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From Thunder Stumpges <tstump...@ntent.com>
Subject RE: Old style "low level" Tasks with alternative deployment model(s)
Date Tue, 20 Mar 2018 04:58:19 GMT
And that last issue was mine. My setting override was not picked up and it was using GroupByContainerCount
instead. 
-Thanks,
Thunder


-----Original Message-----
From: Thunder Stumpges 
Sent: Monday, March 19, 2018 20:58
To: dev@samza.apache.org
Cc: Jagadish Venkatraman <jagadish1989@gmail.com>; tom@recursivedream.com; Yipan@linkedin.com;
Yi Pan <nickpan47@gmail.com>
Subject: RE: Old style "low level" Tasks with alternative deployment model(s)

Well I figured it out. My specific issue was due to a simple dependency problem where I had
gotten an older version of the Jackson-mapper library. However the code was throwing NoSuchMethodError
(an Error instead of Exception) and being silently dropped. I created a pull request to handle
any Throwable in ScheduleAfterDebounceTime. 
https://github.com/apache/samza/pull/450

I'm now running into an issue with the generation of the JobModel and the ProcessorId. The
ZkJobCoordinator has a ProcessorId that is a Guid, but when GroupByContainerIds class (my
TaskNameGrouper) creates the ContainerModels, it is using the ContainerId (a numeric value,
0,1,2,etc) as the ProcessorId (~ line 105). This results in the JobModel that is generated
and published immediately causing the processor to quit with this message:

INFO  o.apache.samza.zk.ZkJobCoordinator - New JobModel does not contain pid=38c637bf-9c2b-4856-afc4-5b1562711cfb.
Stopping this processor.

I was assuming I should be using GroupByContainerIds as my TaskNameGrouper. I don't see any
other promising implementations. Am I just missing something?

Thanks,
Thunder

JobModel
{
  "config" : {
  ...
  },
  "containers" : {
    "0" : {
      "tasks" : {
        "Partition 0" : {
          "task-name" : "Partition 0",
          "system-stream-partitions" : [ {
            "system" : "kafka",
            "partition" : 0,
            "stream" : "test_topic1"
          }, {
            "system" : "kafka",
            "partition" : 0,
            "stream" : "test_topic2"
          } ],
          "changelog-partition" : 0
        },
        "Partition 1" : {
          "task-name" : "Partition 1",
          "system-stream-partitions" : [ {
            "system" : "kafka",
            "partition" : 1,
            "stream" : "test_topic1"
          }, {
            "system" : "kafka",
            "partition" : 1,
            "stream" : "test_topic2"
          } ],
          "changelog-partition" : 1
        }
      },
      "container-id" : 0,
      "processor-id" : "0"
    }
  },
  "max-change-log-stream-partitions" : 2,
  "all-container-locality" : {
    "0" : null
  }
}

-----Original Message-----
From: Thunder Stumpges [mailto:tstumpges@ntent.com]
Sent: Friday, March 16, 2018 18:21
To: dev@samza.apache.org
Cc: Jagadish Venkatraman <jagadish1989@gmail.com>; tom@recursivedream.com; Yipan@linkedin.com;
Yi Pan <nickpan47@gmail.com>
Subject: RE: Old style "low level" Tasks with alternative deployment model(s)

Attached. I don't see any threads actually running this code which is odd. 

There's my main thread that's waiting for the whole thing to finish, the "debounce-thread-0"
(which logged the other surrounding messages below) has this:

"debounce-thread-0" #18 daemon prio=5 os_prio=0 tid=0x00007fa0fd719800 nid=0x21 waiting on
condition [0x00007fa0d0d45000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x00000006f166e350> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1081)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1067)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1127)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:745)

   Locked ownable synchronizers:
        - None

Thanks for having a look.
Thunder


-----Original Message-----
From: Prateek Maheshwari [mailto:prateekmi2@gmail.com]
Sent: Friday, March 16, 2018 17:02
To: dev@samza.apache.org
Cc: Jagadish Venkatraman <jagadish1989@gmail.com>; tom@recursivedream.com; Yipan@linkedin.com;
Yi Pan <nickpan47@gmail.com>
Subject: Re: Old style "low level" Tasks with alternative deployment model(s)

Hi Thunder,

Can you please take and attach a thread dump with this?

