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Dongjoon Hyun 5b8e848bbf [SPARK-16621][SQL] Generate stable SQLs in SQLBuilder 
## What changes were proposed in this pull request?

Currently, the generated SQLs have not-stable IDs for generated attributes.
The stable generated SQL will give more benefit for understanding or testing the queries.
This PR provides stable SQL generation by the followings.

 - Provide unique ids for generated subqueries, `gen_subquery_xxx`.
 - Provide unique and stable ids for generated attributes, `gen_attr_xxx`.

**Before**
```scala
scala> new org.apache.spark.sql.catalyst.SQLBuilder(sql("select 1")).toSQL
res0: String = SELECT `gen_attr_0` AS `1` FROM (SELECT 1 AS `gen_attr_0`) AS gen_subquery_0
scala> new org.apache.spark.sql.catalyst.SQLBuilder(sql("select 1")).toSQL
res1: String = SELECT `gen_attr_4` AS `1` FROM (SELECT 1 AS `gen_attr_4`) AS gen_subquery_0
```

**After**
```scala
scala> new org.apache.spark.sql.catalyst.SQLBuilder(sql("select 1")).toSQL
res1: String = SELECT `gen_attr_0` AS `1` FROM (SELECT 1 AS `gen_attr_0`) AS gen_subquery_0
scala> new org.apache.spark.sql.catalyst.SQLBuilder(sql("select 1")).toSQL
res2: String = SELECT `gen_attr_0` AS `1` FROM (SELECT 1 AS `gen_attr_0`) AS gen_subquery_0
```

## How was this patch tested?

Pass the existing Jenkins tests.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #14257 from dongjoon-hyun/SPARK-16621.
2016-07-27 13:23:59 +08:00
..
catalyst [SPARK-16524][SQL] Add RowBatch and RowBasedHashMapGenerator 2016-07-26 18:08:07 -07:00
core [SPARK-16621][SQL] Generate stable SQLs in SQLBuilder 2016-07-27 13:23:59 +08:00
hive [SPARK-16621][SQL] Generate stable SQLs in SQLBuilder 2016-07-27 13:23:59 +08:00
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.