Update upstream #233
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GulajavaMinistudio merged 20 commits intoGulajavaMinistudio:masterfrom Dec 7, 2017
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## What changes were proposed in this pull request? make `Imputer` inherit `HasOutputCols` ## How was this patch tested? existing tests Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #19889 from zhengruifeng/using_HasOutputCols.
## What changes were proposed in this pull request? This PR accomplishes the following two items. 1. Reduce # of global variables from two to one 2. Make lifetime of global variable local within an operation Item 1. reduces # of constant pool entries in a Java class. Item 2. ensures that an variable is not passed to arguments in a method split by `CodegenContext.splitExpressions()`, which is addressed by #19865. ## How was this patch tested? Added new test into `ArithmeticExpressionSuite` Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com> Closes #19899 from kiszk/SPARK-22704.
## What changes were proposed in this pull request? ScalaUDF is using global variables which are not needed. This can generate some unneeded entries in the constant pool. The PR replaces the unneeded global variables with local variables. ## How was this patch tested? added UT Author: Marco Gaido <mgaido@hortonworks.com> Author: Marco Gaido <marcogaido91@gmail.com> Closes #19900 from mgaido91/SPARK-22695.
…tion ## What changes were proposed in this pull request? I was looking at the config code today and found that configs defined using ConfigBuilder.fallbackConf didn't trigger onCreate function. This patch fixes it. This doesn't require backporting since we currently have no configs that use it. ## How was this patch tested? Added a test case for all the config final creator functions in ConfigEntrySuite. Author: Reynold Xin <rxin@databricks.com> Closes #19905 from rxin/SPARK-22710.
…urs exception: Could not find CoarseGrainedScheduler or it has been stopped
## What changes were proposed in this pull request?
I see the two instances where the exception is occurring.
**Instance 1:**
```
17/11/10 15:49:32 ERROR util.Utils: Uncaught exception in thread driver-revive-thread
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:160)
at org.apache.spark.rpc.netty.Dispatcher.postOneWayMessage(Dispatcher.scala:140)
at org.apache.spark.rpc.netty.NettyRpcEnv.send(NettyRpcEnv.scala:187)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.send(NettyRpcEnv.scala:521)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(CoarseGrainedSchedulerBackend.scala:125)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(CoarseGrainedSchedulerBackend.scala:125)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1$$anonfun$run$1.apply$mcV$sp(CoarseGrainedSchedulerBackend.scala:125)
at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1344)
at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverEndpoint$$anon$1.run(CoarseGrainedSchedulerBackend.scala:124)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
```
In CoarseGrainedSchedulerBackend.scala, driver-revive-thread starts with DriverEndpoint.onStart() and keeps sending the ReviveOffers messages periodically till it gets shutdown as part DriverEndpoint.onStop(). There is no proper coordination between the driver-revive-thread(shutdown) and the RpcEndpoint unregister, RpcEndpoint unregister happens first and then driver-revive-thread shuts down as part of DriverEndpoint.onStop(), In-between driver-revive-thread may try to send the ReviveOffers message which is leading to the above exception.
To fix this issue, this PR moves the shutting down of driver-revive-thread to CoarseGrainedSchedulerBackend.stop() which executes before the DriverEndpoint unregister.
**Instance 2:**
```
17/11/10 16:31:38 ERROR cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Error requesting driver to remove executor 1 for reason Executor for container container_1508535467865_0226_01_000002 exited because of a YARN event (e.g., pre-emption) and not because of an error in the running job.
org.apache.spark.SparkException: Could not find CoarseGrainedScheduler.
at org.apache.spark.rpc.netty.Dispatcher.postMessage(Dispatcher.scala:160)
at org.apache.spark.rpc.netty.Dispatcher.postLocalMessage(Dispatcher.scala:135)
at org.apache.spark.rpc.netty.NettyRpcEnv.ask(NettyRpcEnv.scala:229)
at org.apache.spark.rpc.netty.NettyRpcEndpointRef.ask(NettyRpcEnv.scala:516)
at org.apache.spark.rpc.RpcEndpointRef.ask(RpcEndpointRef.scala:63)
at org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint$$anonfun$receive$1.applyOrElse(YarnSchedulerBackend.scala:269)
at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:117)
at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:205)
at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:101)
at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:221)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
```
Here YarnDriverEndpoint tries to send remove executor messages after the Yarn scheduler backend service stop, which is leading to the above exception. To avoid the above exception,
1) We may add a condition(which checks whether service has stopped or not) before sending executor remove message
2) Add a warn log message in onFailure case when the service is already stopped
In this PR, chosen the 2) option which adds a log message in the case of onFailure without the exception stack trace since the option 1) would need to to go through for every remove executor message.
