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huangzhaowei a45fefd17e [SPARK-16941] Use concurrentHashMap instead of scala Map in SparkSQLOperationManager. 
## What changes were proposed in this pull request?
ThriftServer will have some thread-safe problem in **SparkSQLOperationManager**.
Add a SynchronizedMap trait for the maps in it to avoid this problem.

Details in [SPARK-16941](https://issues.apache.org/jira/browse/SPARK-16941)

## How was this patch tested?
NA

Author: huangzhaowei <carlmartinmax@gmail.com>

Closes #14534 from SaintBacchus/SPARK-16941.
2016-08-11 11:28:28 +01:00
..
catalyst [SPARK-17015][SQL] group-by/order-by ordinal and arithmetic tests 2016-08-11 01:43:08 -07:00
core [SPARK-17015][SQL] group-by/order-by ordinal and arithmetic tests 2016-08-11 01:43:08 -07:00
hive [SPARK-16866][SQL] Infrastructure for file-based SQL end-to-end tests 2016-08-10 17:17:21 +08:00
hive-thriftserver [SPARK-16941] Use concurrentHashMap instead of scala Map in SparkSQLOperationManager. 2016-08-11 11:28:28 +01:00
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.