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Wenchen Fan b7650f11c7 [SPARK-18947][SQL] SQLContext.tableNames should not call Catalog.listTables 
## What changes were proposed in this pull request?

It's a huge waste to call `Catalog.listTables` in `SQLContext.tableNames`, which only need the table names, while `Catalog.listTables` will get the table metadata for each table name.

## How was this patch tested?

N/A

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16352 from cloud-fan/minor.
2016-12-21 19:39:00 +08:00
..
catalyst [SPARK-18899][SPARK-18912][SPARK-18913][SQL] refactor the error checking when append data to an existing table 2016-12-19 20:03:33 -08:00
core [SPARK-18947][SQL] SQLContext.tableNames should not call Catalog.listTables 2016-12-21 19:39:00 +08:00
hive [SPARK-18949][SQL] Add recoverPartitions API to Catalog 2016-12-20 23:40:02 -08:00
hive-thriftserver [SPARK-18695] Bump master branch version to 2.2.0-SNAPSHOT 2016-12-02 21:09:37 -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.