spark-instrumented-optimizer/sql
Shixiong Zhu 3dbff9be06 [SPARK-19542][SS] Delete the temp checkpoint if a query is stopped without errors
## What changes were proposed in this pull request?

When a query uses a temp checkpoint dir, it's better to delete it if it's stopped without errors.

## How was this patch tested?

New unit tests.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16880 from zsxwing/delete-temp-checkpoint.
2017-02-13 11:54:54 -08:00
..
catalyst [SPARK-19544][SQL] Improve error message when some column types are compatible and others are not in set operations 2017-02-13 16:08:31 +01:00
core [SPARK-19542][SS] Delete the temp checkpoint if a query is stopped without errors 2017-02-13 11:54:54 -08:00
hive [SPARK-19448][SQL] optimize some duplication functions between HiveClientImpl and HiveUtils 2017-02-11 22:21:14 -08:00
hive-thriftserver [SPARK-18857][SQL] Don't use Iterator.duplicate for incrementalCollect in Thrift Server 2017-01-10 13:27:55 +00:00
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.