <joshrosen@databricks.com>
* [SPARK-4192][SQL] Internal API for Python UDTXiangrui Meng2014-11-031-1/+92
| | | | | | | | | | | | | | | | | | | | | | | | Following #2919, this PR adds Python UDT (for internal use only) with tests under "pyspark.tests". Before `SQLContext.applySchema`, we check whether we need to convert user-type instances into SQL recognizable data. In the current implementation, a Python UDT must be paired with a Scala UDT for serialization on the JVM side. A following PR will add VectorUDT in MLlib for both Scala and Python. marmbrus jkbradley davies Author: Xiangrui Meng <meng@databricks.com> Closes #3068 from mengxr/SPARK-4192-sql and squashes the following commits: acff637 [Xiangrui Meng] merge master dba5ea7 [Xiangrui Meng] only use pyClass for Python UDT output sqlType as well 2c9d7e4 [Xiangrui Meng] move import to global setup; update needsConversion 7c4a6a9 [Xiangrui Meng] address comments 75223db [Xiangrui Meng] minor update f740379 [Xiangrui Meng] remove UDT from default imports e98d9d0 [Xiangrui Meng] fix py style 4e84fce [Xiangrui Meng] remove local hive tests and add more tests 39f19e0 [Xiangrui Meng] add tests b7f666d [Xiangrui Meng] add Python UDT (cherry picked from commit 04450d11548cfb25d4fb77d4a33e3a7cd4254183) Signed-off-by: Xiangrui Meng <meng@databricks.com>
* [SPARK-3594] [PySpark] [SQL] take more rows to infer schema or samplingDavies Liu2014-11-031-0/+19
| | | | | | | | | | | | | | | | | | | | | | | | | | | This patch will try to infer schema for RDD which has empty value (None, [], {}) in the first row. It will try first 100 rows and merge the types into schema, also merge fields of StructType together. If there is still NullType in schema, then it will show an warning, tell user to try with sampling. If sampling is presented, it will infer schema from all the rows after sampling. Also, add samplingRatio for jsonFile() and jsonRDD() Author: Davies Liu <davies.liu@gmail.com> Author: Davies Liu <davies@databricks.com> Closes #2716 from davies/infer and squashes the following commits: e678f6d [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer 34b5c63 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer 567dc60 [Davies Liu] update docs 9767b27 [Davies Liu] Merge branch 'master' into infer e48d7fb [Davies Liu] fix tests 29e94d5 [Davies Liu] let NullType inherit from PrimitiveType ee5d524 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer 540d1d5 [Davies Liu] merge fields for StructType f93fd84 [Davies Liu] add more tests 3603e00 [Davies Liu] take more rows to infer schema, or infer the schema by sampling the RDD (cherry picked from commit 24544fbce05665ab4999a1fe5aac434d29cd912c) Signed-off-by: Michael Armbrust <michael@databricks.com>
* [SPARK-4148][PySpark] fix seed distribution and add some tests for rdd.sampleXiangrui Meng2014-11-031-0/+15
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The current way of seed distribution makes the random sequences from partition i and i+1 offset by 1. ~~~ In [14]: import random In [15]: r1 = random.Random(10) In [16]: r1.randint(0, 1) Out[16]: 1 In [17]: r1.random() Out[17]: 0.4288890546751146 In [18]: r1.random() Out[18]: 0.5780913011344704 In [19]: r2 = random.Random(10) In [20]: r2.randint(0, 1) Out[20]: 1 In [21]: r2.randint(0, 1) Out[21]: 0 In [22]: r2.random() Out[22]: 0.5780913011344704 ~~~ Note: The new tests are not for this bug fix. Author: Xiangrui Meng <meng@databricks.com> Closes #3010 from mengxr/SPARK-4148 and squashes the following commits: 869ae4b [Xiangrui Meng] move tests tests.py c1bacd9 [Xiangrui Meng] fix seed distribution and add some tests for rdd.sample (cherry picked from commit 3cca1962207745814b9d83e791713c91b659c36c) Signed-off-by: Xiangrui Meng <meng@databricks.com>