Thanks,
Prateek

On Fri, Mar 16, 2018 at 4:47 PM, Thunder Stumpges <tstumpges@ntent.com>
wrote:

> It appears it IS hung while serializing the JobModel... very strange! 
> I added some debug statements around the calls:
>
>       LOG.debug("Getting object mapper to serialize job model");  // 
> this IS printed
>       ObjectMapper mmapper = SamzaObjectMapper.getObjectMapper();
>       LOG.debug("Serializing job model"); // this IS printed
>       String jobModelStr = mmapper.writerWithDefaultPrettyPrinter
> ().writeValueAsString(jobModel);
>       LOG.info("jobModelAsString=" + jobModelStr); // this is NOT printed!
>
> Another thing I noticed is that "getObjectMapper" actually creates the 
> object mapper twice!
>
> 2018-03-16 23:09:24 logback 24985 [debounce-thread-0] DEBUG 
> org.apache.samza.zk.ZkUtils - Getting object mapper to serialize job 
> model
> 2018-03-16 23:09:24 logback 24994 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Creating new object mapper and simple module
> 2018-03-16 23:09:24 logback 25178 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Adding SerDes and mixins
> 2018-03-16 23:09:24 logback 25183 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Adding custom ContainerModel deserializer
> 2018-03-16 23:09:24 logback 25184 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Setting up naming strategy and registering module
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Done!
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Creating new object mapper and simple module
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Adding SerDes  and mixins
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Adding custom ContainerModel deserializer
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Setting up naming strategy and registering module
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> o.a.s.s.model.SamzaObjectMapper
> - Done!
> 2018-03-16 23:09:24 logback 25187 [debounce-thread-0] DEBUG 
> org.apache.samza.zk.ZkUtils - Serializing job model
>
> Could this ObjectMapper be a singleton? I see there is a private 
> static instance, but getObjectMapper creates a new one every time...
>
> Anyway, then it takes off to serialize the job model and never comes 
> back...
>
> Hoping someone has some idea here... the implementation for this 
> mostly comes from Jackson-mapper-asl, and I have the version that is 
> linked in the
> 0.14.0 tag:
> |    |    |    +--- org.codehaus.jackson:jackson-mapper-asl:1.9.13
> |    |    |    |    \--- org.codehaus.jackson:jackson-core-asl:1.9.13
>
> Thanks!
> Thunder
>
> -----Original Message-----
> From: Thunder Stumpges [mailto:tstumpges@ntent.com]
> Sent: Friday, March 16, 2018 15:29
> To: dev@samza.apache.org; Jagadish Venkatraman 
> <jagadish1989@gmail.com>
> Cc: tom@recursivedream.com; Yipan@linkedin.com; Yi Pan < 
> nickpan47@gmail.com>
> Subject: RE: Old style "low level" Tasks with alternative deployment
> model(s)
>
> So, my investigation starts at StreamProcessor.java.  Line 294 in 
> method
> onNewJobModel() logs an INFO message that it's starting a container. 
> This message never appears.
>
> I see that ZkJobCoordinator calls onNewJobModel from its 
> onNewJobModelConfirmed method which also logs an info message stating 
> "version X of the job model got confirmed". I never see this message 
> either, so I go up the chain some more.
>
> I DO see:
>
> 2018-03-16 21:43:58 logback 20498
> [ZkClient-EventThread-13-10.0.127.114:2181]
> INFO  o.apache.samza.zk.ZkJobCoordinator - 
> ZkJobCoordinator::onBecomeLeader
> - I became the leader!
> And
> 2018-03-16 21:44:18 logback 40712 [debounce-thread-0] INFO 
> o.apache.samza.zk.ZkJobCoordinator - 
> pid=91e07d20-ae33-4156-a5f3-534a95642133Generated
> new Job Model. Version = 1
>
> Which led me to method onDoProcessorChange line 210. I see that line, 
> but not the line below " Published new Job Model. Version =" so 
> something in here is not completing:
>
>     LOG.info("pid=" + processorId + "Generated new Job Model. Version = "
> + nextJMVersion);
>
>     // Publish the new job model
>     zkUtils.publishJobModel(nextJMVersion, jobModel);
>
>     // Start the barrier for the job model update
>     barrier.create(nextJMVersion, currentProcessorIds);
>
>     // Notify all processors about the new JobModel by updating 
> JobModel Version number
>     zkUtils.publishJobModelVersion(currentJMVersion, nextJMVersion);
