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* [SPARK-4586][MLLIB] Python API for ML pipeline and parametersXiangrui Meng2015-01-2816-16/+1124
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds Python API for ML pipeline and parameters. The design doc can be found on the JIRA page. It includes transformers and an estimator to demo the simple text classification example code. TODO: - [x] handle parameters in LRModel - [x] unit tests - [x] missing some docs CC: davies jkbradley Author: Xiangrui Meng <meng@databricks.com> Author: Davies Liu <davies@databricks.com> Closes #4151 from mengxr/SPARK-4586 and squashes the following commits: 415268e [Xiangrui Meng] remove inherit_doc from __init__ edbd6fe [Xiangrui Meng] move Identifiable to ml.util 44c2405 [Xiangrui Meng] Merge pull request #2 from davies/ml dd1256b [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586 14ae7e2 [Davies Liu] fix docs 54ca7df [Davies Liu] fix tests 78638df [Davies Liu] Merge branch 'SPARK-4586' of github.com:mengxr/spark into ml fc59a02 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586 1dca16a [Davies Liu] refactor 090b3a3 [Davies Liu] Merge branch 'master' of github.com:apache/spark into ml 0882513 [Xiangrui Meng] update doc style a4f4dbf [Xiangrui Meng] add unit test for LR 7521d1c [Xiangrui Meng] add unit tests to HashingTF and Tokenizer ba0ba1e [Xiangrui Meng] add unit tests for pipeline 0586c7b [Xiangrui Meng] add more comments to the example 5153cff [Xiangrui Meng] simplify java models 036ca04 [Xiangrui Meng] gen numFeatures 46fa147 [Xiangrui Meng] update mllib/pom.xml to include python files in the assembly 1dcc17e [Xiangrui Meng] update code gen and make param appear in the doc f66ba0c [Xiangrui Meng] make params a property d5efd34 [Xiangrui Meng] update doc conf and move embedded param map to instance attribute f4d0fe6 [Xiangrui Meng] use LabeledDocument and Document in example 05e3e40 [Xiangrui Meng] update example d3e8dbe [Xiangrui Meng] more docs optimize pipeline.fit impl 56de571 [Xiangrui Meng] fix style d0c5bb8 [Xiangrui Meng] a working copy bce72f4 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4586 17ecfb9 [Xiangrui Meng] code gen for shared params d9ea77c [Xiangrui Meng] update doc c18dca1 [Xiangrui Meng] make the example working dadd84e [Xiangrui Meng] add base classes and docs a3015cf [Xiangrui Meng] add Estimator and Transformer 46eea43 [Xiangrui Meng] a pipeline in python 33b68e0 [Xiangrui Meng] a working LR
* [SPARK-4387][PySpark] Refactoring python profiling code to make it extensibleYandu Oppacher2015-01-288-71/+232
| | | | | | | | | | | | | | | | | | | | | | | | 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-5440][pyspark] Add toLocalIterator to pyspark rddMichael Nazario2015-01-281-0/+14
| | | | | | | | | | | Since Java and Scala both have access to iterate over partitions via the "toLocalIterator" function, python should also have that same ability. Author: Michael Nazario <mnazario@palantir.com> Closes #4237 from mnazario/feature/toLocalIterator and squashes the following commits: 1c58526 [Michael Nazario] Fix documentation off by one error 0cdc8f8 [Michael Nazario] Add toLocalIterator to PySpark
* SPARK-5458. Refer to aggregateByKey instead of combineByKey in docsSandy Ryza2015-01-281-2/+2
| | | | | | | | | Author: Sandy Ryza <sandy@cloudera.com> Closes #4251 from sryza/sandy-spark-5458 and squashes the following commits: 460827a [Sandy Ryza] Python too d2dc160 [Sandy Ryza] SPARK-5458. Refer to aggregateByKey instead of combineByKey in docs
* [SPARK-5361]Multiple Java RDD <-> Python RDD conversions not working correctlyWinston Chen2015-01-281-0/+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
* [SPARK-5097][SQL] DataFrameReynold Xin2015-01-273-336/+793
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This pull request redesigns the existing Spark SQL dsl, which already provides data frame like functionalities. TODOs: With the exception of Python support, other tasks can be done in separate, follow-up PRs. - [ ] Audit of the API - [ ] Documentation - [ ] More test cases to cover the new API - [x] Python support - [ ] Type alias SchemaRDD Author: Reynold Xin <rxin@databricks.com> Author: Davies Liu <davies@databricks.com> Closes #4173 from rxin/df1 and squashes the following commits: 0a1a73b [Reynold Xin] Merge branch 'df1' of github.com:rxin/spark into df1 23b4427 [Reynold Xin] Mima. 828f70d [Reynold Xin] Merge pull request #7 from davies/df 257b9e6 [Davies Liu] add repartition 6bf2b73 [Davies Liu] fix collect with UDT and tests e971078 [Reynold Xin] Missing quotes. b9306b4 [Reynold Xin] Remove removeColumn/updateColumn for now. a728bf2 [Reynold Xin] Example rename. e8aa3d3 [Reynold Xin] groupby -> groupBy. 9662c9e [Davies Liu] improve DataFrame Python API 4ae51ea [Davies Liu] python API for dataframe 1e5e454 [Reynold Xin] Fixed a bug with symbol conversion. 2ca74db [Reynold Xin] Couple minor fixes. ea98ea1 [Reynold Xin] Documentation & literal expressions. 2b22684 [Reynold Xin] Got rid of IntelliJ problems. 02bbfbc [Reynold Xin] Tightening imports. ffbce66 [Reynold Xin] Fixed compilation error. 59b6d8b [Reynold Xin] Style violation. b85edfb [Reynold Xin] ALS. 8c37f0a [Reynold Xin] Made MLlib and examples compile 6d53134 [Reynold Xin] Hive module. d35efd5 [Reynold Xin] Fixed compilation error. ce4a5d2 [Reynold Xin] Fixed test cases in SQL except ParquetIOSuite. 66d5ef1 [Reynold Xin] SQLContext minor patch. c9bcdc0 [Reynold Xin] Checkpoint: SQL module compiles!
