spark-instrumented-optimizer/sql
Eric Liang 412dba63b5 [SPARK-17069] Expose spark.range() as table-valued function in SQL
## What changes were proposed in this pull request?

This adds analyzer rules for resolving table-valued functions, and adds one builtin implementation for range(). The arguments for range() are the same as those of `spark.range()`.

## How was this patch tested?

Unit tests.

cc hvanhovell

Author: Eric Liang <ekl@databricks.com>

Closes #14656 from ericl/sc-4309.
2016-08-18 13:33:55 +02:00
..
catalyst [SPARK-17069] Expose spark.range() as table-valued function in SQL 2016-08-18 13:33:55 +02:00
core [SPARK-17069] Expose spark.range() as table-valued function in SQL 2016-08-18 13:33:55 +02:00
hive [SPARK-16736][CORE][SQL] purge superfluous fs calls 2016-08-17 11:43:01 -07:00
hive-thriftserver [SPARK-16941] Use concurrentHashMap instead of scala Map in SparkSQLOperationManager. 2016-08-11 11:28:28 +01:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

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.