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[SPARK-17849][SQL] Fix NPE problem when using grouping sets
wangyang authored 
## What changes were proposed in this pull request?

Prior this pr, the following code would cause an NPE:
`case class point(a:String, b:String, c:String, d: Int)`

`val data = Seq(
point("1","2","3", 1),
point("4","5","6", 1),
point("7","8","9", 1)
)`
`sc.parallelize(data).toDF().registerTempTable("table")`
`spark.sql("select a, b, c, count(d) from table group by a, b, c GROUPING SETS ((a)) ").show()`

The reason is that when the grouping_id() behavior was changed in #10677, some code (which should be changed) was left out.

Take the above code for example, prior #10677, the bit mask for set "(a)" was `001`, while after #10677 the bit mask was changed to `011`. However, the `nonNullBitmask` was not changed accordingly.

This pr will fix this problem.
## How was this patch tested?

add integration tests

Author: wangyang <wangyang@haizhi.com>

Closes #15416 from yangw1234/groupingid.

(cherry picked from commit fb0d6081)
Signed-off-by: default avatarHerman van Hovell <hvanhovell@databricks.com>
446d72c5
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catalyst
core
hive-thriftserver
hive
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 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.