* [SPARK-5063] More helpful error messages for several invalid operationsJosh Rosen2015-01-232-0/+19
| | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch adds more helpful error messages for invalid programs that define nested RDDs, broadcast RDDs, perform actions inside of transformations (e.g. calling `count()` from inside of `map()`), and call certain methods on stopped SparkContexts. Currently, these invalid programs lead to confusing NullPointerExceptions at runtime and have been a major source of questions on the mailing list and StackOverflow. In a few cases, I chose to log warnings instead of throwing exceptions in order to avoid any chance that this patch breaks programs that worked "by accident" in earlier Spark releases (e.g. programs that define nested RDDs but never run any jobs with them). In SparkContext, the new `assertNotStopped()` method is used to check whether methods are being invoked on a stopped SparkContext. In some cases, user programs will not crash in spite of calling methods on stopped SparkContexts, so I've only added `assertNotStopped()` calls to methods that always throw exceptions when called on stopped contexts (e.g. by dereferencing a null `dagScheduler` pointer). Author: Josh Rosen <joshrosen@databricks.com> Closes #3884 from JoshRosen/SPARK-5063 and squashes the following commits: a38774b [Josh Rosen] Fix spelling typo a943e00 [Josh Rosen] Convert two exceptions into warnings in order to avoid breaking user programs in some edge-cases. 2d0d7f7 [Josh Rosen] Fix test to reflect 1.2.1 compatibility 3f0ea0c [Josh Rosen] Revert two unintentional formatting changes 8e5da69 [Josh Rosen] Remove assertNotStopped() calls for methods that were sometimes safe to call on stopped SC's in Spark 1.2 8cff41a [Josh Rosen] IllegalStateException fix 6ef68d0 [Josh Rosen] Fix Python line length issues. 9f6a0b8 [Josh Rosen] Add improved error messages to PySpark. 13afd0f [Josh Rosen] SparkException -> IllegalStateException 8d404f3 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-5063 b39e041 [Josh Rosen] Fix BroadcastSuite test which broadcasted an RDD 99cc09f [Josh Rosen] Guard against calling methods on stopped SparkContexts. 34833e8 [Josh Rosen] Add more descriptive error message. 57cc8a1 [Josh Rosen] Add error message when directly broadcasting RDD. 15b2e6b [Josh Rosen] [SPARK-5063] Useful error messages for nested RDDs and actions inside of transformations
* [SPARK-4749] [mllib]: Allow initializing KMeans clusters using a seednate.crosswhite2015-01-212-3/+18
| | | | | | | | | | | | | | | | | | | This implements the functionality for SPARK-4749 and provides units tests in Scala and PySpark Author: nate.crosswhite <nate.crosswhite@stresearch.com> Author: nxwhite-str <nxwhite-str@users.noreply.github.com> Author: Xiangrui Meng <meng@databricks.com> Closes #3610 from nxwhite-str/master and squashes the following commits: a2ebbd3 [nxwhite-str] Merge pull request #1 from mengxr/SPARK-4749-kmeans-seed 7668124 [Xiangrui Meng] minor updates f8d5928 [nate.crosswhite] Addressing PR issues 277d367 [nate.crosswhite] Merge remote-tracking branch 'upstream/master' 9156a57 [nate.crosswhite] Merge remote-tracking branch 'upstream/master' 5d087b4 [nate.crosswhite] Adding KMeans train with seed and Scala unit test 616d111 [nate.crosswhite] Merge remote-tracking branch 'upstream/master' 35c1884 [nate.crosswhite] Add kmeans initial seed to pyspark API
* SPARK-5270 [CORE] Provide isEmpty() function in RDD APISean Owen2015-01-191-0/+12
| | | | | | | | | | | | | Pretty minor, but submitted for consideration -- this would at least help people make this check in the most efficient way I know. Author: Sean Owen <sowen@cloudera.com> Closes #4074 from srowen/SPARK-5270 and squashes the following commits: 66885b8 [Sean Owen] Add note that JavaRDDLike should not be implemented by user code 2e9b490 [Sean Owen] More tests, and Mima-exclude the new isEmpty method in JavaRDDLike 28395ff [Sean Owen] Add isEmpty to Java, Python 7dd04b7 [Sean Owen] Add efficient RDD.isEmpty()
* [SPARK-5193][SQL] Remove Spark SQL Java-specific API.Reynold Xin2015-01-161-36/+12
| | | | | | | | | | | | | | | | | | | | | | | | | After the following patches, the main (Scala) API is now usable for Java users directly. https://github.com/apache/spark/pull/4056 https://github.com/apache/spark/pull/4054 https://github.com/apache/spark/pull/4049 https://github.com/apache/spark/pull/4030 https://github.com/apache/spark/pull/3965 https://github.com/apache/spark/pull/3958 Author: Reynold Xin <rxin@databricks.com> Closes #4065 from rxin/sql-java-api and squashes the following commits: b1fd860 [Reynold Xin] Fix Mima 6d86578 [Reynold Xin] Ok one more attempt in fixing Python... e8f1455 [Reynold Xin] Fix Python again... 3e53f91 [Reynold Xin] Fixed Python. 83735da [Reynold Xin] Fix BigDecimal test. e9f1de3 [Reynold Xin] Use scala BigDecimal. 500d2c4 [Reynold Xin] Fix Decimal. ba3bfa2 [Reynold Xin] Updated javadoc for RowFactory. c4ae1c5 [Reynold Xin] [SPARK-5193][SQL] Remove Spark SQL Java-specific API.
* [SPARK-5274][SQL] Reconcile Java and Scala UDFRegistration.Reynold Xin2015-01-151-8/+8
| | | | | | | | | | | | | | | | | | | | As part of SPARK-5193: 1. Removed UDFRegistration as a mixin in SQLContext and made it a field ("udf"). 2. For Java UDFs, renamed dataType to returnType. 3. For Scala UDFs, added type tags. 4. Added all Java UDF registration methods to Scala's UDFRegistration. 5. Documentation Author: Reynold Xin <rxin@databricks.com> Closes #4056 from rxin/udf-registration and squashes the following commits: ae9c556 [Reynold Xin] Updated example. 675a3c9 [Reynold Xin] Style fix 47c24ff [Reynold Xin] Python fix. 5f00c45 [Reynold Xin] Restore data type position in java udf and added typetags. 032f006 [Reynold Xin] [SPARK-5193][SQL] Reconcile Java and Scala UDFRegistration.
