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Daniel van der Ende 2333a34d39 [SPARK-22880][SQL] Add cascadeTruncate option to JDBC datasource 
This commit adds the `cascadeTruncate` option to the JDBC datasource
API, for databases that support this functionality (PostgreSQL and
Oracle at the moment). This allows for applying a cascading truncate
that affects tables that have foreign key constraints on the table
being truncated.

## What changes were proposed in this pull request?

Add `cascadeTruncate` option to JDBC datasource API. Allow this to affect the
`TRUNCATE` query for databases that support this option.

## How was this patch tested?
Existing tests for `truncateQuery` were updated. Also, an additional test was added
to ensure that the correct syntax was applied, and that enabling the config for databases
that do not support this option does not result in invalid queries.

Author: Daniel van der Ende <daniel.vanderende@gmail.com>

Closes #20057 from danielvdende/SPARK-22880.
2018-07-20 13:03:57 -07:00
..
catalyst Revert "[SPARK-24811][SQL] Avro: add new function from_avro and to_avro" 2018-07-20 12:55:38 -07:00
core [SPARK-22880][SQL] Add cascadeTruncate option to JDBC datasource 2018-07-20 13:03:57 -07:00
hive [SPARK-24268][SQL] Use datatype.catalogString in error messages 2018-07-19 23:29:29 -07:00
hive-thriftserver [SPARK-24553][WEB-UI] http 302 fixes for href redirect 2018-06-27 15:36:59 -07:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

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 allow 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.