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Herman van Hovell 4262fb0d55 [SPARK-19070] Clean-up dataset actions 
## What changes were proposed in this pull request?
Dataset actions currently spin off a new `Dataframe` only to track query execution. This PR simplifies this code path by using the `Dataset.queryExecution` directly. This PR also merges the typed and untyped action evaluation paths.

## How was this patch tested?
Existing tests.

Author: Herman van Hovell <hvanhovell@databricks.com>

Closes #16466 from hvanhovell/SPARK-19070.
2017-01-04 23:47:58 +08:00
..
catalyst [MINOR][DOCS] Remove consecutive duplicated words/typo in Spark Repo 2017-01-04 15:07:29 +00:00
core [SPARK-19070] Clean-up dataset actions 2017-01-04 23:47:58 +08:00
hive [MINOR][DOCS] Remove consecutive duplicated words/typo in Spark Repo 2017-01-04 15:07:29 +00:00
hive-thriftserver [MINOR][DOCS] Remove consecutive duplicated words/typo in Spark Repo 2017-01-04 15:07:29 +00:00
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.