* [SPARK-5224] [PySpark] improve performance of parallelize list/ndarrayDavies Liu2015-01-152-1/+5
| | | | | | | | | | | | | | | | | | | After the default batchSize changed to 0 (batched based on the size of object), but parallelize() still use BatchedSerializer with batchSize=1, this PR will use batchSize=1024 for parallelize by default. Also, BatchedSerializer did not work well with list and numpy.ndarray, this improve BatchedSerializer by using __len__ and __getslice__. Here is the benchmark for parallelize 1 millions int with list or ndarray: | before | after | improvements ------- | ------------ | ------------- | ------- list | 11.7 s | 0.8 s | 14x numpy.ndarray | 32 s | 0.7 s | 40x Author: Davies Liu <davies@databricks.com> Closes #4024 from davies/opt_numpy and squashes the following commits: 7618c7c [Davies Liu] improve performance of parallelize list/ndarray
* [SPARK-2909] [MLlib] [PySpark] SparseVector in pyspark now supports indexingMechCoder2015-01-142-0/+29
| | | | | | | | | | | | | Slightly different than the scala code which converts the sparsevector into a densevector and then checks the index. I also hope I've added tests in the right place. Author: MechCoder <manojkumarsivaraj334@gmail.com> Closes #4025 from MechCoder/spark-2909 and squashes the following commits: 07d0f26 [MechCoder] STY: Rename item to index f02148b [MechCoder] [SPARK-2909] [Mlib] SparseVector in pyspark now supports indexing
* [SPARK-5223] [MLlib] [PySpark] fix MapConverter and ListConverter in MLlibDavies Liu2015-01-131-4/+2
| | | | | | | | | | | | | | | It will introduce problems if the object in dict/list/tuple can not support by py4j, such as Vector. Also, pickle may have better performance for larger object (less RPC). In some cases that the object in dict/list can not be pickled (such as JavaObject), we should still use MapConvert/ListConvert. This PR should be ported into branch-1.2 Author: Davies Liu <davies@databricks.com> Closes #4023 from davies/listconvert and squashes the following commits: 55d4ab2 [Davies Liu] fix MapConverter and ListConverter in MLlib
* [SPARK-5138][SQL] Ensure schema can be inferred from a namedtupleGabe Mulley2015-01-121-4/+14
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | When attempting to infer the schema of an RDD that contains namedtuples, pyspark fails to identify the records as namedtuples, resulting in it raising an error. Example: ```python from pyspark import SparkContext from pyspark.sql import SQLContext from collections import namedtuple import os sc = SparkContext() rdd = sc.textFile(os.path.join(os.getenv('SPARK_HOME'), 'README.md')) TextLine = namedtuple('TextLine', 'line length') tuple_rdd = rdd.map(lambda l: TextLine(line=l, length=len(l))) tuple_rdd.take(5) # This works sqlc = SQLContext(sc) # The following line raises an error schema_rdd = sqlc.inferSchema(tuple_rdd) ``` The error raised is: ``` File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 107, in main process() File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/worker.py", line 98, in process serializer.dump_stream(func(split_index, iterator), outfile) File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/serializers.py", line 227, in dump_stream vs = list(itertools.islice(iterator, batch)) File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/rdd.py", line 1107, in takeUpToNumLeft yield next(iterator) File "/opt/spark-1.2.0-bin-hadoop2.4/python/pyspark/sql.py", line 816, in convert_struct raise ValueError("unexpected tuple: %s" % obj) TypeError: not all arguments converted during string formatting ``` Author: Gabe Mulley <gabe@edx.org> Closes #3978 from mulby/inferschema-namedtuple and squashes the following commits: 98c61cc [Gabe Mulley] Ensure exception message is populated correctly 375d96b [Gabe Mulley] Ensure schema can be inferred from a namedtuple
* [SPARK-4891][PySpark][MLlib] Add gamma/log normal/exp dist sampling to P...RJ Nowling2015-01-081-0/+187
| | | | | | | | | | | | | | ...ySpark MLlib This is a follow up to PR3680 https://github.com/apache/spark/pull/3680 . Author: RJ Nowling <rnowling@gmail.com> Closes #3955 from rnowling/spark4891 and squashes the following commits: 1236a01 [RJ Nowling] Fix Python style issues 7a01a78 [RJ Nowling] Fix Python style issues 174beab [RJ Nowling] [SPARK-4891][PySpark][MLlib] Add gamma/log normal/exp dist sampling to PySpark MLlib
* [SPARK-5089][PYSPARK][MLLIB] Fix vector convertfreeman2015-01-052-1/+11
| | | | | | | | | | | | | | | This is a small change addressing a potentially significant bug in how PySpark + MLlib handles non-float64 numpy arrays. The automatic conversion to `DenseVector` that occurs when passing RDDs to MLlib algorithms in PySpark should automatically upcast to float64s, but currently this wasn't actually happening. As a result, non-float64 would be silently parsed inappropriately during SerDe, yielding erroneous results when running, for example, KMeans. The PR includes the fix, as well as a new test for the correct conversion behavior. davies Author: freeman <the.freeman.lab@gmail.com> Closes #3902 from freeman-lab/fix-vector-convert and squashes the following commits: 764db47 [freeman] Add a test for proper conversion behavior 704f97e [freeman] Return array after changing type
* [SPARK-3325][Streaming] Add a parameter to the method print in class DStreamYadong Qi2015-01-021-5/+7
| | | | | | | | | | | | | | | | | | | | | | | This PR is a fixed version of the original PR #3237 by watermen and scwf. This adds the ability to specify how many elements to print in `DStream.print`. Author: Yadong Qi <qiyadong2010@gmail.com> Author: q00251598 <qiyadong@huawei.com> Author: Tathagata Das <tathagata.das1565@gmail.com> Author: wangfei <wangfei1@huawei.com> Closes #3865 from tdas/print-num and squashes the following commits: cd34e9e [Tathagata Das] Fix bug 7c09f16 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into HEAD bb35d1a [Yadong Qi] Update MimaExcludes.scala f8098ca [Yadong Qi] Update MimaExcludes.scala f6ac3cb [Yadong Qi] Update MimaExcludes.scala e4ed897 [Yadong Qi] Update MimaExcludes.scala 3b9d5cf [wangfei] fix conflicts ec8a3af [q00251598] move to Spark 1.3 26a70c0 [q00251598] extend the Python DStream's print b589a4b [q00251598] add another print function
