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Gengliang Wang 70635b4b26 Revert "[SPARK-35028][SQL] ANSI mode: disallow group by aliases" 
### What changes were proposed in this pull request?

Revert [[SPARK-35028][SQL] ANSI mode: disallow group by aliases ](https://github.com/apache/spark/pull/32129)

### Why are the changes needed?

It turns out that many users are using the group by alias feature.  Spark has its precedence rule when alias names conflict with column names in Group by clause: always use the table column. This should be reasonable and acceptable.
Also, external DBMS such as PostgreSQL and MySQL allow grouping by alias, too.

As we are going to announce ANSI mode GA in Spark 3.2, I suggest allowing the group by alias in ANSI mode.

### Does this PR introduce _any_ user-facing change?

No, the feature is not released yet.

### How was this patch tested?

Unit tests

Closes #33758 from gengliangwang/revertGroupByAlias.

Authored-by: Gengliang Wang <gengliang@apache.org>
Signed-off-by: Gengliang Wang <gengliang@apache.org>
(cherry picked from commit 8bfb4f1e72)
Signed-off-by: Gengliang Wang <gengliang@apache.org>
2021-08-17 20:24:09 +08:00
..
catalyst Revert "[SPARK-35028][SQL] ANSI mode: disallow group by aliases" 2021-08-17 20:24:09 +08:00
core Revert "[SPARK-35028][SQL] ANSI mode: disallow group by aliases" 2021-08-17 20:24:09 +08:00
hive [SPARK-36524][SQL] Common class for ANSI interval types 2021-08-17 12:28:07 +03:00
hive-thriftserver [SPARK-36524][SQL] Common class for ANSI interval types 2021-08-17 12:28:07 +03:00
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-32194][PYTHON] Use proper exception classes instead of plain Exception 2021-05-26 11:54:40 +09:00
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.