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Linhong Liu f3ec79990f [SPARK-35984][SQL][TEST] Config to force applying shuffled hash join 
### What changes were proposed in this pull request?
Add a config `spark.sql.join.forceApplyShuffledHashJoin` to force applying shuffled hash join
during the join selection.

### Why are the changes needed?
In the `SQLQueryTestSuite`, we want to cover 3 kinds of join (BHJ, SHJ, SMJ) in join.sql. But even
if the `spark.sql.join.preferSortMergeJoin` is set to `false`, shuffled hash join is still not guaranteed.
Thus, we need another config to force the selection.

### Does this PR introduce _any_ user-facing change?
No, only for testing

### How was this patch tested?
newly added tests
Verified all queries in join.sql will use `ShuffledHashJoin` when the config set to `true`

Closes #33182 from linhongliu-db/SPARK-35984-hash-join-config.

Authored-by: Linhong Liu <linhong.liu@databricks.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
(cherry picked from commit 7566db6033)
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-07-07 00:58:30 +08:00
..
catalyst [SPARK-35984][SQL][TEST] Config to force applying shuffled hash join 2021-07-07 00:58:30 +08:00
core [SPARK-35984][SQL][TEST] Config to force applying shuffled hash join 2021-07-07 00:58:30 +08:00
hive [SPARK-35686][SQL] Not allow using auto-generated alias when creating view 2021-07-01 12:47:38 +00:00
hive-thriftserver [SPARK-35966][SQL] Port HIVE-17952: Fix license headers to avoid dangling javadoc warnings 2021-07-01 18:22:04 +08:00
create-docs.sh [SPARK-34010][SQL][DODCS] Use python3 instead of python in SQL documentation build 2021-01-05 19:48:10 +09:00
gen-sql-api-docs.py [SPARK-34747][SQL][DOCS] Add virtual operators to the built-in function document 2021-03-19 10:19:26 +09:00
gen-sql-config-docs.py [SPARK-32194][PYTHON] Use proper exception classes instead of plain Exception 2021-05-26 11:54:40 +09:00
gen-sql-functions-docs.py
mkdocs.yml
README.md

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 extensions that allow 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, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.