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wangzhenhua a615513569 [SPARK-19149][SQL] Unify two sets of statistics in LogicalPlan 
## What changes were proposed in this pull request?

Currently we have two sets of statistics in LogicalPlan: a simple stats and a stats estimated by cbo, but the computing logic and naming are quite confusing, we need to unify these two sets of stats.

## How was this patch tested?

Just modify existing tests.

Author: wangzhenhua <wangzhenhua@huawei.com>
Author: Zhenhua Wang <wzh_zju@163.com>

Closes #16529 from wzhfy/unifyStats.
2017-01-10 22:34:44 -08:00
..
catalyst [SPARK-19149][SQL] Unify two sets of statistics in LogicalPlan 2017-01-10 22:34:44 -08:00
core [SPARK-19149][SQL] Unify two sets of statistics in LogicalPlan 2017-01-10 22:34:44 -08:00
hive [SPARK-19149][SQL] Unify two sets of statistics in LogicalPlan 2017-01-10 22:34:44 -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

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.