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From "Lizhengbing (bing, BIPA)" <zhengbing...@huawei.com>
Subject 答复: fail to run LBFS in 5G KDD data in spark 1.0.1?
Date Thu, 07 Aug 2014 03:41:25 GMT
I have test it in spark-1.1.0-SNAPSHOT.
It is ok now

发件人: Xiangrui Meng [mailto:mengxr@gmail.com]
发送时间: 2014年8月6日 23:12
收件人: Lizhengbing (bing, BIPA)
抄送: user@spark.apache.org
主题: Re: fail to run LBFS in 5G KDD data in spark 1.0.1?

Do you mind testing 1.1-SNAPSHOT and allocating more memory to the driver? I think the problem
is with the feature dimension. KDD data has more than 20M features and in v1.0.1, the driver
collects the partial gradients one by one, sums them up, does the update, and then sends the
new weights back to executors one by one. In 1.1-SNAPSHOT, we switched to multi-level tree
aggregation and torrent broadcasting.

For the driver memory, you can set it with spark-summit using `--driver-memory 30g`. It could
be confirmed by visiting the storage tab in the WebUI.

-Xiangrui

On Wed, Aug 6, 2014 at 1:58 AM, Lizhengbing (bing, BIPA) <zhengbing.li@huawei.com<mailto:zhengbing.li@huawei.com>>
wrote:
1 I don’t use spark_submit to run my problem and use spark context directly
val conf = new SparkConf()
             .setMaster("spark://123d101suse11sp3:7077")
             .setAppName("LBFGS")
             .set("spark.executor.memory", "30g")
             .set("spark.akka.frameSize","20")
val sc = new SparkContext(conf)

2 I use KDD data, size is about 5G

3 After I execute LBFGS.runLBFGS, at the stage of 7, the problem occus:

[cid:image001.png@01CFB234.3AA725F0]

14/08/06 16:44:45 INFO DAGScheduler: Failed to run aggregate at LBFGS.scala:201
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure:
Task 7.0:12 failed 4 times, most recent failure: TID 304 on host 123d103suse11sp3 failed for
unknown reason
Driver stacktrace:
        at org.apache.spark.scheduler.DAGScheduler.org<http://org.apache.spark.scheduler.DAGScheduler.org>$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1044)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1028)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1026)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1026)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:634)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:634)
        at scala.Option.foreach(Option.scala:236)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:634)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1229)
        at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
        at akka.actor.ActorCell.invoke(ActorCell.scala:456)
        at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
        at akka.dispatch.Mailbox.run(Mailbox.scala:219)
        at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
        at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
        at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
        at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)

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