* [SPARK-4133] [SQL] [PySpark] type conversionfor python udfDavies Liu2014-10-281-3/+13
| | | | | | | | | | | | | | | | Call Python UDF on ArrayType/MapType/PrimitiveType, the returnType can also be ArrayType/MapType/PrimitiveType. For StructType, it will act as tuple (without attributes). If returnType is StructType, it also should be tuple. Author: Davies Liu <davies@databricks.com> Closes #2973 from davies/udf_array and squashes the following commits: 306956e [Davies Liu] Merge branch 'master' of github.com:apache/spark into udf_array 2c00e43 [Davies Liu] fix merge 11395fa [Davies Liu] Merge branch 'master' of github.com:apache/spark into udf_array 9df50a2 [Davies Liu] address comments 79afb4e [Davies Liu] type conversionfor python udf
* [SPARK-4051] [SQL] [PySpark] Convert Row into dictionaryDavies Liu2014-10-241-0/+9
| | | | | | | | | | | | | | | | Added a method to Row to turn row into dict: ``` >>> row = Row(a=1) >>> row.asDict() {'a': 1} ``` Author: Davies Liu <davies@databricks.com> Closes #2896 from davies/dict and squashes the following commits: 8d97366 [Davies Liu] convert Row into dict
* [SPARK-3993] [PySpark] fix bug while reuse worker after take()Davies Liu2014-10-231-1/+18
| | | | | | | | | | | | | | After take(), maybe there are some garbage left in the socket, then next task assigned to this worker will hang because of corrupted data. We should make sure the socket is clean before reuse it, write END_OF_STREAM at the end, and check it after read out all result from python. Author: Davies Liu <davies.liu@gmail.com> Author: Davies Liu <davies@databricks.com> Closes #2838 from davies/fix_reuse and squashes the following commits: 8872914 [Davies Liu] fix tests 660875b [Davies Liu] fix bug while reuse worker after take()
* Fix for sampling error in NumPy v1.9 [SPARK-3995][PYSPARK]freeman2014-10-221-0/+6
| | | | | | | | | | | | | | Change maximum value for default seed during RDD sampling so that it is strictly less than 2 ** 32. This prevents a bug in the most recent version of NumPy, which cannot accept random seeds above this bound. Adds an extra test that uses the default seed (instead of setting it manually, as in the docstrings). mengxr Author: freeman <the.freeman.lab@gmail.com> Closes #2889 from freeman-lab/pyspark-sampling and squashes the following commits: dc385ef [freeman] Change maximum value for default seed
* [SPARK-3855][SQL] Preserve the result attribute of python UDFs though ↵Michael Armbrust2014-10-171-0/+6
| | | | | | | | | | | | | | transformations In the current implementation it was possible for the reference to change after analysis. Author: Michael Armbrust <michael@databricks.com> Closes #2717 from marmbrus/pythonUdfResults and squashes the following commits: da14879 [Michael Armbrust] Fix test 6343bcb [Michael Armbrust] add test 9533286 [Michael Armbrust] Correctly preserve the result attribute of python UDFs though transformations
* [SPARK-3867][PySpark] ./python/run-tests failed when it run with Python 2.6 ↵cocoatomo2014-10-111-1/+5
| | | | | | | | | | | | | and unittest2 is not installed ./python/run-tests search a Python 2.6 executable on PATH and use it if available. When using Python 2.6, it is going to import unittest2 module which is not a standard library in Python 2.6, so it fails with ImportError. Author: cocoatomo <cocoatomo77@gmail.com> Closes #2759 from cocoatomo/issues/3867-unittest2-import-error and squashes the following commits: f068eb5 [cocoatomo] [SPARK-3867] ./python/run-tests failed when it run with Python 2.6 and unittest2 is not installed
