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Marco Gaido bc4a676b27 [SPARK-28201][SQL] Revisit MakeDecimal behavior on overflow 
## What changes were proposed in this pull request?

In SPARK-23179, it has been introduced a flag to control the behavior in case of overflow on decimals. The behavior is: returning `null` when `spark.sql.decimalOperations.nullOnOverflow` (default and traditional Spark behavior); throwing an `ArithmeticException` if that conf is false (according to SQL standards, other DBs behavior).

`MakeDecimal` so far had an ambiguous behavior. In case of codegen mode, it returned `null` as the other operators, but in interpreted mode, it was throwing an `IllegalArgumentException`.

The PR aligns `MakeDecimal`'s behavior with the one of other operators as defined in SPARK-23179. So now both modes return `null` or throw `ArithmeticException` according to `spark.sql.decimalOperations.nullOnOverflow`'s value.

Credits for this PR to mickjermsurawong-stripe who pointed out the wrong behavior in #20350.

## How was this patch tested?

improved UTs

Closes #25010 from mgaido91/SPARK-28201.

Authored-by: Marco Gaido <marcogaido91@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2019-07-01 11:54:58 +08:00
..
catalyst [SPARK-28201][SQL] Revisit MakeDecimal behavior on overflow 2019-07-01 11:54:58 +08:00
core [SPARK-11412][SQL] Support merge schema for ORC 2019-06-29 17:08:31 -07:00
hive [SPARK-11412][SQL] Support merge schema for ORC 2019-06-29 17:08:31 -07:00
hive-thriftserver [SPARK-28184][SQL][TEST] Avoid creating new sessions in SparkMetadataOperationSuite 2019-06-29 18:29:37 -07:00
create-docs.sh
gen-sql-markdown.py [SPARK-27328][SQL] Add 'deprecated' in ExpressionDescription for extended usage and SQL doc 2019-04-09 13:49:42 +08:00
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.