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Angerszhuuuu a472612eb8 [SPARK-36702][SQL] ArrayUnion handle duplicated Double.NaN and Float.Nan 
### What changes were proposed in this pull request?
For query
```
select array_union(array(cast('nan' as double), cast('nan' as double)), array())
```
This returns [NaN, NaN], but it should return [NaN].
This issue is caused by `OpenHashSet` can't handle `Double.NaN` and `Float.NaN` too.
In this pr we add a wrap for OpenHashSet that can handle `null`, `Double.NaN`, `Float.NaN` together

### Why are the changes needed?
Fix bug

### Does this PR introduce _any_ user-facing change?
ArrayUnion won't show duplicated `NaN` value

### How was this patch tested?
Added UT

Closes #33955 from AngersZhuuuu/SPARK-36702-WrapOpenHashSet.

Lead-authored-by: Angerszhuuuu <angers.zhu@gmail.com>
Co-authored-by: AngersZhuuuu <angers.zhu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
(cherry picked from commit f71f37755d)
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
2021-09-14 18:26:02 +08:00
..
catalyst [SPARK-36702][SQL] ArrayUnion handle duplicated Double.NaN and Float.Nan 2021-09-14 18:26:02 +08:00
core [SPARK-36712][BUILD] Make scala-parallel-collections in 2.13 POM a direct dependency (not in maven profile) 2021-09-13 11:06:58 -05:00
hive [SPARK-36712][BUILD] Make scala-parallel-collections in 2.13 POM a direct dependency (not in maven profile) 2021-09-13 11:06:58 -05:00
hive-thriftserver [SPARK-36712][BUILD] Make scala-parallel-collections in 2.13 POM a direct dependency (not in maven profile) 2021-09-13 11:06:58 -05:00
create-docs.sh [SPARK-34010][SQL][DODCS] Use python3 instead of python in SQL documentation build 2021-01-05 19:48:10 +09:00
gen-sql-api-docs.py [SPARK-34747][SQL][DOCS] Add virtual operators to the built-in function document 2021-03-19 10:19:26 +09:00
gen-sql-config-docs.py [SPARK-36657][SQL] Update comment in 'gen-sql-config-docs.py' 2021-09-02 18:51:10 -07:00
gen-sql-functions-docs.py
mkdocs.yml
README.md

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, and SQL configuration documentation that gets included as part of configuration.md in the main docs directory.