* [SPARK-3786] [PySpark] speedup testsDavies Liu2014-10-061-50/+42
| | | | | | | | | | | | | | | | | | | | | | | | | This patch try to speed up tests of PySpark, re-use the SparkContext in tests.py and mllib/tests.py to reduce the overhead of create SparkContext, remove some test cases, which did not make sense. It also improve the performance of some cases, such as MergerTests and SortTests. before this patch: real 21m27.320s user 4m42.967s sys 0m17.343s after this patch: real 9m47.541s user 2m12.947s sys 0m14.543s It almost cut the time by half. Author: Davies Liu <davies.liu@gmail.com> Closes #2646 from davies/tests and squashes the following commits: c54de60 [Davies Liu] revert change about memory limit 6a2a4b0 [Davies Liu] refactor of tests, speedup 100%
* [SPARK-3749] [PySpark] fix bugs in broadcast large closure of RDDDavies Liu2014-10-011-2/+6
| | | | | | | | | | | | | | 1. broadcast is triggle unexpected 2. fd is leaked in JVM (also leak in parallelize()) 3. broadcast is not unpersisted in JVM after RDD is not be used any more. cc JoshRosen , sorry for these stupid bugs. Author: Davies Liu <davies.liu@gmail.com> Closes #2603 from davies/fix_broadcast and squashes the following commits: 080a743 [Davies Liu] fix bugs in broadcast large closure of RDD
* [SPARK-3478] [PySpark] Profile the Python tasksDavies Liu2014-09-301-0/+30
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* [SPARK-3681] [SQL] [PySpark] fix serialization of List and Map in SchemaRDDDavies Liu2014-09-271-0/+21
| | | | | | | | | | | | Currently, the schema of object in ArrayType or MapType is attached lazily, it will have better performance but introduce issues while serialization or accessing nested objects. This patch will apply schema to the objects of ArrayType or MapType immediately when accessing them, will be a little bit slower, but much robust. Author: Davies Liu <davies.liu@gmail.com> Closes #2526 from davies/nested and squashes the following commits: 2399ae5 [Davies Liu] fix serialization of List and Map in SchemaRDD
* Revert "[SPARK-3478] [PySpark] Profile the Python tasks"Josh Rosen2014-09-261-30/+0
| | | | This reverts commit 1aa549ba9839565274a12c52fa1075b424f138a6.
* [SPARK-3478] [PySpark] Profile the Python tasksDavies Liu2014-09-261-0/+30
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-3679] [PySpark] pickle the exact globals of functionsDavies Liu2014-09-241-0/+18
| | | | | | | | | | | | | | function.func_code.co_names has all the names used in the function, including name of attributes. It will pickle some unnecessary globals if there is a global having the same name with attribute (in co_names). There is a regression introduced by #2144, revert part of changes in that PR. cc JoshRosen Author: Davies Liu <davies.liu@gmail.com> Closes #2522 from davies/globals and squashes the following commits: dfbccf5 [Davies Liu] fix bug while pickle globals of function
* [SPARK-3634] [PySpark] User's module should take precedence over system modulesDavies Liu2014-09-241-0/+12
| | | | | | | | | | | | | | | Python modules added through addPyFile should take precedence over system modules. This patch put the path for user added module in the front of sys.path (just after ''). Author: Davies Liu <davies.liu@gmail.com> Closes #2492 from davies/path and squashes the following commits: 4a2af78 [Davies Liu] fix tests f7ff4da [Davies Liu] ad license header 6b0002f [Davies Liu] add tests c16c392 [Davies Liu] put addPyFile in front of sys.path
