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Gengliang Wang 9c238b8a46 [SPARK-27460][TESTS] Running slowest test suites in their own forked JVMs for higher parallelism 
## What changes were proposed in this pull request?

This patch modifies SparkBuild so that the largest / slowest test suites (or collections of suites) can run in their own forked JVMs, allowing them to be run in parallel with each other. This opt-in / whitelisting approach allows us to increase parallelism without having to fix a long-tail of flakiness / brittleness issues in tests which aren't performance bottlenecks.

See comments in SparkBuild.scala for information on the details, including a summary of why we sometimes opt to run entire groups of tests in a single forked JVM .

The time of full new pull request test in Jenkins is reduced by around 53%:
before changes: 4hr 40min
after changes: 2hr 13min

## How was this patch tested?

Unit test

Closes #24373 from gengliangwang/parallelTest.

Authored-by: Gengliang Wang <gengliang.wang@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2019-04-18 20:49:36 +08:00
..
catalyst [SPARK-27423][SQL][FOLLOWUP] Minor polishes to Cast codegen templates for Date <-> Timestamp 2019-04-18 14:27:33 +08:00
core [SPARK-27460][TESTS] Running slowest test suites in their own forked JVMs for higher parallelism 2019-04-18 20:49:36 +08:00
hive [SPARK-27448][SQL] File source V2 table provider should be compatible with V1 provider 2019-04-16 14:26:38 +08:00
hive-thriftserver [SPARK-27404][CORE][SQL][STREAMING][YARN] Fix build warnings for 3.0: postfixOps edition 2019-04-11 13:43:44 -05:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-27328][SQL] Add 'deprecated' in ExpressionDescription for extended usage and SQL doc 2019-04-09 13:49:42 +08:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

README.md

Spark SQL

This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.

Spark SQL is broken up into four subprojects:

  • Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
  • Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
  • Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allow users to run queries that include Hive UDFs, UDAFs, and UDTFs.
  • HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.