History

Warren Zhu 998086c9a1 [SPARK-30794][CORE] Stage Level scheduling: Add ability to set off heap memory ### What changes were proposed in this pull request? Support set off heap memory in `ExecutorResourceRequests` ### Why are the changes needed? Support stage level scheduling ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? Added UT in `ResourceProfileSuite` and `DAGSchedulerSuite` Closes #28972 from warrenzhu25/30794. Authored-by: Warren Zhu <zhonzh@microsoft.com> Signed-off-by: Thomas Graves <tgraves@apache.org>		2020-07-27 08:16:13 -05:00
..
docs	[SPARK-32179][SPARK-32188][PYTHON][DOCS] Replace and redesign the documentation base	2020-07-27 17:49:21 +09:00
lib	[SPARK-30884][PYSPARK] Upgrade to Py4J 0.10.9	2020-02-20 09:09:30 -08:00
pyspark	[SPARK-30794][CORE] Stage Level scheduling: Add ability to set off heap memory	2020-07-27 08:16:13 -05:00
test_coverage	[SPARK-7721][PYTHON][TESTS] Adds PySpark coverage generation script	2018-01-22 22:12:50 +09:00
test_support	[SPARK-23094][SPARK-23723][SPARK-23724][SQL] Support custom encoding for json files	2018-04-29 11:25:31 +08:00
.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-26803][PYTHON] Add sbin subdirectory to pyspark	2019-02-27 08:39:55 -06:00
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-26252][PYTHON] Add support to run specific unittests and/or doctests in python/run-tests script	2018-12-05 15:22:08 +08:00
run-tests.py	[SPARK-32036] Replace references to blacklist/whitelist language with more appropriate terminology, excluding the blacklisting feature	2020-07-15 11:40:55 -05:00
setup.cfg	[SPARK-1267][SPARK-18129] Allow PySpark to be pip installed	2016-11-16 14:22:15 -08:00
setup.py	[SPARK-29802][BUILD] Use python3 in build scripts	2020-07-19 11:02:37 +09:00

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).