History

Maxim Gekk b3f2911eeb [SPARK-24945][SQL] Switching to uniVocity 2.7.3 ## What changes were proposed in this pull request? In the PR, I propose to upgrade uniVocity parser from 2.6.3 to 2.7.3. The recent version includes a fix for the SPARK-24645 issue and has better performance. Before changes: ``` Parsing quoted values: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ One quoted string 33336 / 34122 0.0 666727.0 1.0X Wide rows with 1000 columns: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ Select 1000 columns 90287 / 91713 0.0 90286.9 1.0X Select 100 columns 31826 / 36589 0.0 31826.4 2.8X Select one column 25738 / 25872 0.0 25737.9 3.5X count() 6931 / 7269 0.1 6931.5 13.0X ``` after: ``` Parsing quoted values: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ One quoted string 33411 / 33510 0.0 668211.4 1.0X Wide rows with 1000 columns: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------------ Select 1000 columns 88028 / 89311 0.0 88028.1 1.0X Select 100 columns 29010 / 32755 0.0 29010.1 3.0X Select one column 22936 / 22953 0.0 22936.5 3.8X count() 6657 / 6740 0.2 6656.6 13.5X ``` Closes #21892 ## How was this patch tested? It was tested by `CSVSuite` and `CSVBenchmarks` Author: Maxim Gekk <maxim.gekk@databricks.com> Closes #21969 from MaxGekk/univocity-2_7_3.		2018-08-03 08:33:28 +08:00
..
catalyst	[SPARK-24773] Avro: support logical timestamp type with different precisions	2018-08-03 08:32:08 +08:00
core	[SPARK-24945][SQL] Switching to uniVocity 2.7.3	2018-08-03 08:33:28 +08:00
hive	[SPARK-14540][CORE] Fix remaining major issues for Scala 2.12 Support	2018-08-02 09:17:09 -05:00
hive-thriftserver	[SPARK-24829][STS] In Spark Thrift Server, CAST AS FLOAT inconsistent with spark-shell or spark-sql	2018-07-27 13:27:17 +08:00
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.