* [PySpark] remove unnecessary use of numSlices from pyspark testsMatthew Farrellee2014-09-201-2/+2
| | | | | | | | Author: Matthew Farrellee <matt@redhat.com> Closes #2467 from mattf/master-pyspark-remove-numslices-from-tests and squashes the following commits: c49a87b [Matthew Farrellee] [PySpark] remove unnecessary use of numSlices from pyspark tests
* [SPARK-3592] [SQL] [PySpark] support applySchema to RDD of RowDavies Liu2014-09-191-1/+10
| | | | | | | | | | | | | | | Fix the issue when applySchema() to an RDD of Row. Also add type mapping for BinaryType. Author: Davies Liu <davies.liu@gmail.com> Closes #2448 from davies/row and squashes the following commits: dd220cf [Davies Liu] fix test 3f3f188 [Davies Liu] add more test f559746 [Davies Liu] add tests, fix serialization 9688fd2 [Davies Liu] support applySchema to RDD of Row
* [SPARK-3554] [PySpark] use broadcast automatically for large closureDavies Liu2014-09-181-0/+6
| | | | | | | | | | | Py4j can not handle large string efficiently, so we should use broadcast for large closure automatically. (Broadcast use local filesystem to pass through data). Author: Davies Liu <davies.liu@gmail.com> Closes #2417 from davies/command and squashes the following commits: fbf4e97 [Davies Liu] bugfix aefd508 [Davies Liu] use broadcast automatically for large closure
* [SPARK-3519] add distinct(n) to PySparkMatthew Farrellee2014-09-161-0/+17
| | | | | | | | | | | | Added missing rdd.distinct(numPartitions) and associated tests Author: Matthew Farrellee <matt@redhat.com> Closes #2383 from mattf/SPARK-3519 and squashes the following commits: 30b837a [Matthew Farrellee] Combine test cases to save on JVM startups 6bc4a2c [Matthew Farrellee] [SPARK-3519] add distinct(n) to SchemaRDD in PySpark 7a17f2b [Matthew Farrellee] [SPARK-3519] add distinct(n) to PySpark
* [SPARK-2951] [PySpark] support unpickle array.array for Python 2.6Davies Liu2014-09-151-2/+0
| | | | | | | | | | | | | | | | | Pyrolite can not unpickle array.array which pickled by Python 2.6, this patch fix it by extend Pyrolite. There is a bug in Pyrolite when unpickle array of float/double, this patch workaround it by reverse the endianness for float/double. This workaround should be removed after Pyrolite have a new release to fix this issue. I had send an PR to Pyrolite to fix it: https://github.com/irmen/Pyrolite/pull/11 Author: Davies Liu <davies.liu@gmail.com> Closes #2365 from davies/pickle and squashes the following commits: f44f771 [Davies Liu] enable tests about array 3908f5c [Davies Liu] Merge branch 'master' into pickle c77c87b [Davies Liu] cleanup debugging code 60e4e2f [Davies Liu] support unpickle array.array for Python 2.6
* [SPARK-3463] [PySpark] aggregate and show spilled bytes in PythonDavies Liu2014-09-131-7/+8
| | | | | | | | | | | | | | | | | | Aggregate the number of bytes spilled into disks during aggregation or sorting, show them in Web UI. ![spilled](https://cloud.githubusercontent.com/assets/40902/4209758/4b995562-386d-11e4-97c1-8e838ee1d4e3.png) This patch is blocked by SPARK-3465. (It includes a fix for that). Author: Davies Liu <davies.liu@gmail.com> Closes #2336 from davies/metrics and squashes the following commits: e37df38 [Davies Liu] remove outdated comments 1245eb7 [Davies Liu] remove the temporary fix ebd2f43 [Davies Liu] Merge branch 'master' into metrics 7e4ad04 [Davies Liu] Merge branch 'master' into metrics fbe9029 [Davies Liu] show spilled bytes in Python in web ui
