ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Davies Liu 0f72e4f04b [SPARK-16958] [SQL] Reuse subqueries within the same query 
## What changes were proposed in this pull request?

There could be multiple subqueries that generate same results, we could re-use the result instead of running it multiple times.

This PR also cleanup up how we run subqueries.

For SQL query
```sql
select id,(select avg(id) from t) from t where id > (select avg(id) from t)
```
The explain is
```
== Physical Plan ==
*Project [id#15L, Subquery subquery29 AS scalarsubquery()#35]
:  +- Subquery subquery29
:     +- *HashAggregate(keys=[], functions=[avg(id#15L)])
:        +- Exchange SinglePartition
:           +- *HashAggregate(keys=[], functions=[partial_avg(id#15L)])
:              +- *Range (0, 1000, splits=4)
+- *Filter (cast(id#15L as double) > Subquery subquery29)
   :  +- Subquery subquery29
   :     +- *HashAggregate(keys=[], functions=[avg(id#15L)])
   :        +- Exchange SinglePartition
   :           +- *HashAggregate(keys=[], functions=[partial_avg(id#15L)])
   :              +- *Range (0, 1000, splits=4)
   +- *Range (0, 1000, splits=4)
```
The visualized plan:

![reuse-subquery](https://cloud.githubusercontent.com/assets/40902/17573229/e578d93c-5f0d-11e6-8a3c-0150d81d3aed.png)

## How was this patch tested?

Existing tests.

Author: Davies Liu <davies@databricks.com>

Closes #14548 from davies/subq.
2016-08-11 09:47:19 -07:00
..
catalyst [SPARK-16958] [SQL] Reuse subqueries within the same query 2016-08-11 09:47:19 -07:00
core [SPARK-16958] [SQL] Reuse subqueries within the same query 2016-08-11 09:47:19 -07:00
hive [SPARK-16866][SQL] Infrastructure for file-based SQL end-to-end tests 2016-08-10 17:17:21 +08:00
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

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.