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From Vineet Mishra <clearmido...@gmail.com>
Subject Re: Storm Field Grouping with specific fields
Date Mon, 23 Feb 2015 13:45:05 GMT
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 <ncleung@gmail.com> 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" <clearmidoubt@gmail.com> 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 <clearmidoubt@gmail.com>
>> 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!
>>>
>>
>>

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