History

Joseph K. Bradley cc67bd5732 [SPARK-20929][ML] LinearSVC should use its own threshold param ## What changes were proposed in this pull request? LinearSVC should use its own threshold param, rather than the shared one, since it applies to rawPrediction instead of probability. This PR changes the param in the Scala, Python and R APIs. ## How was this patch tested? New unit test to make sure the threshold can be set to any Double value. Author: Joseph K. Bradley <joseph@databricks.com> Closes #18151 from jkbradley/ml-2.2-linearsvc-cleanup.		2017-06-19 23:04:17 -07:00
..
docs	[SPARK-20707][ML] ML deprecated APIs should be removed in major release.	2017-05-16 10:08:23 +08:00
lib	[SPARK-17960][PYSPARK][UPGRADE TO PY4J 0.10.4]	2016-10-21 09:48:24 +01:00
pyspark	[SPARK-20929][ML] LinearSVC should use its own threshold param	2017-06-19 23:04:17 -07:00
test_support	[SPARK-19610][SQL] Support parsing multiline CSV files	2017-02-28 13:34:33 -08:00
.gitignore	[SPARK-3946] gitignore in /python includes wrong directory	2014-10-14 14:09:39 -07:00
MANIFEST.in	[SPARK-18652][PYTHON] Include the example data and third-party licenses in pyspark package.	2016-12-07 06:09:27 +08:00
pylintrc	[SPARK-13596][BUILD] Move misc top-level build files into appropriate subdirs	2016-03-07 14:48:02 -08:00
README.md	[SPARK-1267][SPARK-18129] Allow PySpark to be pip installed	2016-11-16 14:22:15 -08:00
run-tests	[SPARK-8583] [SPARK-5482] [BUILD] Refactor python/run-tests to integrate with dev/run-tests module system	2015-06-27 20:24:34 -07:00
run-tests.py	[SPARK-19955][PYSPARK] Jenkins Python Conda based test.	2017-03-29 11:41:17 -07:00
setup.cfg	[SPARK-1267][SPARK-18129] Allow PySpark to be pip installed	2016-11-16 14:22:15 -08:00
setup.py	[SPARK-20102] Fix nightly packaging and RC packaging scripts w/ two minor build fixes	2017-03-27 10:23:28 -07:00

README.md

Apache Spark

Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

http://spark.apache.org/

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project web page

Python Packaging

This README file only contains basic information related to pip installed PySpark. This packaging is currently experimental and may change in future versions (although we will do our best to keep compatibility). Using PySpark requires the Spark JARs, and if you are building this from source please see the builder instructions at "Building Spark".

The Python packaging for Spark is not intended to replace all of the other use cases. This Python packaged version of Spark is suitable for interacting with an existing cluster (be it Spark standalone, YARN, or Mesos) - but does not contain the tools required to setup your own standalone Spark cluster. You can download the full version of Spark from the Apache Spark downloads page.

NOTE: If you are using this with a Spark standalone cluster you must ensure that the version (including minor version) matches or you may experience odd errors.

Python Requirements

At its core PySpark depends on Py4J (currently version 0.10.4), but additional sub-packages have their own requirements (including numpy and pandas).