SchemaRDD works with ALS.train in 1.2, so we should continue support DataFrames for compatibility. coderxiang

Author: Xiangrui Meng <meng@databricks.com>

Closes #5619 from mengxr/SPARK-7036 and squashes the following commits:

dfcaf5a [Xiangrui Meng] ALS.train should support DataFrames in PySpark

This PR update PySpark to support Python 3 (tested with 3.4).

Known issue: unpickle array from Pyrolite is broken in Python 3, those tests are skipped.

TODO: ec2/spark-ec2.py is not fully tested with python3.

Author: Davies Liu <davies@databricks.com>
Author: twneale <twneale@gmail.com>
Author: Josh Rosen <joshrosen@databricks.com>

Closes #5173 from davies/python3 and squashes the following commits:

d7d6323 [Davies Liu] fix tests
6c52a98 [Davies Liu] fix mllib test
99e334f [Davies Liu] update timeout
b716610 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
cafd5ec [Davies Liu] adddress comments from @mengxr
bf225d7 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
179fc8d [Davies Liu] tuning flaky tests
8c8b957 [Davies Liu] fix ResourceWarning in Python 3
5c57c95 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
4006829 [Davies Liu] fix test
2fc0066 [Davies Liu] add python3 path
71535e9 [Davies Liu] fix xrange and divide
5a55ab4 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
125f12c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ed498c8 [Davies Liu] fix compatibility with python 3
820e649 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
e8ce8c9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ad7c374 [Davies Liu] fix mllib test and warning
ef1fc2f [Davies Liu] fix tests
4eee14a [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
20112ff [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
59bb492 [Davies Liu] fix tests
1da268c [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
ca0fdd3 [Davies Liu] fix code style
9563a15 [Davies Liu] add imap back for python 2
0b1ec04 [Davies Liu] make python examples work with Python 3
d2fd566 [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
a716d34 [Davies Liu] test with python 3.4
f1700e8 [Davies Liu] fix test in python3
671b1db [Davies Liu] fix test in python3
692ff47 [Davies Liu] fix flaky test
7b9699f [Davies Liu] invalidate import cache for Python 3.3+
9c58497 [Davies Liu] fix kill worker
309bfbf [Davies Liu] keep compatibility
5707476 [Davies Liu] cleanup, fix hash of string in 3.3+
8662d5b [Davies Liu] Merge branch 'master' of github.com:apache/spark into python3
f53e1f0 [Davies Liu] fix tests
70b6b73 [Davies Liu] compile ec2/spark_ec2.py in python 3
a39167e [Davies Liu] support customize class in __main__
814c77b [Davies Liu] run unittests with python 3
7f4476e [Davies Liu] mllib tests passed
d737924 [Davies Liu] pass ml tests
375ea17 [Davies Liu] SQL tests pass
6cc42a9 [Davies Liu] rename
431a8de [Davies Liu] streaming tests pass
78901a7 [Davies Liu] fix hash of serializer in Python 3
24b2f2e [Davies Liu] pass all RDD tests
35f48fe [Davies Liu] run future again
1eebac2 [Davies Liu] fix conflict in ec2/spark_ec2.py
6e3c21d [Davies Liu] make cloudpickle work with Python3
2fb2db3 [Josh Rosen] Guard more changes behind sys.version; still doesn't run
1aa5e8f [twneale] Turned out `pickle.DictionaryType is dict` == True, so swapped it out
7354371 [twneale] buffer --> memoryview  I'm not super sure if this a valid change, but the 2.7 docs recommend using memoryview over buffer where possible, so hoping it'll work.
b69ccdf [twneale] Uses the pure python pickle._Pickler instead of c-extension _pickle.Pickler. It appears pyspark 2.7 uses the pure python pickler as well, so this shouldn't degrade pickling performance (?).
f40d925 [twneale] xrange --> range
e104215 [twneale] Replaces 2.7 types.InstsanceType with 3.4 `object`....could be horribly wrong depending on how types.InstanceType is used elsewhere in the package--see http://bugs.python.org/issue8206
79de9d0 [twneale] Replaces python2.7 `file` with 3.4 _io.TextIOWrapper
2adb42d [Josh Rosen] Fix up some import differences between Python 2 and 3
854be27 [Josh Rosen] Run `futurize` on Python code:
7c5b4ce [Josh Rosen] Remove Python 3 check in shell.py.