## How was this patch tested?
I verified it manually, I don't see these exceptions with the PR changes.
Author: Devaraj K <devaraj@apache.org>
Closes #19741 from devaraj-kavali/SPARK-14228.
## What changes were proposed in this pull request? Our Analyzer and Optimizer have multiple rules for `UnaryNode`. After making `EventTimeWatermark` extend `UnaryNode`, we do not need a special handling for `EventTimeWatermark`. ## How was this patch tested? The existing tests Author: gatorsmile <gatorsmile@gmail.com> Closes #19913 from gatorsmile/eventtimewatermark.
## What changes were proposed in this pull request? There was a bug in Univocity Parser that causes the issue in SPARK-22516. This was fixed by upgrading from 2.5.4 to 2.5.9 version of the library : **Executing** ``` spark.read.option("header","true").option("inferSchema", "true").option("multiLine", "true").option("comment", "g").csv("test_file_without_eof_char.csv").show() ``` **Before** ``` ERROR Executor: Exception in task 0.0 in stage 6.0 (TID 6) com.univocity.parsers.common.TextParsingException: java.lang.IllegalArgumentException - Unable to skip 1 lines from line 2. End of input reached ... Internal state when error was thrown: line=3, column=0, record=2, charIndex=31 at com.univocity.parsers.common.AbstractParser.handleException(AbstractParser.java:339) at com.univocity.parsers.common.AbstractParser.parseNext(AbstractParser.java:475) at org.apache.spark.sql.execution.datasources.csv.UnivocityParser$$anon$1.next(UnivocityParser.scala:281) at scala.collection.Iterator$$anon$11.next(Iterator.scala:409) ``` **After** ``` +-------+-------+ |column1|column2| +-------+-------+ | abc| def| +-------+-------+ ``` ## How was this patch tested? The already existing `CSVSuite.commented lines in CSV data` test was extended to parse the file also in multiline mode. The test input file was modified to also include a comment in the last line. Author: smurakozi <smurakozi@gmail.com> Closes #19906 from smurakozi/SPARK-22516.
…variables ## What changes were proposed in this pull request? CreateNamedStruct and InSet are using a global variable which is not needed. This can generate some unneeded entries in the constant pool. The PR removes the unnecessary mutable states and makes them local variables. ## How was this patch tested? added UT Author: Marco Gaido <marcogaido91@gmail.com> Author: Marco Gaido <mgaido@hortonworks.com> Closes #19896 from mgaido91/SPARK-22693.
## What changes were proposed in this pull request? This PR upgrade Janino version to 3.0.8. [Janino 3.0.8](https://janino-compiler.github.io/janino/changelog.html) includes an important fix to reduce the number of constant pool entries by using 'sipush' java bytecode. * SIPUSH bytecode is not used for short integer constant [#33](janino-compiler/janino#33). Please see detail in [this discussion thread](#19518 (comment)). ## How was this patch tested? Existing tests Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com> Closes #19890 from kiszk/SPARK-22688.
…set() ## What changes were proposed in this pull request? BytesToBytesMap doesn't update peak memory usage before shrinking back to initial capacity in reset(), so after a disk spill one never knows what was the size of hash table was before spilling. ## How was this patch tested? Checked manually. Author: Juliusz Sompolski <julek@databricks.com> Closes #19915 from juliuszsompolski/SPARK-22721.