* [SPARK-4501][Core] - Create build/mvn to automatically download ↵Brennon York2014-12-271-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | maven/zinc/scalac Creates a top level directory script (as `build/mvn`) to automatically download zinc and the specific version of scala used to easily build spark. This will also download and install maven if the user doesn't already have it and all packages are hosted under the `build/` directory. Tested on both Linux and OSX OS's and both work. All commands pass through to the maven binary so it acts exactly as a traditional maven call would. Author: Brennon York <brennon.york@capitalone.com> Closes #3707 from brennonyork/SPARK-4501 and squashes the following commits: 0e5a0e4 [Brennon York] minor incorrect doc verbage (with -> this) 9b79e38 [Brennon York] fixed merge conflicts with dev/run-tests, properly quoted args in sbt/sbt, fixed bug where relative paths would fail if passed in from build/mvn d2d41b6 [Brennon York] added blurb about leverging zinc with build/mvn b979c58 [Brennon York] updated the merge conflict c5634de [Brennon York] updated documentation to overview build/mvn, updated all points where sbt/sbt was referenced with build/sbt b8437ba [Brennon York] set progress bars for curl and wget when not run on jenkins, no progress bar when run on jenkins, moved sbt script to build/sbt, wrote stub and warning under sbt/sbt which calls build/sbt, modified build/sbt to use the correct directory, fixed bug in build/sbt-launch-lib.bash to correctly pull the sbt version be11317 [Brennon York] added switch to silence download progress only if AMPLAB_JENKINS is set 28d0a99 [Brennon York] updated to remove the python dependency, uses grep instead 7e785a6 [Brennon York] added silent and quiet flags to curl and wget respectively, added single echo output to denote start of a download if download is needed 14a5da0 [Brennon York] removed unnecessary zinc output on startup 1af4a94 [Brennon York] fixed bug with uppercase vs lowercase variable 3e8b9b3 [Brennon York] updated to properly only restart zinc if it was freshly installed a680d12 [Brennon York] Added comments to functions and tested various mvn calls bb8cc9d [Brennon York] removed package files ef017e6 [Brennon York] removed OS complexities, setup generic install_app call, removed extra file complexities, removed help, removed forced install (defaults now), removed double-dash from cli 07bf018 [Brennon York] Updated to specifically handle pulling down the correct scala version f914dea [Brennon York] Beginning final portions of localized scala home 69c4e44 [Brennon York] working linux and osx installers for purely local mvn build 4a1609c [Brennon York] finalizing working linux install for maven to local ./build/apache-maven folder cbfcc68 [Brennon York] Changed the default sbt/sbt to build/sbt and added a build/mvn which will automatically download, install, and execute maven with zinc for easier build capability
* [SPARK-4860][pyspark][sql] speeding up `sample()` and `takeSample()`jbencook2014-12-231-0/+28
| | | | | | | | | | | | | | | | | This PR modifies the python `SchemaRDD` to use `sample()` and `takeSample()` from Scala instead of the slower python implementations from `rdd.py`. This is worthwhile because the `Row`'s are already serialized as Java objects. In order to use the faster `takeSample()`, a `takeSampleToPython()` method was implemented in `SchemaRDD.scala` following the pattern of `collectToPython()`. Author: jbencook <jbenjamincook@gmail.com> Author: J. Benjamin Cook <jbenjamincook@gmail.com> Closes #3764 from jbencook/master and squashes the following commits: 6fbc769 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing sloppy indentation for takeSampleToPython() arguments 5170da2 [J. Benjamin Cook] [SPARK-4860][pyspark][sql] fixing typo: from RDD to SchemaRDD de22f70 [jbencook] [SPARK-4860][pyspark][sql] using sample() method from JavaSchemaRDD b916442 [jbencook] [SPARK-4860][pyspark][sql] adding sample() to JavaSchemaRDD 020cbdf [jbencook] [SPARK-4860][pyspark][sql] using Scala implementations of `sample()` and `takeSample()`
* [SPARK-4822] Use sphinx tags for Python doc annotationslewuathe2014-12-176-17/+17
| | | | | | | | | | | | Modify python annotations for sphinx. There is no change to build process from. https://github.com/apache/spark/blob/master/docs/README.md Author: lewuathe <lewuathe@me.com> Closes #3685 from Lewuathe/sphinx-tag-for-pydoc and squashes the following commits: 88a0fd9 [lewuathe] [SPARK-4822] Fix DevelopApi and WARN tags 3d7a398 [lewuathe] [SPARK-4822] Use sphinx tags for Python doc annotations
* [SPARK-4821] [mllib] [python] [docs] Fix for pyspark.mllib.rand docJoseph K. Bradley2014-12-173-30/+5
| | | | | | | | | | | | | | | | | + small doc edit + include edit to make IntelliJ happy CC: davies mengxr Note to davies -- this does not fix the "WARNING: Literal block expected; none found." warnings since that seems to involve spacing which IntelliJ does not like. (Those warnings occur when generating the Python docs.) Author: Joseph K. Bradley <joseph@databricks.com> Closes #3669 from jkbradley/python-warnings and squashes the following commits: 4587868 [Joseph K. Bradley] fixed warning 8cb073c [Joseph K. Bradley] Updated based on davies recommendation c51eca4 [Joseph K. Bradley] Updated rst file for pyspark.mllib.rand doc. Small doc edit. Small include edit to make IntelliJ happy.
