History

Ruifeng Zheng 1f150b9392 [SPARK-35024][ML] Refactor LinearSVC - support virtual centering ### What changes were proposed in this pull request? 1, remove existing agg, and use a new agg supporting virtual centering 2, add related testsuites ### Why are the changes needed? centering vectors should accelerate convergence, and generate solution more close to R ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? updated testsuites and added testsuites Closes #32124 from zhengruifeng/svc_agg_refactor. Authored-by: Ruifeng Zheng <ruifengz@foxmail.com> Signed-off-by: Ruifeng Zheng <ruifengz@foxmail.com>		2021-04-25 13:16:46 +08:00
..
docs	[MINOR][DOCS] Use ASCII characters when possible in PySpark documentation	2021-04-04 09:49:36 +03:00
lib	[SPARK-34688][PYTHON] Upgrade to Py4J 0.10.9.2	2021-03-11 09:51:41 -06:00
pyspark	[SPARK-35024][ML] Refactor LinearSVC - support virtual centering	2021-04-25 13:16:46 +08:00
test_coverage	[SPARK-7721][PYTHON][TESTS] Adds PySpark coverage generation script	2018-01-22 22:12:50 +09:00
test_support	Spelling r common dev mlib external project streaming resource managers python	2020-11-27 10:22:45 -06:00
.coveragerc	[SPARK-7721][PYTHON][TESTS] Adds PySpark coverage generation script	2018-01-22 22:12:50 +09:00
.gitignore	[SPARK-3946] gitignore in /python includes wrong directory	2014-10-14 14:09:39 -07:00
MANIFEST.in	[SPARK-32714][PYTHON] Initial pyspark-stubs port	2020-09-24 14:15:36 +09:00
mypy.ini	[SPARK-34890][PYTHON] Port/integrate Koalas main codes into PySpark	2021-04-06 12:42:39 +09:00
pylintrc	[SPARK-32435][PYTHON] Remove heapq3 port from Python 3	2020-07-27 20:10:13 +09:00
README.md	[SPARK-30884][PYSPARK] Upgrade to Py4J 0.10.9	2020-02-20 09:09:30 -08:00
run-tests	[SPARK-29672][PYSPARK] update spark testing framework to use python3	2019-11-14 10:18:55 -08:00
run-tests-with-coverage	[SPARK-34968][TEST][PYTHON] Add the `-fr` argument to xargs rm	2021-04-06 15:20:55 -07:00
run-tests.py	[SPARK-34886][PYTHON] Port/integrate Koalas DataFrame unit test into PySpark	2021-04-09 15:48:13 +09:00
setup.cfg	[SPARK-1267][SPARK-18129] Allow PySpark to be pip installed	2016-11-16 14:22:15 -08:00
setup.py	[SPARK-34688][PYTHON] Upgrade to Py4J 0.10.9.2	2021-03-11 09:51:41 -06:00

README.md

Apache Spark

Spark is a unified analytics engine for large-scale data processing. 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 Structured Streaming for stream processing.

https://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 set up 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, but some additional sub-packages have their own extra requirements for some features (including numpy, pandas, and pyarrow).