[
https://issues.apache.org/jira/browse/SPARK-12494?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15204698#comment-15204698
]
Sean Owen commented on SPARK-12494:
-----------------------------------
Is your input empty? what's at /tmp/myhdfs/kmeans?
If your data is on HDFS then my guess that it's a local file issue is wrong.
If this is the exception on empty input, it's not great, but it's possible.
It's an example, so is assuming you're adding valid data rather than showing a
bunch of arg checking.
> Array out of bound Exception in KMeans Yarn Mode
> ------------------------------------------------
>
> Key: SPARK-12494
> URL: https://issues.apache.org/jira/browse/SPARK-12494
> Project: Spark
> Issue Type: Bug
> Components: MLlib
> Affects Versions: 1.5.0
> Reporter: Anandraj
> Attachments: vectors1.tar.gz
>
>
> Hi,
> I am try to run k-means clustering on the word2vec data. I tested the code in
> local mode with small data. Clustering completes fine. But, when I run with
> same data on Yarn Cluster mode, it fails below error.
> 15/12/23 00:49:01 ERROR yarn.ApplicationMaster: User class threw exception:
> java.lang.ArrayIndexOutOfBoundsException: 0
> java.lang.ArrayIndexOutOfBoundsException: 0
> at
> scala.collection.mutable.WrappedArray$ofRef.apply(WrappedArray.scala:126)
> at
> org.apache.spark.mllib.clustering.KMeans$$anonfun$19.apply(KMeans.scala:377)
> at
> org.apache.spark.mllib.clustering.KMeans$$anonfun$19.apply(KMeans.scala:377)
> at scala.Array$.tabulate(Array.scala:331)
> at
> org.apache.spark.mllib.clustering.KMeans.initKMeansParallel(KMeans.scala:377)
> at
> org.apache.spark.mllib.clustering.KMeans.runAlgorithm(KMeans.scala:249)
> at org.apache.spark.mllib.clustering.KMeans.run(KMeans.scala:213)
> at org.apache.spark.mllib.clustering.KMeans$.train(KMeans.scala:520)
> at org.apache.spark.mllib.clustering.KMeans$.train(KMeans.scala:531)
> at
> com.tempurer.intelligence.adhocjobs.spark.kMeans$delayedInit$body.apply(kMeans.scala:24)
> at scala.Function0$class.apply$mcV$sp(Function0.scala:40)
> at
> scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
> at scala.App$$anonfun$main$1.apply(App.scala:71)
> at scala.App$$anonfun$main$1.apply(App.scala:71)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:32)
> at scala.App$class.main(App.scala:71)
> at
> com.tempurer.intelligence.adhocjobs.spark.kMeans$.main(kMeans.scala:9)
> at com.tempurer.intelligence.adhocjobs.spark.kMeans.main(kMeans.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:525)
> 15/12/23 00:49:01 INFO yarn.ApplicationMaster: Final app status: FAILED,
> exitCode: 15, (reason: User class threw exception:
> java.lang.ArrayIndexOutOfBoundsException: 0)
> In Local mode with large data(2375849 vectors of size 200) , the first
> sampling stage completes. Second stage suspends execution without any error
> message. No Active execution in progress. I could only see the below warning
> message
> 15/12/23 01:24:13 INFO TaskSetManager: Finished task 9.0 in stage 1.0 (TID
> 37) in 29 ms on localhost (4/34)
> 15/12/23 01:24:14 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:14 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 2 total executors!
> 15/12/23 01:24:15 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:15 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 3 total executors!
> 15/12/23 01:24:16 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:16 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 4 total executors!
> 15/12/23 01:24:17 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:17 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 5 total executors!
> 15/12/23 01:24:18 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:18 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 6 total executors!
> 15/12/23 01:24:19 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:19 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 7 total executors!
> 15/12/23 01:24:20 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:20 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 8 total executors!
> 15/12/23 01:24:21 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:21 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 9 total executors!
> 15/12/23 01:24:22 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:22 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 10 total executors!
> 15/12/23 01:24:23 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:23 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 11 total executors!
> 15/12/23 01:24:24 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:24 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 12 total executors!
> 15/12/23 01:24:25 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:25 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 13 total executors!
> 15/12/23 01:24:26 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:26 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 14 total executors!
> 15/12/23 01:24:27 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:27 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 15 total executors!
> 15/12/23 01:24:28 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:28 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 16 total executors!
> 15/12/23 01:24:29 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:29 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 17 total executors!
> 15/12/23 01:24:30 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:30 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 18 total executors!
> 15/12/23 01:24:31 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:31 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 19 total executors!
> 15/12/23 01:24:32 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:32 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 20 total executors!
> 15/12/23 01:24:33 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:33 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 21 total executors!
> 15/12/23 01:24:34 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:34 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 22 total executors!
> 15/12/23 01:24:35 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:35 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 23 total executors!
> 15/12/23 01:24:36 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:36 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 24 total executors!
> 15/12/23 01:24:37 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:37 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 25 total executors!
> 15/12/23 01:24:38 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:38 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 26 total executors!
> 15/12/23 01:24:39 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:39 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 27 total executors!
> 15/12/23 01:24:40 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:40 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 28 total executors!
> 15/12/23 01:24:41 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:41 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 29 total executors!
> 15/12/23 01:24:42 WARN SparkContext: Requesting executors is only supported
> in coarse-grained mode
> 15/12/23 01:24:42 WARN ExecutorAllocationManager: Unable to reach the cluster
> manager to request 30 total executors!
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