* [SPARK-4866] support StructType as key in MapTypeDavies Liu2014-12-162-7/+18
| | | | | | | | | | | This PR brings support of using StructType(and other hashable types) as key in MapType. Author: Davies Liu <davies@databricks.com> Closes #3714 from davies/fix_struct_in_map and squashes the following commits: 68585d7 [Davies Liu] fix primitive types in MapType 9601534 [Davies Liu] support StructType as key in MapType
* [SPARK-4855][mllib] testing the Chi-squared hypothesis testjbencook2014-12-161-1/+99
| | | | | | | | | | | | | | | | | | This PR tests the pyspark Chi-squared hypothesis test from this commit: c8abddc5164d8cf11cdede6ab3d5d1ea08028708 and moves some of the error messaging in to python. It is a port of the Scala tests here: [HypothesisTestSuite.scala](https://github.com/apache/spark/blob/master/mllib/src/test/scala/org/apache/spark/mllib/stat/HypothesisTestSuite.scala) Hopefully, SPARK-2980 can be closed. Author: jbencook <jbenjamincook@gmail.com> Closes #3679 from jbencook/master and squashes the following commits: 44078e0 [jbencook] checking that bad input throws the correct exceptions f12ee10 [jbencook] removing checks for ValueError since input tests are on the Scala side 7536cf1 [jbencook] removing python checks for invalid input a17ee84 [jbencook] [SPARK-2980][mllib] adding unit tests for the pyspark chi-squared test 3aeb0d9 [jbencook] [SPARK-2980][mllib] bringing Chi-squared error messages to the python side
* [SPARK-4841] fix zip with textFile()Davies Liu2014-12-153-14/+26
| | | | | | | | | | | | | | 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()
* [SPARK-4494][mllib] IDFModel.transform() add support for single vectorYuu ISHIKAWA2014-12-151-7/+15
| | | | | | | | | | | | | | I improved `IDFModel.transform` to allow using a single vector. [[SPARK-4494] IDFModel.transform() add support for single vector - ASF JIRA](https://issues.apache.org/jira/browse/SPARK-4494) Author: Yuu ISHIKAWA <yuu.ishikawa@gmail.com> Closes #3603 from yu-iskw/idf and squashes the following commits: 256ff3d [Yuu ISHIKAWA] Fix typo a3bf566 [Yuu ISHIKAWA] - Fix typo - Optimize import order - Aggregate the assertion tests - Modify `IDFModel.transform` API for pyspark d25e49b [Yuu ISHIKAWA] Add the implementation of `IDFModel.transform` for a term frequency vector
* [SPARK-4580] [SPARK-4610] [mllib] [docs] Documentation for tree ensembles + ↵Joseph K. Bradley2014-12-041-3/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | DecisionTree API fix Major changes: * Added programming guide sections for tree ensembles * Added examples for tree ensembles * Updated DecisionTree programming guide with more info on parameters * **API change**: Standardized the tree parameter for the number of classes (for classification) Minor changes: * Updated decision tree documentation * Updated existing tree and tree ensemble examples * Use train/test split, and compute test error instead of training error. * Fixed decision_tree_runner.py to actually use the number of classes it computes from data. (small bug fix) Note: I know this is a lot of lines, but most is covered by: * Programming guide sections for gradient boosting and random forests. (The changes are probably best viewed by generating the docs locally.) * New examples (which were copied from the programming guide) * The "numClasses" renaming I have run all examples and relevant unit tests. CC: mengxr manishamde codedeft Author: Joseph K. Bradley <joseph@databricks.com> Author: Joseph K. Bradley <joseph.kurata.bradley@gmail.com> Closes #3461 from jkbradley/ensemble-docs and squashes the following commits: 70a75f3 [Joseph K. Bradley] updated forest vs boosting comparison d1de753 [Joseph K. Bradley] Added note about toString and toDebugString for DecisionTree to migration guide 8e87f8f [Joseph K. Bradley] Combined GBT and RandomForest guides into one ensembles guide 6fab846 [Joseph K. Bradley] small fixes based on review b9f8576 [Joseph K. Bradley] updated decision tree doc 375204c [Joseph K. Bradley] fixed python style 2b60b6e [Joseph K. Bradley] merged Java RandomForest examples into 1 file. added header. Fixed small bug in same example in the programming guide. 706d332 [Joseph K. Bradley] updated python DT runner to print full model if it is small c76c823 [Joseph K. Bradley] added migration guide for mllib abe5ed7 [Joseph K. Bradley] added examples for random forest in Java and Python to examples folder 07fc11d [Joseph K. Bradley] Renamed numClassesForClassification to numClasses everywhere in trees and ensembles. This is a breaking API change, but it was necessary to correct an API inconsistency in Spark 1.1 (where Python DecisionTree used numClasses but Scala used numClassesForClassification). cdfdfbc [Joseph K. Bradley] added examples for GBT 6372a2b [Joseph K. Bradley] updated decision tree examples to use random split. tested all of them. ad3e695 [Joseph K. Bradley] added gbt and random forest to programming guide. still need to update their examples
* [SPARK-4548] []SPARK-4517] improve performance of python broadcastDavies Liu2014-11-245-233/+80
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* [SPARK-4578] fix asDict() with nested Row()Davies Liu2014-11-242-4/+5
| | | | | | | | | | 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()
* [SPARK-4562] [MLlib] speedup vectorDavies Liu2014-11-242-26/+53
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR change the underline array of DenseVector to numpy.ndarray to avoid the conversion, because most of the users will using numpy.array. It also improve the serialization of DenseVector. Before this change: trial | trainingTime | testTime -------|--------|-------- 0 | 5.126 | 1.786 1 |2.698 |1.693 After the change: trial | trainingTime | testTime -------|--------|-------- 0 |4.692 |0.554 1 |2.307 |0.525 This could partially fix the performance regression during test. Author: Davies Liu <davies@databricks.com> Closes #3420 from davies/ser2 and squashes the following commits: 0e1e6f3 [Davies Liu] fix tests 426f5db [Davies Liu] impove toArray() 44707ec [Davies Liu] add name for ISO-8859-1 fa7d791 [Davies Liu] address comments 1cfb137 [Davies Liu] handle zero sparse vector 2548ee2 [Davies Liu] fix tests 9e6389d [Davies Liu] bugfix 470f702 [Davies Liu] speed up DenseMatrix f0d3c40 [Davies Liu] speedup SparseVector ef6ce70 [Davies Liu] speed up dense vector
* [SPARK-4531] [MLlib] cache serialized java objectDavies Liu2014-11-214-13/+8
