lanyuanxiaoyao/hudi
1
0
Fork 0
Code Activity

[HUDI-3485] Adding scheduler pool configs for async clustering (#5043)

Browse Source
This commit is contained in:
Sivabalan Narayanan
2022-03-29 18:27:45 -07:00
committed by GitHub
parent 5c1b482a1b
commit 4fed8dd319
10 changed files with 72 additions and 19 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/HoodieStreamingSink.scala
View File

@@ -205,7 +205,8 @@ class HoodieStreamingSink(sqlContext: SQLContext,
protected def triggerAsyncClustering(client: SparkRDDWriteClient[HoodieRecordPayload[Nothing]]): Unit = {
if (null == asyncClusteringService) {
log.info("Triggering async clustering!")
asyncClusteringService = new SparkStreamingAsyncClusteringService(client)
asyncClusteringService = new SparkStreamingAsyncClusteringService(new HoodieSparkEngineContext(new JavaSparkContext(sqlContext.sparkContext)),
client)
asyncClusteringService.start(new Function[java.lang.Boolean, java.lang.Boolean] {
override def apply(errored: lang.Boolean): lang.Boolean = {
log.info(s"Async clustering service shutdown. Errored ? $errored")

11
hudi-spark-datasource/hudi-spark-common/src/main/scala/org/apache/hudi/SparkConfigs.scala
View File

@@ -27,9 +27,9 @@ object SparkConfigs {
/*
When async compaction is enabled (deltastreamer or streaming sink), users might be interested to set custom
scheduling configs for regular writes and async compaction. This is the property used to set custom scheduler config
file with spark. In Deltastreamer, the file is generated within hudi and set if necessary. Where as in case of streaming
sink, users have to set this property when they invoke spark shell.
scheduling configs for regular writes and async table services like compaction and clustering. This is the property
used to set custom scheduler config file with spark. In Deltastreamer, the file is generated within hudi and set if
necessary. Where as in case of streaming sink, users have to set this property when they invoke spark shell.
Sample format of the file contents.
<?xml version="1.0"?>
<allocations>
@@ -43,6 +43,11 @@ object SparkConfigs {
<weight>3</weight>
<minShare>1</minShare>
</pool>
<pool name="hoodiecluster">
<schedulingMode>FAIR</schedulingMode>
<weight>2</weight>
<minShare>1</minShare>
</pool>
</allocations>
*/
val SPARK_SCHEDULER_ALLOCATION_FILE_KEY = "spark.scheduler.allocation.file"