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### What changes were proposed in this pull request? Before this PR, Subquery reuse does not work. Below are three issues: - Subquery reuse does not work. - It is sharing the same `SQLConf` (`spark.sql.exchange.reuse`) with the one for Exchange Reuse. - No test case covers the rule Subquery reuse. This PR is to fix the above three issues. - Ignored the physical operator `SubqueryExec` when comparing two plans. - Added a dedicated conf `spark.sql.subqueries.reuse` for controlling Subquery Reuse - Added a test case for verifying the behavior ### How was this patch tested? N/A Author: Xiao Li <gatorsmile@gmail.com> Closes #18169 from gatorsmile/subqueryReuse. |
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catalyst | ||
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hive | ||
hive-thriftserver | ||
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.