| | | | | | | | | | | | | | | | | | | The Pyrolite is pretty slow (comparing to the adhoc serializer in 1.1), it cause much performance regression in 1.2, because we cache the serialized Python object in JVM, deserialize them into Java object in each step. This PR change to cache the deserialized JavaRDD instead of PythonRDD to avoid the deserialization of Pyrolite. It should have similar memory usage as before, but much faster. Author: Davies Liu <davies@databricks.com> Closes #3397 from davies/cache and squashes the following commits: 7f6e6ce [Davies Liu] Update -> Updater 4b52edd [Davies Liu] using named argument 63b984e [Davies Liu] fix 7da0332 [Davies Liu] add unpersist() dff33e1 [Davies Liu] address comments c2bdfc2 [Davies Liu] refactor d572f00 [Davies Liu] Merge branch 'master' into cache f1063e1 [Davies Liu] cache serialized java object
* [SPARK-4477] [PySpark] remove numpy from RDDSamplerDavies Liu2014-11-202-69/+40
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | In RDDSampler, it try use numpy to gain better performance for possion(), but the number of call of random() is only (1+faction) * N in the pure python implementation of possion(), so there is no much performance gain from numpy. numpy is not a dependent of pyspark, so it maybe introduce some problem, such as there is no numpy installed in slaves, but only installed master, as reported in SPARK-927. It also complicate the code a lot, so we may should remove numpy from RDDSampler. I also did some benchmark to verify that: ``` >>> from pyspark.mllib.random import RandomRDDs >>> rdd = RandomRDDs.uniformRDD(sc, 1 << 20, 1).cache() >>> rdd.count() # cache it >>> rdd.sample(True, 0.9).count() # measure this line ``` the results: |withReplacement | random | numpy.random | ------- | ------------ | ------- |True | 1.5 s| 1.4 s| |False| 0.6 s | 0.8 s| closes #2313 Note: this patch including some commits that not mirrored to github, it will be OK after it catches up. Author: Davies Liu <davies@databricks.com> Author: Xiangrui Meng <meng@databricks.com> Closes #3351 from davies/numpy and squashes the following commits: 5c438d7 [Davies Liu] fix comment c5b9252 [Davies Liu] Merge pull request #1 from mengxr/SPARK-4477 98eb31b [Xiangrui Meng] make poisson sampling slightly faster ee17d78 [Davies Liu] remove = for float 13f7b05 [Davies Liu] Merge branch 'master' of http://git-wip-us.apache.org/repos/asf/spark into numpy f583023 [Davies Liu] fix tests 51649f5 [Davies Liu] remove numpy in RDDSampler 78bf997 [Davies Liu] fix tests, do not use numpy in randomSplit, no performance gain f5fdf63 [Davies Liu] fix bug with int in weights 4dfa2cd [Davies Liu] refactor f866bcf [Davies Liu] remove unneeded change c7a2007 [Davies Liu] switch to python implementation 95a48ac [Davies Liu] Merge branch 'master' of github.com:apache/spark into randomSplit 0d9b256 [Davies Liu] refactor 1715ee3 [Davies Liu] address comments 41fce54 [Davies Liu] randomSplit()
* [SPARK-4439] [MLlib] add python api for random forestDavies Liu2014-11-202-23/+221
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ``` class RandomForestModel | A model trained by RandomForest | | numTrees(self) | Get number of trees in forest. | | predict(self, x) | Predict values for a single data point or an RDD of points using the model trained. | | toDebugString(self) | Full model | | totalNumNodes(self) | Get total number of nodes, summed over all trees in the forest. | class RandomForest | trainClassifier(cls, data, numClassesForClassification, categoricalFeaturesInfo, numTrees, featureSubsetStrategy='auto', impurity='gini', maxDepth=4, maxBins=32, seed=None): | Method to train a decision tree model for binary or multiclass classification. | | :param data: Training dataset: RDD of LabeledPoint. | Labels should take values {0, 1, ..., numClasses-1}. | :param numClassesForClassification: number of classes for classification. | :param categoricalFeaturesInfo: Map storing arity of categorical features. | E.g., an entry (n -> k) indicates that feature n is categorical | with k categories indexed from 0: {0, 1, ..., k-1}. | :param numTrees: Number of trees in the random forest. | :param featureSubsetStrategy: Number of features to consider for splits at each node. | Supported: "auto" (default), "all", "sqrt", "log2", "onethird". | If "auto" is set, this parameter is set based on numTrees: | if numTrees == 1, set to "all"; | if numTrees > 1 (forest) set to "sqrt". | :param impurity: Criterion used for information gain calculation. | Supported values: "gini" (recommended) or "entropy". | :param maxDepth: Maximum depth of the tree. E.g., depth 0 means 1 leaf node; depth 1 means | 1 internal node + 2 leaf nodes. (default: 4) | :param maxBins: maximum number of bins used for splitting features (default: 100) | :param seed: Random seed for bootstrapping and choosing feature subsets. | :return: RandomForestModel that can be used for prediction | | trainRegressor(cls, data, categoricalFeaturesInfo, numTrees, featureSubsetStrategy='auto', impurity='variance', maxDepth=4, maxBins=32, seed=None): | Method to train a decision tree model for regression. | | :param data: Training dataset: RDD of LabeledPoint. | Labels are real numbers. | :param categoricalFeaturesInfo: Map storing arity of categorical features. | E.g., an entry (n -> k) indicates that feature n is categorical | with k categories indexed from 0: {0, 1, ..., k-1}. | :param numTrees: Number of trees in the random forest. | :param featureSubsetStrategy: Number of features to consider for splits at each node. | Supported: "auto" (default), "all", "sqrt", "log2", "onethird". | If "auto" is set, this parameter is set based on numTrees: | if numTrees == 1, set to "all"; | if numTrees > 1 (forest) set to "onethird". | :param impurity: Criterion used for information gain calculation. | Supported values: "variance". | :param maxDepth: Maximum depth of the tree. E.g., depth 0 means 1 leaf node; depth 1 means | 1 internal node + 2 leaf nodes.(default: 4) | :param maxBins: maximum number of bins used for splitting features (default: 100) | :param seed: Random seed for bootstrapping and choosing feature subsets. | :return: RandomForestModel that can be used for prediction | ``` Author: Davies Liu <davies@databricks.com> Closes #3320 from davies/forest and squashes the following commits: 8003dfc [Davies Liu] reorder 53cf510 [Davies Liu] fix docs 4ca593d [Davies Liu] fix docs e0df852 [Davies Liu] fix docs 0431746 [Davies Liu] rebased 2b6f239 [Davies Liu] Merge branch 'master' of github.com:apache/spark into forest 885abee [Davies Liu] address comments dae7fc0 [Davies Liu] address comments 89a000f [Davies Liu] fix docs 565d476 [Davies Liu] add python api for random forest