* [SPARK-3030] [PySpark] Reuse Python workerDavies Liu2014-09-131-0/+35
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Reuse Python worker to avoid the overhead of fork() Python process for each tasks. It also tracks the broadcasts for each worker, avoid sending repeated broadcasts. This can reduce the time for dummy task from 22ms to 13ms (-40%). It can help to reduce the latency for Spark Streaming. For a job with broadcast (43M after compress): ``` b = sc.broadcast(set(range(30000000))) print sc.parallelize(range(24000), 100).filter(lambda x: x in b.value).count() ``` It will finish in 281s without reused worker, and it will finish in 65s with reused worker(4 CPUs). After reusing the worker, it can save about 9 seconds for transfer and deserialize the broadcast for each tasks. It's enabled by default, could be disabled by `spark.python.worker.reuse = false`. Author: Davies Liu <davies.liu@gmail.com> Closes #2259 from davies/reuse-worker and squashes the following commits: f11f617 [Davies Liu] Merge branch 'master' into reuse-worker 3939f20 [Davies Liu] fix bug in serializer in mllib cf1c55e [Davies Liu] address comments 3133a60 [Davies Liu] fix accumulator with reused worker 760ab1f [Davies Liu] do not reuse worker if there are any exceptions 7abb224 [Davies Liu] refactor: sychronized with itself ac3206e [Davies Liu] renaming 8911f44 [Davies Liu] synchronized getWorkerBroadcasts() 6325fc1 [Davies Liu] bugfix: bid >= 0 e0131a2 [Davies Liu] fix name of config 583716e [Davies Liu] only reuse completed and not interrupted worker ace2917 [Davies Liu] kill python worker after timeout 6123d0f [Davies Liu] track broadcasts for each worker 8d2f08c [Davies Liu] reuse python worker
* [SPARK-3500] [SQL] use JavaSchemaRDD as SchemaRDD._jschema_rddDavies Liu2014-09-121-0/+28
| | | | | | | | | | | | | | Currently, SchemaRDD._jschema_rdd is SchemaRDD, the Scala API (coalesce(), repartition()) can not been called in Python easily, there is no way to specify the implicit parameter `ord`. The _jrdd is an JavaRDD, so _jschema_rdd should also be JavaSchemaRDD. In this patch, change _schema_rdd to JavaSchemaRDD, also added an assert for it. If some methods are missing from JavaSchemaRDD, then it's called by _schema_rdd.baseSchemaRDD().xxx(). BTW, Do we need JavaSQLContext? Author: Davies Liu <davies.liu@gmail.com> Closes #2369 from davies/fix_schemardd and squashes the following commits: abee159 [Davies Liu] use JavaSchemaRDD as SchemaRDD._jschema_rdd
* [SPARK-3094] [PySpark] compatitable with PyPyDavies Liu2014-09-121-9/+76
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | After this patch, we can run PySpark in PyPy (testing with PyPy 2.3.1 in Mac 10.9), for example: ``` PYSPARK_PYTHON=pypy ./bin/spark-submit wordcount.py ``` The performance speed up will depend on work load (from 20% to 3000%). Here are some benchmarks: Job | CPython 2.7 | PyPy 2.3.1 | Speed up ------- | ------------ | ------------- | ------- Word Count | 41s | 15s | 2.7x Sort | 46s | 44s | 1.05x Stats | 174s | 3.6s | 48x Here is the code used for benchmark: ```python rdd = sc.textFile("text") def wordcount(): rdd.flatMap(lambda x:x.split('/'))\ .map(lambda x:(x,1)).reduceByKey(lambda x,y:x+y).collectAsMap() def sort(): rdd.sortBy(lambda x:x, 1).count() def stats(): sc.parallelize(range(1024), 20).flatMap(lambda x: xrange(5024)).stats() ``` Author: Davies