spark-instrumented-optimizer/sql
Takuya UESHIN a386432566 [SPARK-18623][SQL] Add returnNullable to StaticInvoke and modify it to handle properly.
## What changes were proposed in this pull request?

Add `returnNullable` to `StaticInvoke` the same as #15780 is trying to add to `Invoke` and modify to handle properly.

## How was this patch tested?

Existing tests.

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

Closes #16056 from ueshin/issues/SPARK-18623.
2017-07-05 14:25:26 +08:00
..
catalyst [SPARK-18623][SQL] Add returnNullable to StaticInvoke and modify it to handle properly. 2017-07-05 14:25:26 +08:00
core [SPARK-21295][SQL] Use qualified names in error message for missing references 2017-07-05 10:40:02 +08:00
hive [SPARK-21284][SQL] rename SessionCatalog.registerFunction parameter name 2017-07-03 10:51:44 -07:00
hive-thriftserver [SPARK-20345][SQL] Fix STS error handling logic on HiveSQLException 2017-06-12 14:05:03 -07:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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.