>
>     LOG.info("pid=" + processorId + "Published new Job Model. Version = "
> + nextJMVersion);
>
> As I mentioned, after the line "Generated new Job Model. Version = 1" 
> I just get repeated zk ping responses.. no more application logging.
>
> The very next thing that's run is zkUtils.publishJobModel() which only 
> has two lines before another log statement (which I don't see):
>
>   public void publishJobModel(String jobModelVersion, JobModel jobModel) {
>     try {
>       ObjectMapper mmapper = SamzaObjectMapper.getObjectMapper();
>       String jobModelStr = mmapper.writerWithDefaultPrettyPrinter
> ().writeValueAsString(jobModel);
>       LOG.info("jobModelAsString=" + jobModelStr);
>       ...
>
> Could it really be getting hung up on one of these two lines? (seems 
> like it must be, but I don't see anything there that seems like it 
> would just hang). I'll keep troubleshooting, maybe add some more debug 
> logging and try again.
>
> Thanks for any guidance you all might have.
> -Thunder
>
>
> -----Original Message-----
> From: Thunder Stumpges [mailto:tstumpges@ntent.com]
> Sent: Friday, March 16, 2018 14:43
> To: dev@samza.apache.org; Jagadish Venkatraman 
> <jagadish1989@gmail.com>
> Cc: tom@recursivedream.com; Yipan@linkedin.com; Yi Pan < 
> nickpan47@gmail.com>
> Subject: RE: Old style "low level" Tasks with alternative deployment
> model(s)
>
> Well I have my stand-alone application in docker and running in 
> kubernetes. I think something isn't wired up all the way though, 
> because my task never actually gets invoked. I see no errors, however 
> I'm not getting the usual startup logs (checking existing offsets, 
> "entering run loop"...) My logs look like this:
>
> 2018-03-16 21:05:55 logback 50797 [debounce-thread-0] INFO 
> kafka.utils.VerifiableProperties
> - Verifying properties
> 2018-03-16 21:05:55 logback 50797 [debounce-thread-0] INFO 
> kafka.utils.VerifiableProperties
> - Property client.id is overridden to samza_admin-test_stream_task-1
> 2018-03-16 21:05:55 logback 50798 [debounce-thread-0] INFO 
> kafka.utils.VerifiableProperties
> - Property metadata.broker.list is overridden to
> test-kafka-kafka.test-svc:9092
> 2018-03-16 21:05:55 logback 50798 [debounce-thread-0] INFO 
> kafka.utils.VerifiableProperties
> - Property request.timeout.ms is overridden to 30000
> 2018-03-16 21:05:55 logback 50799 [debounce-thread-0] INFO 
> kafka.client.ClientUtils$ - Fetching metadata from broker
> BrokerEndPoint(0,test-kafka-kafka.test-svc,9092) with correlation id 0 
> for 1 topic(s) Set(dev_k8s.samza.test.topic)
> 2018-03-16 21:05:55 logback 50800 [debounce-thread-0] DEBUG 
> kafka.network.BlockingChannel - Created socket with SO_TIMEOUT = 30000 
> (requested 30000), SO_RCVBUF = 179680 (requested -1), SO_SNDBUF =
> 102400 (requested 102400), connectTimeoutMs = 30000.
> 2018-03-16 21:05:55 logback 50800 [debounce-thread-0] INFO 
> kafka.producer.SyncProducer - Connected to
> test-kafka-kafka.test-svc:9092 for producing
> 2018-03-16 21:05:55 logback 50804 [debounce-thread-0] INFO 
> kafka.producer.SyncProducer - Disconnecting from
> test-kafka-kafka.test-svc:9092
> 2018-03-16 21:05:55 logback 50804 [debounce-thread-0] DEBUG 
> kafka.client.ClientUtils$ - Successfully fetched metadata for 1
> topic(s)
> Set(dev_k8s.samza.test.topic)
> 2018-03-16 21:05:55 logback 50813 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - SystemStreamPartitionGrouper 
> org.apache.samza.container.grouper.stream.GroupByPartition@1a7158cc
> has grouped the SystemStreamPartitions into 10 tasks with the 
> following
> taskNames: [Partition 1, Partition 0, Partition 3, Partition 2, 
> Partition 5, Partition 4, Partition 7, Partition 6, Partition 9, 
> Partition 8]
> 2018-03-16 21:05:55 logback 50818 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 0 is being 
> assigned changelog partition 0.
> 2018-03-16 21:05:55 logback 50819 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 1 is being 
> assigned changelog partition 1.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 2 is being 
> assigned changelog partition 2.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 3 is being 
> assigned changelog partition 3.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 4 is being 
> assigned changelog partition 4.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 5 is being 
