Yes, only when using fine grained mode and replication (StorageLevel.MEMORY_ONLY_2 etc).
2015-03-27 19:06 GMT+01:00 Tathagata Das <t...@databricks.com>: > Does it fail with just Spark jobs (using storage levels) on non-coarse > mode? > > TD > > On Fri, Mar 27, 2015 at 4:39 AM, Ondrej Smola <ondrej.sm...@gmail.com> > wrote: > >> More info >> >> when using *spark.mesos.coarse* everything works as expected. I think >> this must be a bug in spark-mesos integration. >> >> >> 2015-03-27 9:23 GMT+01:00 Ondrej Smola <ondrej.sm...@gmail.com>: >> >>> It happens only when StorageLevel is used with 1 replica ( StorageLevel. >>> MEMORY_ONLY_2,StorageLevel.MEMORY_AND_DISK_2) , StorageLevel.MEMORY_ONLY >>> ,StorageLevel.MEMORY_AND_DISK works - the problems must be clearly >>> somewhere between mesos-spark . From console I see that spark is trying to >>> replicate to nodes -> nodes show up in Mesos active tasks ... but they >>> always fail with ClassNotFoundE. >>> >>> 2015-03-27 0:52 GMT+01:00 Tathagata Das <t...@databricks.com>: >>> >>>> Could you try running a simpler spark streaming program with receiver >>>> (may be socketStream) and see if that works. >>>> >>>> TD >>>> >>>> On Thu, Mar 26, 2015 at 2:08 PM, Ondrej Smola <ondrej.sm...@gmail.com> >>>> wrote: >>>> >>>>> Hi thanks for reply, >>>>> >>>>> yes I have custom receiver -> but it has simple logic .. pop ids from >>>>> redis queue -> load docs based on ids from elastic and store them in >>>>> spark. >>>>> No classloader modifications. I am running multiple Spark batch jobs (with >>>>> user supplied partitioning) and they have no problems, debug in local mode >>>>> show no errors. >>>>> >>>>> 2015-03-26 21:47 GMT+01:00 Tathagata Das <t...@databricks.com>: >>>>> >>>>>> Here are few steps to debug. >>>>>> >>>>>> 1. Try using replication from a Spark job: sc.parallelize(1 to 100, >>>>>> 100).persist(StorageLevel.MEMORY_ONLY_2).count() >>>>>> 2. If one works, then we know that there is probably nothing wrong >>>>>> with the Spark installation, and probably in the threads related to the >>>>>> receivers receiving the data. Are you writing a custom receiver? Are you >>>>>> somehow playing around with the class loader in the custom receiver? >>>>>> >>>>>> TD >>>>>> >>>>>> >>>>>> On Thu, Mar 26, 2015 at 10:59 AM, Ondrej Smola < >>>>>> ondrej.sm...@gmail.com> wrote: >>>>>> >>>>>>> Hi, >>>>>>> >>>>>>> I am running spark streaming v 1.3.0 (running inside Docker) on >>>>>>> Mesos 0.21.1. Spark streaming is started using Marathon -> docker >>>>>>> container >>>>>>> gets deployed and starts streaming (from custom Actor). Spark binary is >>>>>>> located on shared GlusterFS volume. Data is streamed from >>>>>>> Elasticsearch/Redis. When new batch arrives Spark tries to replicate it >>>>>>> but >>>>>>> fails with following error : >>>>>>> >>>>>>> 15/03/26 14:50:00 INFO MemoryStore: Block broadcast_0 of size 2840 >>>>>>> dropped from memory (free 278017782) >>>>>>> 15/03/26 14:50:00 INFO BlockManager: Removing block >>>>>>> broadcast_0_piece0 >>>>>>> 15/03/26 14:50:00 INFO MemoryStore: Block broadcast_0_piece0 of size >>>>>>> 1658 dropped from memory (free 278019440) >>>>>>> 15/03/26 14:50:00 INFO BlockManagerMaster: Updated info of block >>>>>>> broadcast_0_piece0 >>>>>>> 15/03/26 14:50:00 ERROR TransportRequestHandler: Error while >>>>>>> invoking RpcHandler#receive() on RPC id 7178767328921933569 >>>>>>> java.lang.ClassNotFoundException: >>>>>>> org/apache/spark/storage/StorageLevel >>>>>>> at java.lang.Class.forName0(Native Method) >>>>>>> at java.lang.Class.forName(Class.java:344) >>>>>>> at >>>>>>> org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:65) >>>>>>> at >>>>>>> java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1613) >>>>>>> at >>>>>>> java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518) >>>>>>> at >>>>>>> java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774) >>>>>>> at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351) >>>>>>> at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371) >>>>>>> at >>>>>>> org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:68) >>>>>>> at >>>>>>> org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:88) >>>>>>> at >>>>>>> org.apache.spark.network.netty.NettyBlockRpcServer.receive(NettyBlockRpcServer.scala:65) >>>>>>> at >>>>>>> org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:124) >>>>>>> at >>>>>>> org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:97) >>>>>>> at >>>>>>> org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:91) >>>>>>> at >>>>>>> org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:44) >>>>>>> at >>>>>>> io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) >>>>>>> at >>>>>>> io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333) >>>>>>> at >>>>>>> io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319) >>>>>>> at >>>>>>> io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103) >>>>>>> at >>>>>>> io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333) >>>>>>> at >>>>>>> io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319) >>>>>>> at >>>>>>> io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:163) >>>>>>> at >>>>>>> io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:333) >>>>>>> at >>>>>>> io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:319) >>>>>>> at >>>>>>> io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:787) >>>>>>> at >>>>>>> io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:130) >>>>>>> at >>>>>>> io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511) >>>>>>> at >>>>>>> io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468) >>>>>>> at >>>>>>> io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382) >>>>>>> at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354) >>>>>>> at >>>>>>> io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:116) >>>>>>> at java.lang.Thread.run(Thread.java:745) >>>>>>> 15/03/26 14:50:01 ERROR TransportRequestHandler: Error while >>>>>>> invoking RpcHandler#receive() on RPC id 9001562482648380222 >>>>>>> >>>>>>> From mesos UI i see unpacked spark binary and my assembly jar in >>>>>>> place (on running driver and on replication targets). I have other spark >>>>>>> BATCH jobs running from same base docker image OK. When there is no >>>>>>> incoming data exception is not thrown. Spark config : >>>>>>> >>>>>>> spark.master >>>>>>> >>>>>>> mesos://zk://incomparable-brush.maas:2181,cumbersome-match.maas:2181,voluminous-toys.maas:2181/mesos >>>>>>> spark.serializer org.apache.spark.serializer.KryoSerializer >>>>>>> spark.executor.uri >>>>>>> file:///master/spark/spark-1.3.0-bin-hadoop2.4.tgz >>>>>>> spark.local.dir /opt/spark_tmp >>>>>>> >>>>>>> spark.driver.port 41000 >>>>>>> spark.executor.port 41016 >>>>>>> spark.fileserver.port 41032 >>>>>>> spark.broadcast.port 41048 >>>>>>> spark.replClassServer.port 41064 >>>>>>> spark.blockManager.port 41080 >>>>>>> spark.ui.port 41096 >>>>>>> spark.history.ui.port 41112 >>>>>>> >>>>>>> Thanks for any help >>>>>>> >>>>>> >>>>>> >>>>> >>>> >>> >> >
