Skip to content
Snippets Groups Projects
user avatar
Dongjoon Hyun authored
## What changes were proposed in this pull request?

Currently, `NullPropagation` optimizer replaces `COUNT` on null literals in a bottom-up fashion. During that, `WindowExpression` is not covered properly. This PR adds the missing propagation logic.

**Before**
```scala
scala> sql("SELECT COUNT(1 + NULL) OVER ()").show
java.lang.UnsupportedOperationException: Cannot evaluate expression: cast(0 as bigint) windowspecdefinition(ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)
```

**After**
```scala
scala> sql("SELECT COUNT(1 + NULL) OVER ()").show
+----------------------------------------------------------------------------------------------+
|count((1 + CAST(NULL AS INT))) OVER (ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING)|
+----------------------------------------------------------------------------------------------+
|                                                                                             0|
+----------------------------------------------------------------------------------------------+
```

## How was this patch tested?

Pass the Jenkins test with a new test case.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #14689 from dongjoon-hyun/SPARK-17098.
91c23976
History
Name Last commit Last update
..
catalyst
core
hive-thriftserver
hive
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 allows 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.