> assigned changelog partition 5.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 6 is being 
> assigned changelog partition 6.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 7 is being 
> assigned changelog partition 7.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 8 is being 
> assigned changelog partition 8.
> 2018-03-16 21:05:55 logback 50820 [debounce-thread-0] INFO 
> o.a.s.coordinator.JobModelManager$ - New task Partition 9 is being 
> assigned changelog partition 9.
> 2018-03-16 21:05:55 logback 50838 [main-SendThread(10.0.127.114:2181)]
> DEBUG org.apache.zookeeper.ClientCnxn - Reading reply 
> sessionid:0x1622c8b5fc01ac7, packet:: clientPath:null serverPath:null 
> finished:false header:: 23,4  replyHeader:: 23,14024,0  request::
> '/app-test_stream_task-1/dev_test_stream_task-1-coordinationData/
> JobModelGeneration/jobModelVersion,T  response::
> ,s{13878,13878,1521234010089,1521234010089,0,0,0,0,0,0,13878}
> 2018-03-16 21:05:55 logback 50838 [debounce-thread-0] INFO 
> o.apache.samza.zk.ZkJobCoordinator - 
> pid=a14a0434-a238-4ff6-935b-c78d906fe80dGenerated
> new Job Model. Version = 1
> 2018-03-16 21:06:05 logback 60848 [main-SendThread(10.0.127.114:2181)]
> DEBUG org.apache.zookeeper.ClientCnxn - Got ping response for sessionid:
> 0x1622c8b5fc01ac7 after 2ms
> 2018-03-16 21:06:15 logback 70856 [main-SendThread(10.0.127.114:2181)]
> DEBUG org.apache.zookeeper.ClientCnxn - Got ping response for sessionid:
> 0x1622c8b5fc01ac7 after 1ms
> 2018-03-16 21:06:25 logback 80865 [main-SendThread(10.0.127.114:2181)]
> DEBUG org.apache.zookeeper.ClientCnxn - Got ping response for sessionid:
> 0x1622c8b5fc01ac7 after 2ms ...
>
> The zk ping responses continue every 10 seconds, but no other activity 
> or messages occur.
> It looks like it gets as far as confirming the JobModel and grouping 
> the partitions, but nothing actually starts up.
>
> Any ideas?
> Thanks in advance!
> Thunder
>
>
> -----Original Message-----
> From: Thunder Stumpges [mailto:tstumpges@ntent.com]
> Sent: Thursday, March 15, 2018 16:35
> To: Jagadish Venkatraman <jagadish1989@gmail.com>
> Cc: dev@samza.apache.org; tom@recursivedream.com; Yipan@linkedin.com; 
> Yi Pan <nickpan47@gmail.com>
> Subject: RE: Old style "low level" Tasks with alternative deployment
> model(s)
>
> Thanks a lot for the info. I have something basically working at this 
> point! I have not integrated it with Docker nor Kubernetes yet, but it 
> does run from my local machine.
>
> I have determined that LocalApplicationRunner does NOT do config 
> rewriting. I had to write my own little “StandAloneApplicationRunner”
> that handles the “main” entrypoint. It does command parsing using 
> CommandLine, load config from ConfigFactory, and perform rewriting 
> before creating the new instance of LocalApplicationRunner. This is 
> all my StandAloneApplicationRunner contains:
>
>
> object StandAloneSamzaRunner extends App with LazyLogging {
>
>   // parse command line args just like JobRunner.
>   val cmdline = new ApplicationRunnerCommandLine
>   val options = cmdline.parser.parse(args: _*)
>   val config = cmdline.loadConfig(options)
>
>   val runner = new LocalApplicationRunner(Util.rewriteConfig(config))
>   runner.runTask()
>   runner.waitForFinish()
> }
>
> The only config settings I needed to make to use this runner were 
> (easily configured due to our central Consul config system and our rewriter) :
>
> # use the ZK based job coordinator
> job.coordinator.factory=org.apache.samza.zk.ZkJobCoordinatorFactory
> # need to use GroupByContainerIds instead of GroupByContainerCount 
> task.name.grouper.factory=org.apache.samza.container.grouper.task.
> GroupByContainerIdsFactory
> # ZKJC config
> job.coordinator.zk.connect=<our_zk_connection>
>
> I did run into one potential problem; as you see above, I have started 
> the task using runTask() and then to prevent my main method from 
> returning, I have called waitForFinish(). The first time I ran it, the 
> job itself failed because I had forgotten to override the task 
> grouper, and container count was pulled from our staging environment.
> There are some failures logged and it appears the JobCoordinator 
> fails, but it never returns from waitForFinish. Stack trace and continuation of log is
below:
>
> 2018-03-15 22:34:32 logback 77786 [debounce-thread-0] ERROR 
> o.a.s.zk.ScheduleAfterDebounceTime
> - Execution of action: OnProcessorChange failed.
