ODIn/spark-instrumented-optimizer
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
spark-instrumented-optimizer/sql
History
Yuming Wang e1de34113e [SPARK-17091][SQL] Add rule to convert IN predicate to equivalent Parquet filter 
## What changes were proposed in this pull request?

The original pr is: https://github.com/apache/spark/pull/18424

Add a new optimizer rule to convert an IN predicate to an equivalent Parquet filter and add `spark.sql.parquet.pushdown.inFilterThreshold` to control limit thresholds. Different data types have different limit thresholds, this is a copy of data for reference:

Type | limit threshold
-- | --
string | 370
int | 210
long | 285
double | 270
float | 220
decimal | Won't provide better performance before [SPARK-24549](https://issues.apache.org/jira/browse/SPARK-24549)

## How was this patch tested?
unit tests and manual tests

Author: Yuming Wang <yumwang@ebay.com>

Closes #21603 from wangyum/SPARK-17091.
2018-07-14 17:50:54 +08:00
..
catalyst [SPARK-17091][SQL] Add rule to convert IN predicate to equivalent Parquet filter 2018-07-14 17:50:54 +08:00
core [SPARK-17091][SQL] Add rule to convert IN predicate to equivalent Parquet filter 2018-07-14 17:50:54 +08:00
hive [SPARK-23831][SQL] Add org.apache.derby to IsolatedClientLoader 2018-07-13 14:07:52 -07:00
hive-thriftserver [SPARK-24553][WEB-UI] http 302 fixes for href redirect 2018-06-27 15:36:59 -07:00
create-docs.sh [MINOR][DOCS] Minor doc fixes related with doc build and uses script dir in SQL doc gen script 2017-08-26 13:56:24 +09:00
gen-sql-markdown.py [SPARK-21485][FOLLOWUP][SQL][DOCS] Describes examples and arguments separately, and note/since in SQL built-in function documentation 2017-08-05 10:10:56 -07:00
mkdocs.yml [SPARK-21485][SQL][DOCS] Spark SQL documentation generation for built-in functions 2017-07-26 09:38:51 -07:00
README.md [MINOR][DOC] Fix some typos and grammar issues 2018-04-06 13:37:08 +08:00

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 allow 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.

Running sql/create-docs.sh generates SQL documentation for built-in functions under sql/site.