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Lianhui Wang 06e33985c6 [SPARK-16302][SQL] Set the right number of partitions for reading data from a local collection. 
follow #13137 This pr sets the right number of partitions when reading data from a local collection.
Query 'val df = Seq((1, 2)).toDF("key", "value").count' always use defaultParallelism tasks. So it causes run many empty or small tasks.

Manually tested and checked.

Author: Lianhui Wang <lianhuiwang09@gmail.com>

Closes #13979 from lianhuiwang/localTable-Parallel.
2016-09-01 17:09:23 -07:00
..
catalyst [SPARK-16525] [SQL] Enable Row Based HashMap in HashAggregateExec 2016-09-01 16:56:35 -07:00
core [SPARK-16302][SQL] Set the right number of partitions for reading data from a local collection. 2016-09-01 17:09:23 -07:00
hive [SPARK-16525] [SQL] Enable Row Based HashMap in HashAggregateExec 2016-09-01 16:56:35 -07:00
hive-thriftserver [SPARK-17190][SQL] Removal of HiveSharedState 2016-08-25 12:50:03 +08:00
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.