> java.lang.IllegalArgumentException: Your container count (4) is larger 
> than your task count (2). Can't have containers with nothing to do, so 
> aborting.
>        at org.apache.samza.container.grouper.task.GroupByContainerCount.
> validateTasks(GroupByContainerCount.java:212)
>        at org.apache.samza.container.grouper.task.
> GroupByContainerCount.group(GroupByContainerCount.java:62)
>        at org.apache.samza.container.grouper.task.TaskNameGrouper.
> group(TaskNameGrouper.java:56)
>        at org.apache.samza.coordinator.JobModelManager$.readJobModel(
> JobModelManager.scala:266)
>        at org.apache.samza.coordinator.JobModelManager.readJobModel(
> JobModelManager.scala)
>        at org.apache.samza.zk.ZkJobCoordinator.generateNewJobModel(
> ZkJobCoordinator.java:306)
>        at org.apache.samza.zk.ZkJobCoordinator.doOnProcessorChange(
> ZkJobCoordinator.java:197)
>        at org.apache.samza.zk.ZkJobCoordinator$LeaderElectorListenerImpl.
> lambda$onBecomingLeader$0(ZkJobCoordinator.java:318)
>        at org.apache.samza.zk.ScheduleAfterDebounceTime.
> lambda$getScheduleableAction$0(ScheduleAfterDebounceTime.java:134)
>        at java.util.concurrent.Executors$RunnableAdapter.
> call$$$capture(Executors.java:511)
>        at java.util.concurrent.Executors$RunnableAdapter.
> call(Executors.java)
>        at java.util.concurrent.FutureTask.run$$$capture(
> FutureTask.java:266)
>        at java.util.concurrent.FutureTask.run(FutureTask.java)
>        at java.util.concurrent.ScheduledThreadPoolExecutor$
> ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
>        at java.util.concurrent.ScheduledThreadPoolExecutor$
> ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
>        at java.util.concurrent.ThreadPoolExecutor.runWorker(
> ThreadPoolExecutor.java:1142)
>        at java.util.concurrent.ThreadPoolExecutor$Worker.run(
> ThreadPoolExecutor.java:617)
>        at java.lang.Thread.run(Thread.java:745)
> 2018-03-15 22:34:32 logback 77787 [debounce-thread-0] DEBUG 
> o.a.samza.processor.StreamProcessor - Container is not instantiated yet.
> 2018-03-15 22:34:32 logback 77787 [debounce-thread-0] DEBUG 
> org.I0Itec.zkclient.ZkClient - Closing ZkClient...
> 2018-03-15 22:34:32 logback 77789
> [ZkClient-EventThread-15-10.0.127.114:2181]
> INFO  org.I0Itec.zkclient.ZkEventThread - Terminate ZkClient event thread.
>
> And then the application continues on with metric reporters, and other 
> debug logging (not actually running the task though)
>
> Thanks in advance for the guidance, this has been easier than I imagined!
> I’ll report back when I get more of the Dockerization/Kubernetes 
> running and test it a bit more.
> Cheers,
> Thunder
>
>
> From: Jagadish Venkatraman [mailto:jagadish1989@gmail.com]
> Sent: Thursday, March 15, 2018 14:46
> To: Thunder Stumpges <tstumpges@ntent.com>
> Cc: dev@samza.apache.org; tom@recursivedream.com; Yipan@linkedin.com; 
> Yi Pan <nickpan47@gmail.com>
> Subject: Re: Old style "low level" Tasks with alternative deployment
> model(s)
>
> >>  Thanks for the info on the tradeoffs. That makes a lot of sense. I 
> >> am
> on-board with using ZkJobCoordinator, sounds like some good benefits 
> over just the Kafka high-level consumer.
>
> This certainly looks like the simplest alternative.
>
> For your other questions, please find my answers inline.
>
> >> Q1: If I use LocalApplicationRunner, It does not use
> "ProcessJobFactory" (or any StreamJob or *Job classes) correct?
>
> Your understanding is correct. It directly instantiates the 
> StreamProcessor, which in-turn creates and runs the SamzaContainer.
>
> >> Q2: If I use LocalApplicationRunner, I will need to code myself the
> loading and rewriting of the Config that is currently handled by 
> JobRunner, correct?
>
> I don't think you'll need to do this. IIUC, the LocalApplicationRunner 
> should automatically invoke rewriters and do the right thing.
>
> >>  Q3: Do I need to also handle coordinator stream(s) and storing of
> config that is done in JobRunner (I don’t think so as the ?
>
> I don't think this is necessary either. The creation of coordinator 
> stream and persisting configuration happens in the 
> LocalApplicationRunner (more specifically in StreamManager#createStreams).
>
> >> Q4: Where/How do I specify the Container ID for each instance? Is 
> >> there
> a config setting that I can pass, (or pull from an env variable and 
