spark-instrumented-optimizer/sql
ptkool 259860d23d [SPARK-20463] Add support for IS [NOT] DISTINCT FROM.
## What changes were proposed in this pull request?

Add support for the SQL standard distinct predicate to SPARK SQL.

```
<expression> IS [NOT] DISTINCT FROM <expression>
```

## How was this patch tested?

Tested using unit tests, integration tests, manual tests.

Author: ptkool <michael.styles@shopify.com>

Closes #17764 from ptkool/is_not_distinct_from.
2017-05-01 17:05:35 -07:00
..
catalyst [SPARK-20463] Add support for IS [NOT] DISTINCT FROM. 2017-05-01 17:05:35 -07:00
core [SPARK-20459][SQL] JdbcUtils throws IllegalStateException: Cause already initialized after getting SQLException 2017-05-01 17:01:05 -07:00
hive [SPARK-20487][SQL] Display serde for HiveTableScan node in explained plan 2017-04-28 23:12:26 -07:00
hive-thriftserver [SPARK-20453] Bump master branch version to 2.3.0-SNAPSHOT 2017-04-24 21:48:04 -07:00
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.