94922d79e9
## What changes were proposed in this pull request?
Partial aggregations are generated in `EnsureRequirements`, but the planner fails to
check if partial aggregation satisfies sort requirements.
For the following query:
```
val df2 = (0 to 1000).map(x => (x % 2, x.toString)).toDF("a", "b").createOrReplaceTempView("t2")
spark.sql("select max(b) from t2 group by a").explain(true)
```
Now, the SortAggregator won't insert Sort operator before partial aggregation, this will break sort-based partial aggregation.
```
== Physical Plan ==
SortAggregate(key=[a#5], functions=[max(b#6)], output=[max(b)#17])
+- *Sort [a#5 ASC], false, 0
+- Exchange hashpartitioning(a#5, 200)
+- SortAggregate(key=[a#5], functions=[partial_max(b#6)], output=[a#5, max#19])
+- LocalTableScan [a#5, b#6]
```
Actually, a correct plan is:
```
== Physical Plan ==
SortAggregate(key=[a#5], functions=[max(b#6)], output=[max(b)#17])
+- *Sort [a#5 ASC], false, 0
+- Exchange hashpartitioning(a#5, 200)
+- SortAggregate(key=[a#5], functions=[partial_max(b#6)], output=[a#5, max#19])
+- *Sort [a#5 ASC], false, 0
+- LocalTableScan [a#5, b#6]
```
## How was this patch tested?
Added tests in `PlannerSuite`.
Author: Takeshi YAMAMURO <linguin.m.s@gmail.com>
Closes #14865 from maropu/SPARK-17289.
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| hive | ||
| hive-thriftserver | ||
| 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.