Liu <davies.liu@gmail.com> Closes #2144 from davies/pypy and squashes the following commits: 9aed6c5 [Davies Liu] use protocol 2 in CloudPickle 4bc1f04 [Davies Liu] refactor b20ab3a [Davies Liu] pickle sys.stdout and stderr in portable way 3ca2351 [Davies Liu] Merge branch 'master' into pypy fae8b19 [Davies Liu] improve attrgetter, add tests 591f830 [Davies Liu] try to run tests with PyPy in run-tests c8d62ba [Davies Liu] cleanup f651fd0 [Davies Liu] fix tests using array with PyPy 1b98fb3 [Davies Liu] serialize itemgetter/attrgetter in portable ways 3c1dbfe [Davies Liu] Merge branch 'master' into pypy 42fb5fa [Davies Liu] Merge branch 'master' into pypy cb2d724 [Davies Liu] fix tests 9986692 [Davies Liu] Merge branch 'master' into pypy 25b4ca7 [Davies Liu] support PyPy
* [SPARK-3458] enable python "with" statements for SparkContextMatthew Farrellee2014-09-091-0/+29
| | | | | | | | | | | | | | | | | | | | | | | | | allow for best practice code, ``` try: sc = SparkContext() app(sc) finally: sc.stop() ``` to be written using a "with" statement, ``` with SparkContext() as sc: app(sc) ``` Author: Matthew Farrellee <matt@redhat.com> Closes #2335 from mattf/SPARK-3458 and squashes the following commits: 5b4e37c [Matthew Farrellee] [SPARK-3458] enable python "with" statements for SparkContext
* SPARK-2978. Transformation with MR shuffle semanticsSandy Ryza2014-09-081-0/+8
| | | | | | | | | | | | | | | | | | I didn't add this to the transformations list in the docs because it's kind of obscure, but would be happy to do so if others think it would be helpful. Author: Sandy Ryza <sandy@cloudera.com> Closes #2274 from sryza/sandy-spark-2978 and squashes the following commits: 4a5332a [Sandy Ryza] Fix Java test c04b447 [Sandy Ryza] Fix Python doc and add back deleted code 433ad5b [Sandy Ryza] Add Java test 4c25a54 [Sandy Ryza] Add s at the end and a couple other fixes 9b0ba99 [Sandy Ryza] Fix compilation 36e0571 [Sandy Ryza] Fix import ordering 48c12c2 [Sandy Ryza] Add Java version and additional doc e5381cd [Sandy Ryza] Fix python style warnings f147634 [Sandy Ryza] SPARK-2978. Transformation with MR shuffle semantics
* [SPARK-3415] [PySpark] removes SerializingAdapter codeWard Viaene2014-09-071-0/+11
| | | | | | | | | | | | | | | | This code removes the SerializingAdapter code that was copied from PiCloud Author: Ward Viaene <ward.viaene@bigdatapartnership.com> Closes #2287 from wardviaene/feature/pythonsys and squashes the following commits: 5f0d426 [Ward Viaene] SPARK-3415: modified test class to do dump and load 5f5d559 [Ward Viaene] SPARK-3415: modified test class name and call cloudpickle.dumps instead using StringIO afc4a9a [Ward Viaene] SPARK-3415: added newlines to pass lint aaf10b7 [Ward Viaene] SPARK-3415: removed references to SerializingAdapter and rewrote test 65ffeff [Ward Viaene] removed duplicate test a958866 [Ward Viaene] SPARK-3415: test script e263bf5 [Ward Viaene] SPARK-3415: removes legacy SerializingAdapter code
* [SPARK-2334] fix AttributeError when call PipelineRDD.id()Davies Liu2014-09-061-0/+9
| | | | | | | | | | | | | | | The underline JavaRDD for PipelineRDD is created lazily, it's delayed until call _jrdd. The id of JavaRDD is cached as `_id`, it saves a RPC call in py4j for later calls. closes #1276 Author: Davies Liu <davies.liu@gmail.com> Closes #2296 from davies/id and squashes the following commits: e197958 [Davies Liu] fix style 9721716 [Davies Liu] fix id of PipelineRDD
* [SPARK-3335] [SQL] [PySpark] support broadcast in Python UDFDavies Liu2014-09-031-0/+22
