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Wenchen Fan d0990e3dfe [SPARK-25454][SQL] add a new config for picking minimum precision for integral literals 
## What changes were proposed in this pull request?

https://github.com/apache/spark/pull/20023 proposed to allow precision lose during decimal operations, to reduce the possibilities of overflow. This is a behavior change and is protected by the DECIMAL_OPERATIONS_ALLOW_PREC_LOSS config. However, that PR introduced another behavior change: pick a minimum precision for integral literals, which is not protected by a config. This PR add a new config for it: `spark.sql.literal.pickMinimumPrecision`.

This can allow users to work around issue in SPARK-25454, which is caused by a long-standing bug of negative scale.

## How was this patch tested?

a new test

Closes #22494 from cloud-fan/decimal.

Authored-by: Wenchen Fan <wenchen@databricks.com>
Signed-off-by: gatorsmile <gatorsmile@gmail.com>
2018-09-26 17:47:05 -07:00
..
catalyst [SPARK-25454][SQL] add a new config for picking minimum precision for integral literals 2018-09-26 17:47:05 -07:00
core [SPARK-25454][SQL] add a new config for picking minimum precision for integral literals 2018-09-26 17:47:05 -07:00
hive [SPARK-25534][SQL] Make SQLHelper trait 2018-09-25 23:03:54 -07:00
hive-thriftserver [SPARK-25436] Bump master branch version to 2.5.0-SNAPSHOT 2018-09-15 16:24:02 -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.