## What changes were proposed in this pull request? Since SPARK-20682, we have two `OrcFileFormat`s. This PR refactors ORC tests with three principles (with a few exceptions) 1. Move test suite into `sql/core`. 2. Create `HiveXXX` test suite in `sql/hive` by reusing `sql/core` test suite. 3. `OrcTest` will provide common helper functions and `val orcImp: String`. **Test Suites** *Native OrcFileFormat* - org.apache.spark.sql.hive.orc - OrcFilterSuite - OrcPartitionDiscoverySuite - OrcQuerySuite - OrcSourceSuite - o.a.s.sql.hive.orc - OrcHadoopFsRelationSuite *Hive built-in OrcFileFormat* - o.a.s.sql.hive.orc - HiveOrcFilterSuite - HiveOrcPartitionDiscoverySuite - HiveOrcQuerySuite - HiveOrcSourceSuite - HiveOrcHadoopFsRelationSuite **Hierarchy** ``` OrcTest -> OrcSuite -> OrcSourceSuite -> OrcQueryTest -> OrcQuerySuite -> OrcPartitionDiscoveryTest -> OrcPartitionDiscoverySuite -> OrcFilterSuite HadoopFsRelationTest -> OrcHadoopFsRelationSuite -> HiveOrcHadoopFsRelationSuite ``` Please note the followings. - Unlike the other test suites, `OrcHadoopFsRelationSuite` doesn't inherit `OrcTest`. It is inside `sql/hive` like `ParquetHadoopFsRelationSuite` due to the dependencies and follows the existing convention to use `val dataSourceName: String` - `OrcFilterSuite`s cannot reuse test cases due to the different function signatures using Hive 1.2.1 ORC classes and Apache ORC 1.4.1 classes. ## How was this patch tested? Pass the Jenkins tests with reorganized test suites. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #19882 from dongjoon-hyun/SPARK-22672.
## What changes were proposed in this pull request? Similar to #19842 , we should also make `ColumnarRow` an immutable view, and move forward to make `ColumnVector` public. ## How was this patch tested? Existing tests. The performance concern should be same as #19842 . Author: Wenchen Fan <wenchen@databricks.com> Closes #19898 from cloud-fan/row-id.
## What changes were proposed in this pull request? This PR accomplishes the following two items. 1. Reduce # of global variables from two to one for generated code of `Case` and `Coalesce` and remove global variables for generated code of `In`. 2. Make lifetime of global variable local within an operation Item 1. reduces # of constant pool entries in a Java class. Item 2. ensures that an variable is not passed to arguments in a method split by `CodegenContext.splitExpressions()`, which is addressed by #19865. ## How was this patch tested? Added new tests into `PredicateSuite`, `NullExpressionsSuite`, and `ConditionalExpressionSuite`. Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com> Closes #19901 from kiszk/SPARK-22705.
…ions - Implemented methods getInt, getLong, getBoolean for DataSourceV2Options - Added new unit tests to exercise these methods Author: Sunitha Kambhampati <skambha@us.ibm.com> Closes #19902 from skambha/spark22452.
## What changes were proposed in this pull request? I propose that BlockManagerMasterEndpoint.removeRdd() should catch and log any IOExceptions it receives. As it is now, the exception can bubble up to the main thread and kill user applications when called from RDD.unpersist(). I think this change is a better experience for the end user. I chose to catch the exception in BlockManagerMasterEndpoint.removeRdd() instead of RDD.unpersist() because this way the RDD.unpersist() blocking option will still work correctly. Otherwise, blocking will get short circuited by the first error. ## How was this patch tested? This patch was tested with a job that shows the job killing behavior mentioned above. rxin, it looks like you originally wrote this method, I would appreciate it if you took a look. Thanks. This contribution is my original work and is licensed under the project's open source license. Author: Brad Kaiser <kaiserb@us.ibm.com> Closes #19836 from brad-kaiser/catch-unpersist-exception.
…FileFormat ## What changes were proposed in this pull request? To support vectorization in native OrcFileFormat later, we need to use `buildReaderWithPartitionValues` instead of `buildReader` like ParquetFileFormat. This PR replaces `buildReader` with `buildReaderWithPartitionValues`. ## How was this patch tested? Pass the Jenkins with the existing test cases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #19907 from dongjoon-hyun/SPARK-ORC-BUILD-READER.
…bles for struct ## What changes were proposed in this pull request? GenerateSafeProjection is defining a mutable state for each struct, which is not needed. This is bad for the well known issues related to constant pool limits. The PR replace the global variable with a local one. ## How was this patch tested? added UT Author: Marco Gaido <marcogaido91@gmail.com> Closes #19914 from mgaido91/SPARK-22699.
