9c5935d00b
## What changes were proposed in this pull request? When inferring constraints from children, Join's condition can be simplified as None. For example, ``` val testRelation = LocalRelation('a.int) val x = testRelation.as("x") val y = testRelation.where($"a" === 2 && !($"a" === 2)).as("y") x.join.where($"x.a" === $"y.a") ``` The plan will become ``` Join Inner :- LocalRelation <empty>, [a#23] +- LocalRelation <empty>, [a#224] ``` And the Cartesian products check will throw exception for above plan. Propagate empty relation before checking Cartesian products, and the issue is resolved. ## How was this patch tested? Unit test Author: Wang Gengliang <ltnwgl@gmail.com> Closes #19362 from gengliangwang/MoveCheckCartesianProducts. |
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catalyst | ||
core | ||
hive | ||
hive-thriftserver | ||
create-docs.sh | ||
gen-sql-markdown.py | ||
mkdocs.yml | ||
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 allows 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
.