[
https://issues.apache.org/jira/browse/SPARK-43221?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Qiang Yang updated SPARK-43221:
-------------------------------
Description:
Spark on Yarn Cluster
When multiple executors exist on a node, and the same block exists on both
executors, with some in memory and some on disk.
Probabilistically, the executor failed to obtain the block,throw Exception:
java.lang.ArrayIndexOutofBoundsException: 0
at
org.apache.spark.broadcast.TorrentBroadcast.$anonfun$readBlocks$1(TorrentBroadcast.scala:183)
Next, I will replay the process of the problem occurring:
step 1:
The executor requests the driver to obtain block
information(locationsAndStatusOption). The input parameters are BlockId and the
host of its own node. Please note that it does not carry port information
{code:java}
// private[spark] def getRemoteBlock[T](
blockId: BlockId,
bufferTransformer: ManagedBuffer => T): Option[T] = {
logDebug(s"Getting remote block $blockId")
require(blockId != null, "BlockId is null") // Because all the remote
blocks are registered in driver, it is not necessary to ask
// all the storage endpoints to get block status.
val locationsAndStatusOption = master.getLocationsAndStatus(blockId,
blockManagerId.host) {code}
step 2:
was:
Spark on Yarn Cluster
When multiple executors exist on a node, and the same block exists on both
executors, with some in memory and some on disk.
Probabilistically, the executor failed to obtain the block,throw Exception:
java.lang.ArrayIndexOutofBoundsException: 0
at
org.apache.spark.broadcast.TorrentBroadcast.$anonfun$readBlocks$1(TorrentBroadcast.scala:183)
Next, I will replay the process of the problem occurring:
step 1:
The executor requests the driver to obtain block
information(locationsAndStatusOption). The input parameters are BlockId and the
host of its own node. Please note that it does not carry port information
step 2:
> Executor obtained error information
> ------------------------------------
>
> Key: SPARK-43221
> URL: https://issues.apache.org/jira/browse/SPARK-43221
> Project: Spark
> Issue Type: Bug
> Components: Block Manager
> Affects Versions: 3.1.1, 3.2.0, 3.3.0
> Reporter: Qiang Yang
> Priority: Major
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> Spark on Yarn Cluster
> When multiple executors exist on a node, and the same block exists on both
> executors, with some in memory and some on disk.
> Probabilistically, the executor failed to obtain the block,throw Exception:
> java.lang.ArrayIndexOutofBoundsException: 0
> at
> org.apache.spark.broadcast.TorrentBroadcast.$anonfun$readBlocks$1(TorrentBroadcast.scala:183)
>
> Next, I will replay the process of the problem occurring:
> step 1:
> The executor requests the driver to obtain block
> information(locationsAndStatusOption). The input parameters are BlockId and
> the host of its own node. Please note that it does not carry port information
> {code:java}
> // private[spark] def getRemoteBlock[T](
> blockId: BlockId,
> bufferTransformer: ManagedBuffer => T): Option[T] = {
> logDebug(s"Getting remote block $blockId")
> require(blockId != null, "BlockId is null") // Because all the remote
> blocks are registered in driver, it is not necessary to ask
> // all the storage endpoints to get block status.
> val locationsAndStatusOption = master.getLocationsAndStatus(blockId,
> blockManagerId.host) {code}
> step 2:
>
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