…ariables ## What changes were proposed in this pull request? Some objects functions are using global variables which are not needed. This can generate some unneeded entries in the constant pool. The PR replaces the unneeded global variables with local variables. ## How was this patch tested? added UTs Author: Marco Gaido <mgaido@hortonworks.com> Author: Marco Gaido <marcogaido91@gmail.com> Closes #19908 from mgaido91/SPARK-22696.
…e in scala-2.12
…a-2.12 and JDK9
## What changes were proposed in this pull request?
Some compile error after upgrading to scala-2.12
```javascript
spark_source/core/src/main/scala/org/apache/spark/executor/Executor.scala:455: ambiguous reference to overloaded definition, method limit in class ByteBuffer of type (x$1: Int)java.nio.ByteBuffer
method limit in class Buffer of type ()Int
match expected type ?
val resultSize = serializedDirectResult.limit
error
```
The limit method was moved from ByteBuffer to the superclass Buffer and it can no longer be called without (). The same reason for position method.
```javascript
/home/zly/prj/oss/jdk9_HOS_SOURCE/spark_source/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/ScriptTransformationExec.scala:427: ambiguous reference to overloaded definition, [error] both method putAll in class Properties of type (x$1: java.util.Map[_, _])Unit [error] and method putAll in class Hashtable of type (x$1: java.util.Map[_ <: Object, _ <: Object])Unit [error] match argument types (java.util.Map[String,String])
[error] props.putAll(outputSerdeProps.toMap.asJava)
[error] ^
```
This is because the key type is Object instead of String which is unsafe.
## How was this patch tested?
running tests
Please review http://spark.apache.org/contributing.html before opening a pull request.
Author: kellyzly <kellyzly@126.com>
Closes #19854 from kellyzly/SPARK-22660.
## What changes were proposed in this pull request?
The current time complexity of ConstantPropagation is O(n^2), which can be slow when the query is complex.
Refactor the implementation with O( n ) time complexity, and some pruning to avoid traversing the whole `Condition`
## How was this patch tested?
Unit test.
Also simple benchmark test in ConstantPropagationSuite
```
val condition = (1 to 500).map{_ => Rand(0) === Rand(0)}.reduce(And)
val query = testRelation
.select(columnA)
.where(condition)
val start = System.currentTimeMillis()
(1 to 40).foreach { _ =>
Optimize.execute(query.analyze)
}
val end = System.currentTimeMillis()
println(end - start)
```
Run time before changes: 18989ms (474ms per loop)
Run time after changes: 1275 ms (32ms per loop)
Author: Wang Gengliang <ltnwgl@gmail.com>
Closes #19912 from gengliangwang/ConstantPropagation.
GulajavaMinistudio
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Nov 10, 2020
### What changes were proposed in this pull request?
Push down filter through expand. For case below:
```
create table t1(pid int, uid int, sid int, dt date, suid int) using parquet;
create table t2(pid int, vs int, uid int, csid int) using parquet;
SELECT
years,
appversion,
SUM(uusers) AS users
FROM (SELECT
Date_trunc('year', dt) AS years,
CASE
WHEN h.pid = 3 THEN 'iOS'
WHEN h.pid = 4 THEN 'Android'
ELSE 'Other'
END AS viewport,
h.vs AS appversion,
Count(DISTINCT u.uid) AS uusers
,Count(DISTINCT u.suid) AS srcusers
FROM t1 u
join t2 h
ON h.uid = u.uid
GROUP BY 1,
2,
3) AS a
WHERE viewport = 'iOS'
GROUP BY 1,
2
```
Plan. before this pr:
```
== Physical Plan ==
*(5) HashAggregate(keys=[years#30, appversion#32], functions=[sum(uusers#33L)])
+- Exchange hashpartitioning(years#30, appversion#32, 200), true, [id=#251]
+- *(4) HashAggregate(keys=[years#30, appversion#32], functions=[partial_sum(uusers#33L)])
+- *(4) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12], functions=[count(if ((gid#44 = 1)) u.`uid`#47 else null)])
+- Exchange hashpartitioning(date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, 200), true, [id=#246]
+- *(3) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12], functions=[partial_count(if ((gid#44 = 1)) u.`uid`#47 else null)])
+- *(3) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44], functions=[])
+- Exchange hashpartitioning(date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44, 200), true, [id=#241]
+- *(2) HashAggregate(keys=[date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44], functions=[])
