GitHub user uncleGen opened a pull request:
https://github.com/apache/spark/pull/17025
[SPARK-19690][SS] Join a streaming DataFrame with a batch DataFrame which
has an aggregation may not work
## What changes were proposed in this pull request?
`StatefulAggregationStrategy` should check logicplan is streaming or not
Test code:
```
case class Record(key: Int, value: String)
val df = spark.createDataFrame((1 to 100).map(i => Record(i,
s"value_$i"))).groupBy("value").count
val lines = spark.readStream.format("socket").option("host",
"localhost").option("port", "9999").load
val words = lines.as[String].flatMap(_.split(" "))
val wordCounts = words.join(df, "value")
```
before pr:
```
== Physical Plan ==
*Project [value#13, count#19L]
+- *BroadcastHashJoin [value#13], [value#1], Inner, BuildRight
:- *Filter isnotnull(value#13)
: +- *SerializeFromObject [staticinvoke(class
org.apache.spark.unsafe.types.UTF8String, StringType, fromString, input[0,
java.lang.String, true], true) AS value#13]
: +- MapPartitions <function1>, obj#12: java.lang.String
: +- DeserializeToObject value#5.toString, obj#11:
java.lang.String
: +- StreamingRelation textSocket, [value#5]
+- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
true]))
+- *HashAggregate(keys=[value#1], functions=[count(1)])
+- StateStoreSave [value#1], OperatorStateId(<unknown>,0,0),
Append, 0
+- *HashAggregate(keys=[value#1], functions=[merge_count(1)])
+- StateStoreRestore [value#1],
OperatorStateId(<unknown>,0,0)
+- *HashAggregate(keys=[value#1],
functions=[merge_count(1)])
+- Exchange hashpartitioning(value#1, 200)
+- *HashAggregate(keys=[value#1],
functions=[partial_count(1)])
+- *Project [value#1]
+- *Filter isnotnull(value#1)
+- LocalTableScan [key#0, value#1]
```
after pr:
```
== Physical Plan ==
*Project [value#13, count#19L]
+- *BroadcastHashJoin [value#13], [value#1], Inner, BuildRight
:- *Filter isnotnull(value#13)
: +- *SerializeFromObject [staticinvoke(class
org.apache.spark.unsafe.types.UTF8String, StringType, fromString, input[0,
java.lang.String, true], true) AS value#13]
: +- MapPartitions <function1>, obj#12: java.lang.String
: +- DeserializeToObject value#5.toString, obj#11:
java.lang.String
: +- StreamingRelation textSocket, [value#5]
+- BroadcastExchange HashedRelationBroadcastMode(List(input[0, string,
true]))
+- *HashAggregate(keys=[value#1], functions=[count(1)])
+- Exchange hashpartitioning(value#1, 200)
+- *HashAggregate(keys=[value#1], functions=[partial_count(1)])
+- *Project [value#1]
+- *Filter isnotnull(value#1)
+- LocalTableScan [key#0, value#1]
```
## How was this patch tested?
add new unit test.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/uncleGen/spark SPARK-19690
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17025.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #17025
----
commit 0d0c19a2f99b6417f419f72fb28c155a70dda201
Author: uncleGen <[email protected]>
Date: 2017-02-22T10:18:31Z
Join a streaming DataFrame with a batch DataFrame which has an aggregation
may not work
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