| | | | | | | | | | After this patch, broadcast can be used in Python UDF. Author: Davies Liu <davies.liu@gmail.com> Closes #2243 from davies/udf_broadcast and squashes the following commits: 7b88861 [Davies Liu] support broadcast in UDF
* [SPARK-2871] [PySpark] add countApproxDistinct() APIDavies Liu2014-09-021-0/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | RDD.countApproxDistinct(relativeSD=0.05): :: Experimental :: Return approximate number of distinct elements in the RDD. The algorithm used is based on streamlib's implementation of "HyperLogLog in Practice: Algorithmic Engineering of a State of The Art Cardinality Estimation Algorithm", available <a href="http://dx.doi.org/10.1145/2452376.2452456">here</a>. This support all the types of objects, which is supported by Pyrolite, nearly all builtin types. param relativeSD Relative accuracy. Smaller values create counters that require more space. It must be greater than 0.000017. >>> n = sc.parallelize(range(1000)).map(str).countApproxDistinct() >>> 950 < n < 1050 True >>> n = sc.parallelize([i % 20 for i in range(1000)]).countApproxDistinct() >>> 18 < n < 22 True Author: Davies Liu <davies.liu@gmail.com> Closes #2142 from davies/countApproxDistinct and squashes the following commits: e20da47 [Davies Liu] remove the correction in Python c38c4e4 [Davies Liu] fix doc tests 2ab157c [Davies Liu] fix doc tests 9d2565f [Davies Liu] add commments and link for hash collision correction d306492 [Davies Liu] change range of hash of tuple to [0, maxint] ded624f [Davies Liu] calculate hash in Python 4cba98f [Davies Liu] add more tests a85a8c6 [Davies Liu] Merge branch 'master' into countApproxDistinct e97e342 [Davies Liu] add countApproxDistinct()
* [SPARK-3073] [PySpark] use external sort in sortBy() and sortByKey()Davies Liu2014-08-261-1/+41
| | | | | | | | | | | | | | | | | Using external sort to support sort large datasets in reduce stage. Author: Davies Liu <davies.liu@gmail.com> Closes #1978 from davies/sort and squashes the following commits: bbcd9ba [Davies Liu] check spilled bytes in tests b125d2f [Davies Liu] add test for external sort in rdd eae0176 [Davies Liu] choose different disks from different processes and instances 1f075ed [Davies Liu] Merge branch 'master' into sort eb53ca6 [Davies Liu] Merge branch 'master' into sort 644abaf [Davies Liu] add license in LICENSE 19f7873 [Davies Liu] improve tests 55602ee [Davies Liu] use external sort in sortBy() and sortByKey()
* [SPARK-2871] [PySpark] add histgram() APIDavies Liu2014-08-261-0/+104
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | RDD.histogram(buckets) Compute a histogram using the provided buckets. The buckets are all open to the right except for the last which is closed. e.g. [1,10,20,50] means the buckets are [1,10) [10,20) [20,50], which means 1<=x<10, 10<=x<20, 20<=x<=50. And on the input of 1 and 50 we would have a histogram of 1,0,1. If your histogram is evenly spaced (e.g. [0, 10, 20, 30]), this can be switched from an O(log n) inseration to O(1) per element(where n = # buckets). Buckets must be sorted and not contain any duplicates, must be at least two elements. If `buckets` is a number, it will generates buckets which is evenly spaced between the minimum and maximum of the RDD. For example, if the min value is 0 and the max is 100, given buckets as 2, the resulting buckets will be [0,50) [50,100]. buckets must be at least 1 If the RDD contains infinity, NaN throws an exception If the elements in RDD do not vary (max == min) always returns a single bucket. It will return an tuple of buckets and histogram. >>> rdd = sc.parallelize(range(51)) >>> rdd.histogram(2) ([0, 25, 50], [25, 26]) >>> rdd.histogram([0, 5, 25, 50]) ([0, 5, 25, 50], [5, 20, 26]) >>> rdd.histogram([0, 15, 30, 45, 60], True) ([0, 15, 30, 45, 60], [15, 15, 15, 6]) >>> rdd = sc.parallelize(["ab", "ac", "b", "bd", "ef"]) >>> rdd.histogram(("a", "b", "c")) (('a', 'b', 'c'), [2, 2]) closes #122, it's duplicated. Author: Davies Liu <davies.liu@gmail.com> Closes #2091 from davies/histgram and squashes the following commits: a322f8a [Davies Liu] fix deprecation of e.message 84e85fa [Davies Liu] remove evenBuckets, add more tests (including str) d9a0722 [Davies Liu] address comments 0e18a2d [Davies Liu] add histgram() API
* [SPARK-2790] [PySpark] fix zip with serializers which have different batch ↵Davies Liu2014-08-191-1/+26
| | | | | | | | | | | | | | | sizes. If two RDDs have different batch size in serializers, then it will try to re-serialize the one with smaller batch size, then call RDD.zip() in Spark. Author: Davies Liu <davies.liu@gmail.com> Closes #1894 from davies/zip and squashes the following commits: c4652ea [Davies Liu] add more test cases 6d05fc8 [Davies Liu] Merge branch 'master' into zip 813b1e4 [Davies Liu] add more tests for failed cases a4aafda [Davies Liu] fix zip with serializers which have different batch sizes.
* [SPARK-3103] [PySpark] fix saveAsTextFile() with utf-8Davies Liu2014-08-181-0/+9
| | | | | | | | | | bugfix: It will raise an exception when it try to encode non-ASCII strings into unicode. It should only encode unicode as "utf-8". Author: Davies Liu <davies.liu@gmail.com> Closes #2018 from davies/fix_utf8 and squashes the following commits: 4db7967 [Davies Liu] fix saveAsTextFile() with utf-8
* [SPARK-1065] [PySpark] improve supporting for large broadcastDavies Liu2014-08-161-0/+7
| | | | | | | | | | | | | | | | | | Passing large object by py4j is very slow (cost much memory), so pass broadcast objects via files (similar to parallelize()). Add an option to keep object in driver (it's False by default) to save memory in driver. Author: Davies Liu <davies.liu@gmail.com> Closes #1912 from davies/broadcast and squashes the following commits: e06df4a [Davies Liu] load broadcast from disk in driver automatically db3f232 [Davies Liu] fix serialization of accumulator 631a827 [Davies Liu] Merge branch 'master' into broadcast c7baa8c [Davies Liu] compress serrialized broadcast and command 9a7161f [Davies Liu] fix doc tests e93cf4b [Davies Liu] address comments: add test 6226189 [Davies Liu] improve large broadcast
* [PySpark] [SPARK-2954] [SPARK-2948] [SPARK-2910] [SPARK-2101] Python 2.6 FixesJosh Rosen2014-08-111-3/+10
| | | | | | | | | | | | | | | | | - Modify python/run-tests to test with Python 2.6 - Use unittest2 when running on Python 2.6. - Fix issue with namedtuple. - Skip TestOutputFormat.test_newhadoop on Python 2.6 until SPARK-2951 is fixed. - Fix MLlib _deserialize_double on Python 2.6. Closes #1868. Closes #1042. Author: Josh Rosen <joshrosen@apache.org> Closes #1874 from JoshRosen/python2.6 and squashes the following commits: 983d259 [Josh Rosen] [SPARK-2954] Fix MLlib _deserialize_double on Python 2.6. 5d18fd7 [Josh Rosen] [SPARK-2948] [SPARK-2910] [SPARK-2101] Python 2.6 fixes
* [SPARK-2627] [PySpark] have the build enforce PEP 8 automaticallyNicholas Chammas2014-08-061-62/+81
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
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