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* [SPARK-5012][MLLib][PySpark]Python API for Gaussian Mixture ModelFlytxtRnD2015-02-021-4/+88
| | | | | | | | | | | | | | | | | | | | | | | | | | | Python API for the Gaussian Mixture Model clustering algorithm in MLLib. Author: FlytxtRnD <meethu.mathew@flytxt.com> Closes #4059 from FlytxtRnD/PythonGmmWrapper and squashes the following commits: c973ab3 [FlytxtRnD] Merge branch 'PythonGmmWrapper', remote-tracking branch 'upstream/master' into PythonGmmWrapper 339b09c [FlytxtRnD] Added MultivariateGaussian namedtuple and Arraybuffer in trainGaussianMixture fa0a142 [FlytxtRnD] New line added d5b36ab [FlytxtRnD] Changed argument names to lowercase ac134f1 [FlytxtRnD] Merge branch 'PythonGmmWrapper' of https://github.com/FlytxtRnD/spark into PythonGmmWrapper 6671ea1 [FlytxtRnD] Added mllib/stat/distribution.py 3aee84b [FlytxtRnD] Fixed style issues 2e9f12a [FlytxtRnD] Added mllib/stat/distribution.py and fixed style issues b22532c [FlytxtRnD] Merge branch 'PythonGmmWrapper', remote-tracking branch 'upstream/master' into PythonGmmWrapper 2e14d82 [FlytxtRnD] Incorporate MultivariateGaussian instances in GaussianMixtureModel 05767c7 [FlytxtRnD] Merge branch 'PythonGmmWrapper', remote-tracking branch 'upstream/master' into PythonGmmWrapper 3464d19 [FlytxtRnD] Merge branch 'PythonGmmWrapper', remote-tracking branch 'upstream/master' into PythonGmmWrapper c1d4c71 [FlytxtRnD] Merge branch 'PythonGmmWrapper', remote-tracking branch 'origin/PythonGmmWrapper' into PythonGmmWrapper 426d130 [FlytxtRnD] Added random seed parameter 332bad1 [FlytxtRnD] Merge branch 'PythonGmmWrapper', remote-tracking branch 'upstream/master' into PythonGmmWrapper f82750b [FlytxtRnD] Fixed style issues 5c83825 [FlytxtRnD] Split input file with space delimiter fda60f3 [FlytxtRnD] Python API for Gaussian Mixture Model
* [SPARK-4749] [mllib]: Allow initializing KMeans clusters using a seednate.crosswhite2015-01-211-2/+2
| | | | | | | | | | | | | | | | | | | 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-4531] [MLlib] cache serialized java objectDavies Liu2014-11-211-5/+3
| | | | | | | | | | | | | | | | | | | 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-4124] [MLlib] [PySpark] simplify serialization in MLlib Python APIDavies Liu2014-10-301-9/+6
| | | | | | | | | | | | | | | | | 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
* [SPARK-3971] [MLLib] [PySpark] hotfix: Customized pickler should work in ↵Davies Liu2014-10-161-2/+2
| | | | | | | | | | | | | | | | cluster mode 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
* [SPARK-3491] [MLlib] [PySpark] use pickle to serialize data in MLlibDavies Liu2014-09-191-22/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* [SPARK-3309] [PySpark] Put all public API in __all__Davies Liu2014-09-031-0/+2
| | | | | | | | | | | | | | Put all public API in __all__, also put them all in pyspark.__init__.py, then we can got all the documents for public API by `pydoc pyspark`. It also can be used by other programs (such as Sphinx or Epydoc) to generate only documents for public APIs. Author: Davies Liu <davies.liu@gmail.com> Closes #2205 from davies/public and squashes the following commits: c6c5567 [Davies Liu] fix message f7b35be [Davies Liu] put SchemeRDD, Row in pyspark.sql module 7e3016a [Davies Liu] add __all__ in mllib 6281b48 [Davies Liu] fix doc for SchemaRDD 6caab21 [Davies Liu] add public interfaces into pyspark.__init__.py
* [SPARK-2627] [PySpark] have the build enforce PEP 8 automaticallyNicholas Chammas2014-08-061-0/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* Fix PEP8 violations in Python mllib.Reynold Xin2014-05-251-8/+7
| | | | | | | | | 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.
* [WIP] SPARK-1430: Support sparse data in Python MLlibMatei Zaharia2014-04-151-12/+39
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds a SparseVector class in PySpark and updates all the regression, classification and clustering algorithms and models to support sparse data, similar to MLlib. I chose to add this class because SciPy is quite difficult to install in many environments (more so than NumPy), but I plan to add support for SciPy sparse vectors later too, and make the methods work transparently on objects of either type. On the Scala side, we keep Python sparse vectors sparse and pass them to MLlib. We always return dense vectors from our models. Some to-do items left: - [x] Support SciPy's scipy.sparse matrix objects when SciPy is available. We can easily add a function to convert these to our own SparseVector. - [x] MLlib currently uses a vector with one extra column on the left to represent what we call LabeledPoint in Scala. Do we really want this? It may get annoying once you deal with sparse data since you must add/subtract 1 to each feature index when training. We can remove this API in 1.0 and use tuples for labeling. - [x] Explain how to use these in the Python MLlib docs. CC @mengxr, @joshrosen Author: Matei Zaharia <matei@databricks.com> Closes #341 from mateiz/py-ml-update and squashes the following commits: d52e763 [Matei Zaharia] Remove no-longer-needed slice code and handle review comments ea5a25a [Matei Zaharia] Fix remaining uses of copyto() after merge b9f97a3 [Matei Zaharia] Fix test 1e1bd0f [Matei Zaharia] Add MLlib logistic regression example in Python 88bc01f [Matei Zaharia] Clean up inheritance of LinearModel in Python, and expose its parametrs 37ab747 [Matei Zaharia] Fix some examples and docs due to changes in MLlib API da0f27e [Matei Zaharia] Added a MLlib K-means example and updated docs to discuss sparse data c48e85a [Matei Zaharia] Added some tests for passing lists as input, and added mllib/tests.py to run-tests script. a07ba10 [Matei Zaharia] Fix some typos and calculation of initial weights 74eefe7 [Matei Zaharia] Added LabeledPoint class in Python 889dde8 [Matei Zaharia] Support scipy.sparse matrices in all our algorithms and models ab244d1 [Matei Zaharia] Allow SparseVectors to be initialized using a dict a5d6426 [Matei Zaharia] Add linalg.py to run-tests script 0e7a3d8 [Matei Zaharia] Keep vectors sparse in Java when reading LabeledPoints eaee759 [Matei Zaharia] Update regression, classification and clustering models for sparse data 2abbb44 [Matei Zaharia] Further work to get linear models working with sparse data 154f45d [Matei Zaharia] Update docs, name some magic values 881fef7 [Matei Zaharia] Added a sparse vector in Python and made Java-Python format more compact
* Add Naive Bayes to Python MLlib, and some API fixesMatei Zaharia2014-01-111-5/+6
| | | | | | | | | | | | - 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)
* Split the mllib bindings into a whole bunch of modules and rename some things.Tor Myklebust2013-12-251-0/+79
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