Hi Nathan, Thanks for your revert but eventually what I am following is the same approach you have mentioned but still couldn't get the benefit of parallelism, so just to brief I have 3 node cluster setup with 1 supervisor and 2 workers.
After running the instance, I could see that multiple tasks are running in the same node. *Id* *Uptime* *Host* *Port* *Emitted* *Transferred* *Capacity (last 10m)* *Execute latency (ms)* *Executed* *Process latency (ms)* *Acked* *Failed* *[5-5]}* *1m 56s* *ip-20-0-0-75* *6703* <http://ip-20-0-0-75:8000/log?file=worker-6703.log> *0* *0* *0.296* *0.02* *1723420* *0.02* *1723420* *0* [4-4]} 30m 4s ip-20-0-0-78 6703 <http://ip-20-0-0-78:8000/log?file=worker-6703.log> 0 0 0 0.029 9700 0.043 9720 0 [3-3]} 1m 56s ip-20-0-0-75 6703 <http://ip-20-0-0-75:8000/log?file=worker-6703.log> 0 0 0.001 0.025 2380 0.017 2360 0 [2-2]} 30m 4s ip-20-0-0-78 6703 <http://ip-20-0-0-78:8000/log?file=worker-6703.log> 0 0 0.004 0.025 400680 0.024 400680 0 [1-1]} 1m 56s ip-20-0-0-75 6703 <http://ip-20-0-0-75:8000/log?file=worker-6703.log> 0 0 0.019 0.023 96480 0.02 96500 0 Which seems to the reason behind why their is lag in running the topology. I was looking out a way to curb this gap! Thanks! On Mon, Feb 23, 2015 at 6:30 PM, Nathan Leung <[email protected]> wrote: > You can put user and host in separate tuple fields and do fields grouping > on those fields. > On Feb 23, 2015 6:18 AM, "Vineet Mishra" <[email protected]> wrote: > >> I tried looking for a solution and could find this, CustomStreamGrouping >> >> I guess this should help me out, but I am getting an exception while >> implementing this. >> >> java.lang.RuntimeException: java.lang.IndexOutOfBoundsException at >> backtype.storm.utils.DisruptorQueue.consumeBatchToCursor(DisruptorQueue.java:128) >> at >> backtype.storm.utils.DisruptorQueue.consumeBatchWhenAvailable(DisruptorQueue.java:99) >> at >> backtype.storm.disruptor$consume_batch_when_available.invoke(disruptor.clj:80) >> at >> backtype.storm.daemon.executor$fn__3441$fn__3453$fn__3500.invoke(executor.clj:748) >> at backtype.storm.util$async_loop$fn__464.invoke(util.clj:463) at >> clojure.lang.AFn.run(AFn.java:24) at java.lang.Thread.run(Thread.java:745) >> Caused by: java.lang.IndexOutOfBoundsException at >> clojure.lang.PersistentVector.arrayFor(PersistentVector.java:107) at >> clojure.lang.PersistentVector.nth(PersistentVector.java:111) at >> clojure.lang.APersistentVector.get(APersistentVector.java:171) at >> com.sd.dwh.kafka.storm.plugin.HostAPIGrouping.chooseTasks(HostAPIGrouping.java:24) >> at >> backtype.storm.daemon.executor$mk_custom_grouper$fn__3151.invoke(executor.clj:49) >> at backtype.storm.daemon.task$mk_tasks_fn$fn__3101.invoke(task.clj:158) at >> backtype.storm.daemon.executor$fn__3441$fn__3453$bolt_emit__3480.invoke(executor.clj:663) >> at >> backtype.storm.daemon.executor$fn__3441$fn$reify__3486.emit(executor.clj:698) >> at backtype.storm.task.OutputCollector.emit(OutputCollector.java:203) at >> backtype.storm.task.OutputCollector.emit(OutputCollector.java:49) at >> backtype.storm.topology.BasicOutputCollector.emit(BasicOutputCollector.java:36) >> at >> backtype.storm.topology.BasicOutputCollector.emit(BasicOutputCollector.java:40) >> at com.sd.dwh.kafka.storm.ParserBolt.execute(ParserBolt.java:76) at >> backtype.storm.topology.BasicBoltExecutor.execute(BasicBoltExecutor.java:50) >> at >> backtype.storm.daemon.executor$fn__3441$tuple_action_fn__3443.invoke(executor.clj:633) >> at >> backtype.storm.daemon.executor$mk_task_receiver$fn__3364.invoke(executor.clj:401) >> at >> backtype.storm.disruptor$clojure_handler$reify__1447.onEvent(disruptor.clj:58) >> at >> backtype.storm.utils.DisruptorQueue.consumeBatchToCursor(DisruptorQueue.java:125) >> ... 6 more >> >> Let me know who has even faced the same issue. >> >> On Mon, Feb 23, 2015 at 3:45 PM, Vineet Mishra <[email protected]> >> wrote: >> >>> Hi All, >>> >>> I am having a topology with Kafka Spout Implementation with the >>> topologyBuilder mentioned below, >>> >>> TopologyBuilder builder=new TopologyBuilder(); >>> builder.setSpout("KafkaSpout", new KafkaSpout(kafkaConfig), 8); >>> builder.setBolt("Parser", new >>> ParserBolt()).globalGrouping("KafkaSpout"); >>> builder.setBolt("FileBolt", new >>> PersistBolt()).globalGrouping("Parser"); >>> >>> Config config=new Config(); >>> config.put(Config.TOPOLOGY_WORKERS, 4); >>> config.setNumWorkers(2); >>> config.setMaxSpoutPending(10); >>> config.setMaxTaskParallelism(10); >>> >>> I am having two level of Bolts, >>> >>> 1) Parser - Parsing of data and emitting a output tuple value which is >>> containing POJO serialized object >>> 2) Persist - Persisting of the forwarded data after some computation, >>> which is received through previous bolt(Parser). >>> >>> Now I was looking out a way for the last PersistBolt("FileBolt") I want >>> the field grouping on the parser bolt based on the some field value(POJO) >>> which is being emitted. >>> >>> >>> To make it more clear, >>> >>> Parser is emitting a POJO of the form, >>> >>> collector.emit(new Values(responseHandler)); >>> >>> where responseHandler is a POJO, >>> >>> public class ResponseHandler implements Serializable{ >>> >>> private String host = null; >>> private String user = null; >>> private String msg = null; >>> public String getHost() { >>> return host; >>> } >>> public void setHost(String host) { >>> this.host = host; >>> } >>> public String getUser() { >>> return hostName; >>> } >>> public void setuser(String user) { >>> this.user = user; >>> } >>> public String getMsg() { >>> return msg; >>> } >>> public void setMsg(String msg) { >>> this.msg = msg; >>> } >>> } >>> >>> Now I was looking out for a way to field group on the host and user >>> level. >>> >>> Actively looking for the way around! >>> >>> Thanks! >>> >> >>