This PR changes lambda scaling from number of users/items to number of explicit ratings. The latter is the behavior in 1.2. Slight refactor of NormalEquation to make it independent of ALS models. srowen codexiang

Author: Xiangrui Meng <meng@databricks.com>

Closes #5314 from mengxr/SPARK-6642 and squashes the following commits:

dc655a1 [Xiangrui Meng] relax python tests
f410df2 [Xiangrui Meng] use 1.2 scaling and remove addImplicit from NormalEquation

This fixes `predictAll` after load. jkbradley

Author: Xiangrui Meng <meng@databricks.com>

Closes #5243 from mengxr/SPARK-6571 and squashes the following commits:

82dcaa7 [Xiangrui Meng] use wrapper in MatrixFactorizationModel.load

Similar to `MatrixFactorizaionModel`, we only need wrappers to support save/load for tree models in Python.

jkbradley

Author: Xiangrui Meng <meng@databricks.com>

Closes #4854 from mengxr/SPARK-6097 and squashes the following commits:

4586a4d [Xiangrui Meng] fix more typos
8ebcac2 [Xiangrui Meng] fix python style
91172d8 [Xiangrui Meng] fix typos
201b3b9 [Xiangrui Meng] update user guide
b5158e2 [Xiangrui Meng] support tree model save/load in PySpark/MLlib

A simple wrapper to save/load `MatrixFactorizationModel` in Python. jkbradley

Author: Xiangrui Meng <meng@databricks.com>

Closes #4811 from mengxr/SPARK-5991 and squashes the following commits:

f135dac [Xiangrui Meng] update save doc
57e5200 [Xiangrui Meng] address comments
06140a4 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-5991
282ec8d [Xiangrui Meng] support save/load in PySpark's ALS

The only issue is that `analyzeBlock` is removed, which was marked as a developer API. I didn't change other tests in the ALSSuite under `spark.mllib` to ensure that the implementation is correct.

CC: srowen coderxiang

Author: Xiangrui Meng <meng@databricks.com>

Closes #4321 from mengxr/SPARK-5536 and squashes the following commits:

5a3cee8 [Xiangrui Meng] update python tests that are too strict
e840acf [Xiangrui Meng] ignore scala style check for ALS.train
e9a721c [Xiangrui Meng] update mima excludes
9ee6a36 [Xiangrui Meng] merge master
9a8aeac [Xiangrui Meng] update tests
d8c3271 [Xiangrui Meng] remove analyzeBlocks
d68eee7 [Xiangrui Meng] add checkpoint to new ALS
22a56f8 [Xiangrui Meng] wrap old ALS
c387dff [Xiangrui Meng] support random seed
3bdf24b [Xiangrui Meng] make storage level configurable in the new ALS

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

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 -->
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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

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

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.

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.

Create several helper functions to call MLlib Java API, convert the arguments to Java type and convert return value to Python object automatically, this simplify serialization in MLlib Python API very much.

After this, the MLlib Python API does not need to deal with serialization details anymore, it's easier to add new API.

cc mengxr

Author: Davies Liu <davies@databricks.com>

Closes #2995 from davies/cleanup and squashes the following commits:

8fa6ec6 [Davies Liu] address comments
16b85a0 [Davies Liu] Merge branch 'master' of github.com:apache/spark into cleanup
43743e5 [Davies Liu] bugfix
731331f [Davies Liu] simplify serialization in MLlib Python API

https://issues.apache.org/jira/browse/SPARK-3770

We need access to the underlying latent user features from python. However, the userFeatures RDD from the MatrixFactorizationModel isn't accessible from the python bindings. I've added a method to the underlying scala class to turn the RDD[(Int, Array[Double])] to an RDD[String]. This is then accessed from the python recommendation.py

Author: Michelangelo D'Agostino <mdagostino@civisanalytics.com>

Closes #2636 from mdagost/mf_user_features and squashes the following commits:

c98f9e2 [Michelangelo D'Agostino] Added unit tests for userFeatures and productFeatures and merged master.
d5eadf8 [Michelangelo D'Agostino] Merge branch 'master' into mf_user_features
2481a2a [Michelangelo D'Agostino] Merged master and resolved conflict.
a6ffb96 [Michelangelo D'Agostino] Eliminated a function from our first approach to this problem that is no longer needed now that we added the fromTuple2RDD function.
2aa1bf8 [Michelangelo D'Agostino] Implemented a function called fromTuple2RDD in PythonMLLibAPI and used it to expose the MF userFeatures and productFeatures in python.
34cb2a2 [Michelangelo D'Agostino] A couple of lint cleanups and a comment.
cdd98e3 [Michelangelo D'Agostino] It's working now.
e1fbe5e [Michelangelo D'Agostino] Added scala function to stringify userFeatures for access in python.

Customized pickler should be registered before unpickling, but in executor, there is no way to register the picklers before run the tasks.

