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Takuya UESHIN 9f262ae163 [SPARK-18398][SQL] Fix nullabilities of MapObjects and ExternalMapToCatalyst. 
## What changes were proposed in this pull request?

The nullabilities of `MapObject` can be made more strict by relying on `inputObject.nullable` and `lambdaFunction.nullable`.

Also `ExternalMapToCatalyst.dataType` can be made more strict by relying on `valueConverter.nullable`.

## How was this patch tested?

Existing tests.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #15840 from ueshin/issues/SPARK-18398.
2016-11-21 05:50:35 -08:00
..
catalyst [SPARK-18398][SQL] Fix nullabilities of MapObjects and ExternalMapToCatalyst. 2016-11-21 05:50:35 -08:00
core [HOTFIX][SQL] Fix DDLSuite failure. 2016-11-20 20:00:59 -08:00
hive [SPARK-18505][SQL] Simplify AnalyzeColumnCommand 2016-11-18 16:34:11 -08:00
hive-thriftserver [SPARK-14914][CORE] Fix Resource not closed after using, for unit tests and example 2016-11-10 10:54:36 +00:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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 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.