> add to the config) ? I am assuming it is my responsibility to ensure 
> that each instance is started with a unique container ID..?
>
> Nope, If you are using the ZkJobCoordinator, you need not have to 
> worry about assigning IDs for each instance. The framework will 
> automatically take care of generating IDs and reaching consensus by 
> electing a leader. If you are curious please take a look at 
> implementations of the ProcessorIdGenerator interface.
>
> Please let us know should you have further questions!
>
> Best,
> Jagdish
>
> On Thu, Mar 15, 2018 at 11:48 AM, Thunder Stumpges 
> <tstumpges@ntent.com <mailto:tstumpges@ntent.com>> wrote:
>
> Thanks for the info on the tradeoffs. That makes a lot of sense. I am 
> on-board with using ZkJobCoordinator, sounds like some good benefits 
> over just the Kafka high-level consumer.
>
>
>
> To that end, I have made some notes on possible approaches based on 
> the previous thread, and from my look into the code. I’d love to get feedback.
>
>
>
> Approach 1. Configure jobs to use “ProcessJobFactory” and run 
> instances of the job using run-job.sh or using JobRunner directly.
>
> I don’t think this makes sense from what I can see for a few reasons:
>
>   *   JobRunner is concerned with stuff I don't *think* we need:
>
>      *   coordinatorSystemProducer|Consumer,
>      *   writing/reading the configuration to the coordinator streams
>
>   *   ProcessJobFactory hard-codes the ID to “0” so I don’t think that
> will work for multiple instances.
>
>
>
> Approach 2. Configure ZkJobCoordinator, GroupByContainerIds, and 
> invoke
> LocalApplicationRunner.runTask()
>
>
>
>     Q1: If I use LocalApplicationRunner, It does not use 
> "ProcessJobFactory" (or any StreamJob or *Job classes) correct?
>
>     Q2: If I use LocalApplicationRunner, I will need to code myself 
> the loading and rewriting of the Config that is currently handled by 
> JobRunner, correct?
>
>     Q3: Do I need to also handle coordinator stream(s) and storing of 
> config that is done in JobRunner (I don’t think so as the ?
>
>     Q4: Where/How do I specify the Container ID for each instance? Is 
> there a config setting that I can pass, (or pull from an env variable 
> and add to the config) ? I am assuming it is my responsibility to 
> ensure that each instance is started with a unique container ID..?
>
> I am getting started on the above (Approach 2.), and looking closer at 
> the code so I may have my own answers to my questions, but figured I 
> should go ahead and ask now anyway. Thanks!
>
> -Thunder
>
>
> From: Jagadish Venkatraman [mailto:jagadish1989@gmail.com<mailto:
> jagadish1989@gmail.com>]
> Sent: Thursday, March 15, 2018 1:41
> To: dev@samza.apache.org<mailto:dev@samza.apache.org>; Thunder 
> Stumpges < tstumpges@ntent.com<mailto:tstumpges@ntent.com>>;
> tom@recursivedream.com <mailto:tom@recursivedream.com>
> Cc: Yipan@linkedin.com<mailto:Yipan@linkedin.com>; Yi Pan < 
> nickpan47@gmail.com<mailto:nickpan47@gmail.com>>
>
> Subject: Re: Old style "low level" Tasks with alternative deployment
> model(s)
>
> >> You are correct that this is focused on the higher-level API but 
> >> doesn't
> preclude using the lower-level API. I was at the same point you were 
> not long ago, in fact, and had a very productive conversation on the 
> list
>
> Thanks Tom for linking the thread, and I'm glad that you were able to 
> get Kubernetes integration working with Samza.
>
> >> If it is helpful for everyone, once I get the low-level API + 
> >> ZkJobCoordinator + Docker +
> K8s working, I'd be glad to formulate an additional sample for hello-samza.
>
> @Thunder Stumpges:
> We'd be thrilled to receive your contribution. Examples, demos, 
> tutorials etc.
> contribute a great deal to improving the ease of use of Apache Samza. 
> I'm happy to shepherd design discussions/code-reviews in the 
> open-source including answering any questions you may have.
>
>
> >> One thing I'm still curious about, is what are the drawbacks or 
> >> complexities of leveraging the Kafka High-level consumer + 
> >> PassthroughJobCoordinator in a stand-alone setup like this? We do 
> >> have Zookeeper (because of kafka) so I think either would work. The 
> >> Kafka High-level consumer comes with other nice tools for 
> >> monitoring offsets, lag, etc
>
>
> @Thunder Stumpges:
>
> Samza uses a "Job-Coordinator" to assign your input-partitions among 