* [SPARK-4228][SQL] SchemaRDD to JSONDan McClary2014-11-201-1/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Here's a simple fix for SchemaRDD to JSON. Author: Dan McClary <dan.mcclary@gmail.com> Closes #3213 from dwmclary/SPARK-4228 and squashes the following commits: d714e1d [Dan McClary] fixed PEP 8 error cac2879 [Dan McClary] move pyspark comment and doctest to correct location f9471d3 [Dan McClary] added pyspark doc and doctest 6598cee [Dan McClary] adding complex type queries 1a5fd30 [Dan McClary] removing SPARK-4228 from SQLQuerySuite 4a651f0 [Dan McClary] cleaned PEP and Scala style failures. Moved tests to JsonSuite 47ceff6 [Dan McClary] cleaned up scala style issues 2ee1e70 [Dan McClary] moved rowToJSON to JsonRDD 4387dd5 [Dan McClary] Added UserDefinedType, cleaned up case formatting 8f7bfb6 [Dan McClary] Map type added to SchemaRDD.toJSON 1b11980 [Dan McClary] Map and UserDefinedTypes partially done 11d2016 [Dan McClary] formatting and unicode deserialization default fixed 6af72d1 [Dan McClary] deleted extaneous comment 4d11c0c [Dan McClary] JsonFactory rewrite of toJSON for SchemaRDD 149dafd [Dan McClary] wrapped scala toJSON in sql.py 5e5eb1b [Dan McClary] switched to Jackson for JSON processing 6c94a54 [Dan McClary] added toJSON to pyspark SchemaRDD aaeba58 [Dan McClary] added toJSON to pyspark SchemaRDD 1d171aa [Dan McClary] upated missing brace on if statement 319e3ba [Dan McClary] updated to upstream master with merged SPARK-4228 424f130 [Dan McClary] tests pass, ready for pull and PR 626a5b1 [Dan McClary] added toJSON to SchemaRDD f7d166a [Dan McClary] added toJSON method 5d34e37 [Dan McClary] merge resolved d6d19e9 [Dan McClary] pr example
* [SPARK-4384] [PySpark] improve sort spillingDavies Liu2014-11-191-1/+10
| | | | | | | | | | | | If there some big broadcasts (or other object) in Python worker, the free memory could be used for sorting will be too small, then it will keep spilling small files into disks, finally failed with too many open files. This PR try to delay the spilling until the used memory goes over limit and start to increase since last spilling, it will increase the size of spilling files, improve the stability and performance in this cases. (We also do this in ExternalAggregator). Author: Davies Liu <davies@databricks.com> Closes #3252 from davies/sort and squashes the following commits: 711fb6c [Davies Liu] improve sort spilling
* [DOC][PySpark][Streaming] Fix docstring for sphinxKen Takagiwa2014-11-191-2/+2
| | | | | | | | | | | This commit should be merged for 1.2 release. cc tdas Author: Ken Takagiwa <ugw.gi.world@gmail.com> Closes #3311 from giwa/patch-3 and squashes the following commits: ab474a8 [Ken Takagiwa] [DOC][PySpark][Streaming] Fix docstring for sphinx
* [SPARK-4327] [PySpark] Python API for RDD.randomSplit()Davies Liu2014-11-182-3/+41
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ``` pyspark.RDD.randomSplit(self, weights, seed=None) Randomly splits this RDD with the provided weights. :param weights: weights for splits, will be normalized if they don't sum to 1 :param seed: random seed :return: split RDDs in an list >>> rdd = sc.parallelize(range(10), 1) >>> rdd1, rdd2, rdd3 = rdd.randomSplit([0.4, 0.6, 1.0], 11) >>> rdd1.collect() [3, 6] >>> rdd2.collect() [0, 5, 7] >>> rdd3.collect() [1, 2, 4, 8, 9] ``` Author: Davies Liu <davies@databricks.com> Closes #3193 from davies/randomSplit and squashes the following commits: 78bf997 [Davies Liu] fix tests, do not use numpy in randomSplit, no performance gain f5fdf63 [Davies Liu] fix bug with int in weights 4dfa2cd [Davies Liu] refactor f866bcf [Davies Liu] remove unneeded change c7a2007 [Davies Liu] switch to python implementation 95a48ac [Davies Liu] Merge branch 'master' of github.com:apache/spark into randomSplit 0d9b256 [Davies Liu] refactor 1715ee3 [Davies Liu] address comments 41fce54 [Davies Liu] randomSplit()
* [SPARK-3721] [PySpark] broadcast objects larger than 2GDavies Liu2014-11-186-17/+239
| | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* [SPARK-4306] [MLlib] Python API for LogisticRegressionWithLBFGSDavies Liu2014-11-181-4/+53
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ``` class LogisticRegressionWithLBFGS | train(cls, data, iterations=100, initialWeights=None, corrections=10, tolerance=0.0001, regParam=0.01, intercept=False) | Train a logistic regression model on the given data. | | :param data: The training data, an RDD of LabeledPoint. | :param iterations: The number of iterations (default: 100). | :param initialWeights: The initial weights (default: None). | :param regParam: The regularizer parameter (default: 0.01). | :param regType: The type of regularizer used for training | our model. | :Allowed values: | - "l1" for using L1 regularization | - "l2" for using L2 regularization | - None for no regularization | (default: "l2") | :param intercept: Boolean parameter which indicates the use | or not of the augmented representation for | training data (i.e. whether bias features | are activated or not). | :param corrections: The number of corrections used in the LBFGS update (default: 10). | :param tolerance: The convergence tolerance of iterations for L-BFGS (default: 1e-4). | | >>> data = [ | ... LabeledPoint(0.0, [0.0, 1.0]), | ... LabeledPoint(1.0, [1.0, 0.0]), | ... ] | >>> lrm = LogisticRegressionWithLBFGS.train(sc.parallelize(data)) | >>> lrm.predict([1.0, 0.0]) | 1 | >>> lrm.predict([0.0, 1.0]) | 0 | >>> lrm.predict(sc.parallelize([[1.0, 0.0], [0.0, 1.0]])).collect() | [1, 0] ``` Author: Davies Liu <davies@databricks.com> Closes #3307 from davies/lbfgs and squashes the following commits: 34bd986 [Davies Liu] Merge branch 'master' of http://git-wip-us.apache.org/repos/asf/spark into lbfgs 5a945a6 [Davies Liu] address comments 941061b [Davies Liu] Merge branch 'master' of github.com:apache/spark into lbfgs 03e5543 [Davies Liu] add it to docs ed2f9a8 [Davies Liu] add regType 76cd1b6 [Davies Liu] reorder arguments 4429a74 [Davies Liu] Update classification.py 9252783 [Davies Liu] python api for LogisticRegressionWithLBFGS
* [SPARK-4396] allow lookup by index in Python's RatingXiangrui Meng2014-11-181-11/+15
| | | | | | | | | | | | | | | | | | In PySpark, ALS can take an RDD of (user, product, rating) tuples as input. However, model.predict outputs an RDD of Rating. So on the input side, users can use r[0], r[1], r[2], while on the output side, users have to use r.user, r.product, r.rating. We should allow lookup by index in Rating by making Rating a namedtuple. davies <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3261) <!-- Reviewable:end --> Author: Xiangrui Meng <meng@databricks.com> Closes #3261 from mengxr/SPARK-4396 and squashes the following commits: 543aef0 [Xiangrui Meng] use named tuple to implement ALS 0b61bae [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-4396 d3bd7d4 [Xiangrui Meng] allow lookup by index in Python's Rating
