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Maxim Gekk 5e9a155eba [SPARK-29520][SS] Fix checks of negative intervals 
### What changes were proposed in this pull request?
- Added `getDuration()` to calculate interval duration in specified time units assuming provided days per months
- Added `isNegative()` which return `true` is the interval duration is less than 0
- Fix checking negative intervals by using `isNegative()` in structured streaming classes
- Fix checking of `year-months` intervals

### Why are the changes needed?
This fixes incorrect checking of negative intervals. An interval is negative when its duration is negative but not if interval's months **or** microseconds is negative. Also this fixes checking of `year-month` interval support because the `month` field could be negative.

### Does this PR introduce any user-facing change?
Should not

### How was this patch tested?
- Added tests for the `getDuration()` and `isNegative()` methods to `IntervalUtilsSuite`
- By existing SS tests

Closes #26177 from MaxGekk/interval-is-positive.

Authored-by: Maxim Gekk <max.gekk@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2019-10-31 15:35:04 +08:00
..
catalyst [SPARK-29520][SS] Fix checks of negative intervals 2019-10-31 15:35:04 +08:00
core [SPARK-29520][SS] Fix checks of negative intervals 2019-10-31 15:35:04 +08:00
hive Revert "Prepare Spark release v3.0.0-preview-rc2" 2019-10-30 17:45:44 -07:00
hive-thriftserver Revert "Prepare Spark release v3.0.0-preview-rc2" 2019-10-30 17:45:44 -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-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 [SPARK-28980][CORE][SQL][STREAMING][MLLIB] Remove most items deprecated in Spark 2.2.0 or earlier, for Spark 3 2019-09-09 10:19:40 -05:00

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 extensions that allow 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.