Thanks and apologies, I should I mentioned that in my question earlier. I am using storm 0.9.2 and using the inbuilt KafkaSpout. I do not implement any failure my self. Do I need to create my own custom KafkaSpout?
I have not set timeout for tuples. In fact I dont know where to set that. Here is my storm config if that is where I need to set the time out. But non of them say anything about tuple timeout. dev.zookeeper.path/tmp/dev-storm-zookeeperdrpc.childopts-Xmx768m drpc.invocations.port3773drpc.port3772drpc.queue.size128 drpc.request.timeout.secs600drpc.worker.threads64java.library.path /usr/local/lib:/opt/local/lib:/usr/liblogviewer.appender.nameA1 logviewer.childopts-Xmx128mlogviewer.port8000nimbus.childopts-Xmx1024m nimbus.cleanup.inbox.freq.secs600nimbus.file.copy.expiration.secs600 nimbus.hostnmcxstrmd001nimbus.inbox.jar.expiration.secs3600 nimbus.monitor.freq.secs10nimbus.reassigntruenimbus.supervisor.timeout.secs 60nimbus.task.launch.secs120nimbus.task.timeout.secs30 nimbus.thrift.max_buffer_size1048576nimbus.thrift.port6627 nimbus.topology.validatorbacktype.storm.nimbus.DefaultTopologyValidator storm.cluster.modedistributedstorm.local.dir/data/disk00/storm/localdir storm.local.mode.zmqfalsestorm.messaging.netty.buffer_size5242880 storm.messaging.netty.client_worker_threads1 storm.messaging.netty.flush.check.interval.ms10 storm.messaging.netty.max_retries30storm.messaging.netty.max_wait_ms1000 storm.messaging.netty.min_wait_ms100 storm.messaging.netty.server_worker_threads1 storm.messaging.netty.transfer.batch.size262144storm.messaging.transport backtype.storm.messaging.netty.Contextstorm.thrift.transport backtype.storm.security.auth.SimpleTransportPlugin storm.zookeeper.connection.timeout15000storm.zookeeper.port2181 storm.zookeeper.retry.interval1000 storm.zookeeper.retry.intervalceiling.millis30000storm.zookeeper.retry.times 5storm.zookeeper.root/stormstorm.zookeeper.serversnmcxstrmd001 storm.zookeeper.session.timeout20000supervisor.childopts-Xmx256m supervisor.enabletruesupervisor.heartbeat.frequency.secs5 supervisor.monitor.frequency.secs3supervisor.slots.ports 6700,6701,6702,6703,6704,6705,6706,6707,6708,6709,6710,6711,6712,6713,6714,6715,6716,6717,6718,6719,6720,6721,6722,6723,6724,6725,6726,6727,6728 supervisor.worker.start.timeout.secs120supervisor.worker.timeout.secs30 task.heartbeat.frequency.secs3task.refresh.poll.secs10 topology.acker.executorstopology.builtin.metrics.bucket.size.secs60 topology.debugfalsetopology.disruptor.wait.strategy com.lmax.disruptor.BlockingWaitStrategytopology.enable.message.timeoutstrue topology.error.throttle.interval.secs10topology.executor.receive.buffer.size 1024topology.executor.send.buffer.size1024 topology.fall.back.on.java.serializationtruetopology.kryo.factory backtype.storm.serialization.DefaultKryoFactory topology.max.error.report.per.interval5topology.max.spout.pending topology.max.task.parallelismtopology.message.timeout.secs30 topology.multilang.serializerbacktype.storm.multilang.JsonSerializer topology.receiver.buffer.size8topology.skip.missing.kryo.registrationsfalse topology.sleep.spout.wait.strategy.time.ms1topology.spout.wait.strategy backtype.storm.spout.SleepSpoutWaitStrategy topology.state.synchronization.timeout.secs60topology.stats.sample.rate0.05 topology.taskstopology.tick.tuple.freq.secstopology.transfer.buffer.size1024 topology.trident.batch.emit.interval.millis500topology.tuple.serializer backtype.storm.serialization.types.ListDelegateSerializer