* [SPARK-4435] [MLlib] [PySpark] improve classificationDavies Liu2014-11-181-29/+106
| | | | | | | | | | | | | | | This PR add setThrehold() and clearThreshold() for LogisticRegressionModel and SVMModel, also support RDD of vector in LogisticRegressionModel.predict(), SVNModel.predict() and NaiveBayes.predict() Author: Davies Liu <davies@databricks.com> Closes #3305 from davies/setThreshold and squashes the following commits: d0b835f [Davies Liu] Merge branch 'master' of github.com:apache/spark into setThreshold e4acd76 [Davies Liu] address comments 2231a5f [Davies Liu] bugfix 7bd9009 [Davies Liu] address comments 0b0a8a7 [Davies Liu] address comments c1e5573 [Davies Liu] improve classification
* [SPARK-4415] [PySpark] JVM should exit after Python exitDavies Liu2014-11-141-1/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | When JVM is started in a Python process, it should exit once the stdin is closed. test: add spark.driver.memory in conf/spark-defaults.conf ``` daviesdm:~/work/spark$ cat conf/spark-defaults.conf spark.driver.memory 8g daviesdm:~/work/spark$ bin/pyspark >>> quit daviesdm:~/work/spark$ jps 4931 Jps 286 daviesdm:~/work/spark$ python wc.py 943738 0.719928026199 daviesdm:~/work/spark$ jps 286 4990 Jps ``` Author: Davies Liu <davies@databricks.com> Closes #3274 from davies/exit and squashes the following commits: df0e524 [Davies Liu] address comments ce8599c [Davies Liu] address comments 050651f [Davies Liu] JVM should exit after Python exit
* [SPARK-4398][PySpark] specialize sc.parallelize(xrange)Xiangrui Meng2014-11-141-4/+21
| | | | | | | | | | | | | `sc.parallelize(range(1 << 20), 1).count()` may take 15 seconds to finish and the rdd object stores the entire list, making task size very large. This PR adds a specialized version for xrange. JoshRosen davies Author: Xiangrui Meng <meng@databricks.com> Closes #3264 from mengxr/SPARK-4398 and squashes the following commits: 8953c41 [Xiangrui Meng] follow davies' suggestion cbd58e3 [Xiangrui Meng] specialize sc.parallelize(xrange)
* [SPARK-4372][MLLIB] Make LR and SVM's default parameters consistent in Scala ↵Xiangrui Meng2014-11-132-35/+37
| | | | | | | | | | | | | | | | | | and Python The current default regParam is 1.0 and regType is claimed to be none in Python (but actually it is l2), while regParam = 0.0 and regType is L2 in Scala. We should make the default values consistent. This PR sets the default regType to L2 and regParam to 0.01. Note that the default regParam value in LIBLINEAR (and hence scikit-learn) is 1.0. However, we use average loss instead of total loss in our formulation. Hence regParam=1.0 is definitely too heavy. In LinearRegression, we set regParam=0.0 and regType=None, because we have separate classes for Lasso and Ridge, both of which use regParam=0.01 as the default. davies atalwalkar Author: Xiangrui Meng <meng@databricks.com> Closes #3232 from mengxr/SPARK-4372 and squashes the following commits: 9979837 [Xiangrui Meng] update Ridge/Lasso to use default regParam 0.01 cast input arguments d3ba096 [Xiangrui Meng] change 'none' back to None 1909a6e [Xiangrui Meng] change default regParam to 0.01 and regType to L2 in LR and SVM
* [SPARK-4348] [PySpark] [MLlib] rename random.py to rand.pyDavies Liu2014-11-136-20/+38
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR rename random.py to rand.py to avoid the side affects of conflict with random module, but still keep the same interface as before. ``` >>> from pyspark.mllib.random import RandomRDDs ``` ``` $ pydoc pyspark.mllib.random Help on module random in pyspark.mllib: NAME random - Python package for random data generation. FILE /Users/davies/work/spark/python/pyspark/mllib/rand.py CLASSES __builtin__.object pyspark.mllib.random.RandomRDDs class RandomRDDs(__builtin__.object) | Generator methods for creating RDDs comprised of i.i.d samples from | some distribution. | | Static methods defined here: | | normalRDD(sc, size, numPartitions=None, seed=None) ``` cc mengxr reference link: http://xion.org.pl/2012/05/06/hacking-python-imports/ Author: Davies Liu <davies@databricks.com> Closes #3216 from davies/random and squashes the following commits: 7ac4e8b [Davies Liu] rename random.py to rand.py
* [SPARK-4369] [MLLib] fix TreeModel.predict() with RDDDavies Liu2014-11-121-12/+14
| | | | | | | | | | | | Fix TreeModel.predict() with RDD, added tests for it. (Also checked that other models don't have this issue) Author: Davies Liu <davies@databricks.com> Closes #3230 from davies/predict and squashes the following commits: 81172aa [Davies Liu] fix predict
* [SPARK-4324] [PySpark] [MLlib] support numpy.array for all MLlib APIDavies Liu2014-11-107-32/+105
| | | | | | | | | | | | | | | This PR check all of the existing Python MLlib API to make sure that numpy.array is supported as Vector (also RDD of numpy.array). It also improve some docstring and doctest. cc mateiz mengxr Author: Davies Liu <davies@databricks.com> Closes #3189 from davies/numpy and squashes the following commits: d5057c4 [Davies Liu] fix tests 6987611 [Davies Liu] support numpy.array for all MLlib API
* [MLLIB] [PYTHON] SPARK-4221: Expose nonnegative ALS in the python APIMichelangelo D'Agostino2014-11-071-15/+25
| | | | | | | | | | | | | | | SPARK-1553 added alternating nonnegative least squares to MLLib, however it's not possible to access it via the python API. This pull request resolves that. Author: Michelangelo D'Agostino <mdagostino@civisanalytics.com> Closes #3095 from mdagost/python_nmf and squashes the following commits: a6743ad [Michelangelo D'Agostino] Use setters instead of static methods in PythonMLLibAPI. Remove the new static methods I added. Set seed in tests. Change ratings to ratingsRDD in both train and trainImplicit for consistency. 7cffd39 [Michelangelo D'Agostino] Swapped nonnegative and seed in a few more places. 3fdc851 [Michelangelo D'Agostino] Moved seed to the end of the python parameter list. bdcc154 [Michelangelo D'Agostino] Change seed type to java.lang.Long so that it can handle null. cedf043 [Michelangelo D'Agostino] Added in ability to set the seed from python and made that play nice with the nonnegative changes. Also made the python ALS tests more exact. a72fdc9 [Michelangelo D'Agostino] Expose nonnegative ALS in the python API.
* [SPARK-4304] [PySpark] Fix sort on empty RDDDavies Liu2014-11-072-0/+5
| | | | | | | | | | | | | 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
* [SPARK-4186] add binaryFiles and binaryRecords in PythonDavies Liu2014-11-062-1/+50
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
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