> the different instances of your application s.t. they don't overlap. A 
> typical way to solve this "partition distribution"
> problem is to have a single instance elected as a "leader" and have 
> the leader assign partitions to the group.
> The ZkJobCoordinator uses Zk primitives to achieve this, while the 
> YarnJC relies on Yarn's guarantee that there will be a 
> singleton-AppMaster to achieve this.
>
> A key difference that separates the PassthroughJC from the Yarn/Zk 
> variants is that it does _not_ attempt to solve the "partition 
> distribution" problem. As a result, there's no leader-election involved.
> Instead, it pushes the problem of "partition distribution" to the 
> underlying consumer.
>
> The PassThroughJc supports these 2 scenarios:
>
> 1. Consumer-managed partition distribution: When using the Kafka 
> high-level consumer (or an AWS KinesisClientLibrary consumer) with 
> Samza, the consumer manages partitions internally.
>
> 2. Static partition distribution: Alternately, partitions can be 
> managed statically using configuration. You can achieve static 
> partition assignment by implementing a custom 
> SystemStreamPartitionGrouper<h 
> ttps://samza.apache.org/learn/documentation/0.8/api/
> javadocs/org/apache/samza/container/grouper/stream/
> SystemStreamPartitionGrouper.html> and TaskNameGrouper<https:// 
> github.com/apache/samza/blob/master/samza-core/src/main/
> java/org/apache/samza/container/grouper/task/TaskNameGrouper.java>.
> Solutions in this category will typically require you to distinguish 
> the various processors in the group by providing an "id" for each.
> Once the "id"s are decided, you can then statically compute 
> assignments using a function (eg: modulo N).
> You can rely on the following mechanisms to provide this id:
>  - Configure each instance differently to have its own id
>  - Obtain the id from the cluster-manager. For instance, Kubernetes 
> will provide each POD an unique id in the range [0,N). AWS ECS should 
> expose similar capabilities via a REST end-point.
>
> >> One thing I'm still curious about, is what are the drawbacks or
> complexities of leveraging the Kafka High-level consumer + 
> PassthroughJobCoordinator in a stand-alone setup like this?
>
> Leveraging the Kafka High-level consumer:
>
> The Kafka high-level consumer is not integrated into Samza just yet.
> Instead, Samza's integration with Kafka uses the low-level consumer 
> because
> i) It allows for greater control in fetching data from individual brokers.
> It is simple and performant in-terms of the threading model to have 
> one-thread pull from each broker.
> ii) It is efficient in memory utilization since it does not do 
> internal-buffering of messages.
> iii) There's no overhead like Kafka-controller heart-beats that are 
> driven by consumer.poll
>
> Since there's no built-in integration, you will have to build a new 
> SystemConsumer if you need to integrate with the Kafka High-level consumer.
> Further, there's more a fair bit of complexity to manage in checkpointing.
>
> >> The Kafka High-level consumer comes with other nice tools for 
> >> monitoring offsets, lag, etc
>
> Samza exposes<https://github.com/apache/samza/blob/master/
> samza-kafka/src/main/scala/org/apache/samza/system/kafka/
> KafkaSystemConsumerMetrics.scala> the below metrics for lag-monitoring:
> - The current log-end offset for each partition
> - The last check-pointed offset for each partition
> - The number of messages behind the highwatermark of the partition
>
> Please let us know if you need help discovering these or integrating 
> these with other systems/tools.
>
>
> Leveraging the Passthrough JobCoordinator:
>
> It's helpful to split this discussion on tradeoffs with PassthroughJC 
> into
> 2 parts:
>
> 1. PassthroughJC + consumer managed partitions:
>
> - In this model, Samza has no control over partition-assignment since 
> it's managed by the consumer. This means that stateful operations like 
> joins that rely on partitions being co-located on the same task will not work.
> Simple stateless operations (eg: map, filter, remote lookups) are fine.
>
> - A key differentiator between Samza and other frameworks is our 
> support for "host 
> affinity<https://samza.apache.org/learn/documentation/0.14/
> yarn/yarn-host-affinity.html>". Samza achieves this by assigning 
> partitions to hosts taking data-locality into account. If the consumer 
