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Wenchen Fan 5effc016c8 [SPARK-16879][SQL] unify logical plans for CREATE TABLE and CTAS 
## What changes were proposed in this pull request?

we have various logical plans for CREATE TABLE and CTAS: `CreateTableUsing`, `CreateTableUsingAsSelect`, `CreateHiveTableAsSelectLogicalPlan`. This PR unifies them to reduce the complexity and centralize the error handling.

## How was this patch tested?

existing tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #14482 from cloud-fan/table.
2016-08-05 10:50:26 +02:00
..
catalyst [SPARK-16879][SQL] unify logical plans for CREATE TABLE and CTAS 2016-08-05 10:50:26 +02:00
core [SPARK-16879][SQL] unify logical plans for CREATE TABLE and CTAS 2016-08-05 10:50:26 +02:00
hive [SPARK-16879][SQL] unify logical plans for CREATE TABLE and CTAS 2016-08-05 10:50:26 +02:00
hive-thriftserver [SPARK-16535][BUILD] In pom.xml, remove groupId which is redundant definition and inherited from the parent 2016-07-19 11:59:46 +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.