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## What changes were proposed in this pull request? Join processing in the parser relies on the fact that the grammar produces a right nested trees, for instance the parse tree for `select * from a join b join c` is expected to produce a tree similar to `JOIN(a, JOIN(b, c))`. However there are cases in which this (invariant) is violated, like: ```sql SELECT COUNT(1) FROM test T1 CROSS JOIN test T2 JOIN test T3 ON T3.col = T1.col JOIN test T4 ON T4.col = T1.col ``` In this case the parser returns a tree in which Joins are located on both the left and the right sides of the parent join node. This PR introduces a different grammar rule which does not make this assumption. The new rule takes a relation and searches for zero or more joined relations. As a bonus processing is much easier. ## How was this patch tested? Existing tests and I have added a regression test to the plan parser suite. Author: Herman van Hovell <hvanhovell@databricks.com> Closes #14867 from hvanhovell/SPARK-17296. |
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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.