> can arbitrarily shuffle partitions, it'd be hard to support this 
> affinity/locality. Often this is a key optimization when dealing with 
> large stateful jobs.
>
> 2. PassthroughJC + static partitions:
>
> - In this model, it is possible to make stateful processing (including 
> host affinity) work by carefully choosing how "id"s are assigned and 
> computed.
>
> Recommendation:
>
> - Owing to the above subtleties, I would recommend that we give the 
> ZkJobCoordinator + the built-in low-level Kafka integration a try.
> - If we hit snags down this path, we can certainly explore the 
> approach with PassthroughJC + static partitions.
> - Using the PassthroughJC + consumer-managed distribution would be 
> least preferable owing to the subtleties I outlined above.
>
> Please let us know should you have more questions.
>
> Best,
> Jagdish
>
> On Wed, Mar 14, 2018 at 9:24 PM, Thunder Stumpges <tstumpges@ntent.com 
> <mailto:tstumpges@ntent.com>> wrote:
> Wow, what great timing, and what a great thread! I definitely have 
> some good starters to go off of here.
>
> If it is helpful for everyone, once I get the low-level API + 
> ZkJobCoordinator + Docker + K8s working, I'd be glad to formulate an 
> additional sample for hello-samza.
>
> One thing I'm still curious about, is what are the drawbacks or 
> complexities of leveraging the Kafka High-level consumer + 
> PassthroughJobCoordinator in a stand-alone setup like this? We do have 
> Zookeeper (because of kafka) so I think either would work. The Kafka 
> High-level consumer comes with other nice tools for monitoring 
> offsets, lag, etc....
>
> Thanks guys!
> -Thunder
>
> -----Original Message-----
> From: Tom Davis [mailto:tom@recursivedream.com<mailto:
> tom@recursivedream.com>]
> Sent: Wednesday, March 14, 2018 17:50
> To: dev@samza.apache.org<mailto:dev@samza.apache.org>
> Subject: Re: Old style "low level" Tasks with alternative deployment
> model(s)
>
> Hey there!
>
> You are correct that this is focused on the higher-level API but 
> doesn't preclude using the lower-level API. I was at the same point 
> you were not long ago, in fact, and had a very productive conversation on the list:
> you should look for "Question about custom StreamJob/Factory" in the 
> list archive for the past couple months.
>
> I'll quote Jagadish Venkatraman from that thread:
>
> > For the section on the low-level API, can you use 
> > LocalApplicationRunner#runTask()? It basically creates a new 
> > StreamProcessor and runs it. Remember to provide task.class and set 
> > it to your implementation of StreamTask or AsyncStreamTask. Please 
> > note that this is an evolving API and hence, subject to change.
>
> I ended up just switching to the high-level API because I don't have 
> any existing Tasks and the Kubernetes story is a little more straight 
> forward there (there's only one container/configuration to deploy).
>
> Best,
>
> Tom
>
> Thunder Stumpges <tstumpges@ntent.com<mailto:tstumpges@ntent.com>> writes:
>
> > Hi all,
> >
> > We are using Samza (0.12.0) in about 2 dozen jobs implementing 
> > several processing pipelines. We have also begun a significant move 
> > of other services within our company to Docker/Kubernetes. Right now 
> > our Hadoop/Yarn cluster has a mix of stream and batch "Map Reduce"
> > jobs
> (many reporting and other batch processing jobs). We would really like 
> to move our stream processing off of Hadoop/Yarn and onto Kubernetes.
> >
> > When I just read about some of the new progress in .13 and .14 I got 
> > really excited! We would love to have our jobs run as simple 
> > libraries in our own JVM, and use the Kafka High-Level-Consumer for 
> > partition
> distribution and such. This would let us "dockerfy" our application 
> and run/scale in kubernetes.
> >
> > However as I read it, this new deployment model is ONLY for the
> > new(er) High Level API, correct? Is there a plan and/or resources 
> > for adapting this back to existing low-level tasks ? How complicated 
> > of a
> task is that? Do I have any other options to make this transition easier?
> >
> > Thanks in advance.
> > Thunder
>
>
>
> --
> Jagadish V,
> Graduate Student,
> Department of Computer Science,
> Stanford University
>
>
>
> --
> Jagadish V,
> Graduate Student,
> Department of Computer Science,
> Stanford University
>
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