+- *(2) Filter (CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46 = iOS)
+- *(2) Expand [ArrayBuffer(date_trunc(year, cast(dt#9 as timestamp), Some(Etc/GMT+7)), CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END, vs#12, uid#7, null, 1), ArrayBuffer(date_trunc(year, cast(dt#9 as timestamp), Some(Etc/GMT+7)), CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END, vs#12, null, suid#10, 2)], [date_trunc('year', CAST(u.`dt` AS TIMESTAMP))#45, CASE WHEN (h.`pid` = 3) THEN 'iOS' WHEN (h.`pid` = 4) THEN 'Android' ELSE 'Other' END#46, vs#12, u.`uid`#47, u.`suid`#48, gid#44]
+- *(2) Project [uid#7, dt#9, suid#10, pid#11, vs#12]
+- *(2) BroadcastHashJoin [uid#7], [uid#13], Inner, BuildRight
:- *(2) Project [uid#7, dt#9, suid#10]
: +- *(2) Filter isnotnull(uid#7)
: +- *(2) ColumnarToRow
: +- FileScan parquet default.t1[uid#7,dt#9,suid#10] Batched: true, DataFilters: [isnotnull(uid#7)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-bin-hadoop3.2/spark-warehouse/t1], PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<uid:int,dt:date,suid:int>
+- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[2, int, true] as bigint))), [id=#233]
+- *(1) Project [pid#11, vs#12, uid#13]
+- *(1) Filter isnotnull(uid#13)
+- *(1) ColumnarToRow
+- FileScan parquet default.t2[pid#11,vs#12,uid#13] Batched: true, DataFilters: [isnotnull(uid#13)], Format: Parquet, Location: InMemoryFileIndex[file:/root/spark-3.0.0-bin-hadoop3.2/spark-warehouse/t2], PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<pid:int,vs:int,uid:int>
```
Plan. after. this pr. :
```
== Physical Plan ==
AdaptiveSparkPlan isFinalPlan=false
+- HashAggregate(keys=[years#0, appversion#2], functions=[sum(uusers#3L)], output=[years#0, appversion#2, users#5L])
+- Exchange hashpartitioning(years#0, appversion#2, 5), true, [id=#71]
+- HashAggregate(keys=[years#0, appversion#2], functions=[partial_sum(uusers#3L)], output=[years#0, appversion#2, sum#22L])
+- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12], functions=[count(distinct uid#7)], output=[years#0, appversion#2, uusers#3L])
+- Exchange hashpartitioning(date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, 5), true, [id=#67]
+- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12], functions=[partial_count(distinct uid#7)], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, count#27L])
+- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7], functions=[], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7])
+- Exchange hashpartitioning(date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7, 5), true, [id=#63]
+- HashAggregate(keys=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles)) AS date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END AS CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7], functions=[], output=[date_trunc(year, cast(dt#9 as timestamp), Some(America/Los_Angeles))#23, CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END#24, vs#12, uid#7])
+- Project [uid#7, dt#9, pid#11, vs#12]
+- BroadcastHashJoin [uid#7], [uid#13], Inner, BuildRight, false
:- Filter isnotnull(uid#7)
: +- FileScan parquet default.t1[uid#7,dt#9] Batched: true, DataFilters: [isnotnull(uid#7)], Format: Parquet, Location: InMemoryFileIndex[file:/private/var/folders/4l/7_c5c97s1_gb0d9_d6shygx00000gn/T/warehouse-c069d87..., PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<uid:int,dt:date>
+- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[2, int, false] as bigint)),false), [id=#58]
+- Filter ((CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END = iOS) AND isnotnull(uid#13))
+- FileScan parquet default.t2[pid#11,vs#12,uid#13] Batched: true, DataFilters: [(CASE WHEN (pid#11 = 3) THEN iOS WHEN (pid#11 = 4) THEN Android ELSE Other END = iOS), isnotnull..., Format: Parquet, Location: InMemoryFileIndex[file:/private/var/folders/4l/7_c5c97s1_gb0d9_d6shygx00000gn/T/warehouse-c069d87..., PartitionFilters: [], PushedFilters: [IsNotNull(uid)], ReadSchema: struct<pid:int,vs:int,uid:int>
```
### Why are the changes needed?
Improve performance, filter more data.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Added UT
Closes apache#30278 from AngersZhuuuu/SPARK-33302.
Authored-by: angerszhu <angers.zhu@gmail.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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