topology.worker.childoptstopology.worker.receiver.thread.count1 topology.worker.shared.thread.pool.size4topology.workers1 transactional.zookeeper.porttransactional.zookeeper.root/transactional transactional.zookeeper.serversui.childopts-Xmx768mui.port8080 worker.childopts-Xmx768mworker.heartbeat.frequency.secs1zmq.hwm0 zmq.linger.millis5000zmq.threads1 -- Kushan Maskey 817.403.7500 On Tue, Sep 9, 2014 at 9:23 AM, Naresh Kosgi <[email protected]> wrote: > What is your timeout setting for failing a tuple? Its hard to say what is > causing this issue without more information but the default timeout on > tuples is 30 seconds and for some tuples it maybe taking longer then 30 > seconds to process. Try increasing the timeout to 1 or 2 min? > > > "Why the ack/failure ack counts are so much higher than the number of > records I am trying to process?" > > how are you implementing the fail() method in your spout? on failure, > this method is called by the framework. It could be you are reemitting the > tuple to be processed and its failing again. This could be a reason why u > have more failed tuples then records > > On Tue, Sep 9, 2014 at 10:06 AM, Kushan Maskey < > [email protected]> wrote: > >> I have a batch job where I process more than 100k records from file. I >> post all these message to Kafka topic. I have a topology that goes and >> fetches these records and dumps them into Cassandra database and also >> updates solr and couch databases. >> >> I have been trying to run the process multiple times to make sure that >> the process completes successfully. It does run successfully sometimes and >> sometimes it errors out saying the following error that says "Too many >> tuple failures" in the storm UI. >> >> java.lang.RuntimeException: java.lang.RuntimeException: Too many tuple >> failures at >> backtype.storm.utils.DisruptorQueue.consumeBatchToCursor(DisruptorQueue.java:128) >> at backtype.storm.utils.DisruptorQueue.consumeBatch(DisruptorQueue.java:87) >> at backtype.storm.disruptor$consume_batch.invoke(disruptor.clj:76) at >> backtype.storm.daemon.executor$fn__5573$fn__5588$fn__5617.invoke(executor.clj:540) >> at backtype.storm.util$async_loop$fn__457.invoke(util.clj:431) at >> clojure.lang.AFn.run(AFn.java:24) at java.lang.Thread.run(Thread.java:744) >> Caused by: java.lang.RuntimeException: Too many tuple failures at >> storm.kafka.PartitionManager.fail(PartitionManager.java:210) at >> storm.kafka.KafkaSpout.fail(KafkaSpout.java:174) at >> backtype.storm.daemon.executor$fail_spout_msg.invoke(executor.clj:370) at >> backtype.storm.daemon.executor$fn$reify__5576.expire(executor.clj:430) at >> backtype.storm.utils.RotatingMap.rotate(RotatingMap.java:73) at >> backtype.storm.daemon.executor$fn__5573$tuple_action_fn__5579.invoke(executor.clj:435) >> at >> backtype.storm.daemon.executor$mk_task_receiver$fn__5564.invoke(executor.clj:402) >> at >> backtype.storm.disruptor$clojure_handler$reify__745.onEvent(disruptor.clj:58) >> at >> backtype.storm.utils.DisruptorQueue.consumeBatchToCursor(DisruptorQueue.java:125) >> ... 6 more >> >> once this failure happens, i also see that the number of records stored >> in Cassandra database if way much higher than the actual batch records >> count. How do I handle this error? Also when there is any kind of >> error/exception occurs then the ack failed values goes up form 0 to >> thousands. Why the ack/failure ack counts are so much higher thank the >> number of records I am trying to process? >> >> >> -- >> Kushan Maskey >> > >