So, we need to register the picklers in the tasks itself, duplicate the javaToPython() and pythonToJava() in MLlib, call SerDe.initialize() before pickling or unpickling.

Author: Davies Liu <davies.liu@gmail.com>

Closes #2830 from davies/fix_pickle and squashes the following commits:

0c85fb9 [Davies Liu] revert the privacy change
6b94e15 [Davies Liu] use JavaConverters instead of JavaConversions
0f02050 [Davies Liu] hotfix: Customized pickler does not work in cluster

Currently, we serialize the data between JVM and Python case by case manually, this cannot scale to support so many APIs in MLlib.

This patch will try to address this problem by serialize the data using pickle protocol, using Pyrolite library to serialize/deserialize in JVM. Pickle protocol can be easily extended to support customized class.

All the modules are refactored to use this protocol.

Known issues: There will be some performance regression (both CPU and memory, the serialized data increased)

Author: Davies Liu <davies.liu@gmail.com>

Closes #2378 from davies/pickle_mllib and squashes the following commits:

dffbba2 [Davies Liu] Merge branch 'master' of github.com:apache/spark into pickle_mllib
810f97f [Davies Liu] fix equal of matrix
032cd62 [Davies Liu] add more type check and conversion for user_product
bd738ab [Davies Liu] address comments
e431377 [Davies Liu] fix cache of rdd, refactor
19d0967 [Davies Liu] refactor Picklers
2511e76 [Davies Liu] cleanup
1fccf1a [Davies Liu] address comments
a2cc855 [Davies Liu] fix tests
9ceff73 [Davies Liu] test size of serialized Rating
44e0551 [Davies Liu] fix cache
a379a81 [Davies Liu] fix pickle array in python2.7
df625c7 [Davies Liu] Merge commit '154d141' into pickle_mllib
154d141 [Davies Liu] fix autobatchedpickler
44736d7 [Davies Liu] speed up pickling array in Python 2.7
e1d1bfc [Davies Liu] refactor
708dc02 [Davies Liu] fix tests
9dcfb63 [Davies Liu] fix style
88034f0 [Davies Liu] rafactor, address comments
46a501e [Davies Liu] choose batch size automatically
df19464 [Davies Liu] memorize the module and class name during pickleing
f3506c5 [Davies Liu] Merge branch 'master' into pickle_mllib
722dd96 [Davies Liu] cleanup _common.py
0ee1525 [Davies Liu] remove outdated tests
b02e34f [Davies Liu] remove _common.py
84c721d [Davies Liu] Merge branch 'master' into pickle_mllib
4d7963e [Davies Liu] remove muanlly serialization
6d26b03 [Davies Liu] fix tests
c383544 [Davies Liu] classification
f2a0856 [Davies Liu] mllib/regression
d9f691f [Davies Liu] mllib/util
cccb8b1 [Davies Liu] mllib/tree
8fe166a [Davies Liu] Merge branch 'pickle' into pickle_mllib
aa2287e [Davies Liu] random
f1544c4 [Davies Liu] refactor clustering
52d1350 [Davies Liu] use new protocol in mllib/stat
b30ef35 [Davies Liu] use pickle to serialize data for mllib/recommendation
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

Put all public API in __all__, also put them all in pyspark.__init__.py, then we can got all the documents for public API by `pydoc pyspark`. It also can be used by other programs (such as Sphinx or Epydoc) to generate only documents for public APIs.

Author: Davies Liu <davies.liu@gmail.com>

Closes #2205 from davies/public and squashes the following commits:

c6c5567 [Davies Liu] fix message
f7b35be [Davies Liu] put SchemeRDD, Row in pyspark.sql module
7e3016a [Davies Liu] add __all__ in mllib
6281b48 [Davies Liu] fix doc for SchemaRDD
6caab21 [Davies Liu] add public interfaces into pyspark.__init__.py

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

Author: Reynold Xin <rxin@apache.org>

Closes #871 from rxin/mllib-pep8 and squashes the following commits:

848416f [Reynold Xin] Fixed a typo in the previous cleanup (c -> sc).
a8db4cd [Reynold Xin] Fix PEP8 violations in Python mllib.

- Added a Python wrapper for Naive Bayes
- Updated the Scala Naive Bayes to match the style of our other
  algorithms better and in particular make it easier to call from Java
  (added builder pattern, removed default value in train method)
- Updated Python MLlib functions to not require a SparkContext; we can
  get that from the RDD the user gives
- Added a toString method in LabeledPoint
- Made the Python MLlib tests run as part of run-tests as well (before
  they could only be run individually through each file)