Re: [infinispan-dev] Infinispan - Hadoop integration

Yes, the M/R v1 by default launches one *new* JVM per task, so during the execution of a certain Job, at a given moment in a node there could be dozens of JVMs running in parallel, that will be destroyed when the task (map or reduce) finishes. It is possible to instruct the map reduce system to reuse the same JVM for several map or reduce tasks: this is interesting when map tasks executes in a matter of seconds and the overhead of creating, warming up and destroying a JVM becomes significant. But even in this case, there will be 'n' JVM running where 'n' is the task capacity of the node. The difference is that they are recycled. In Yarn the behaviour is similar, the YarnChild runs in a separate JVM and it's possible to cause some reuse setting the property "mapreduce.job.ubertask.enable" Apart from all those transient tasks JVMs, there will more long running JVMs in each node which is the TaskTracker (who accepts tasks and send status to the global jobtracker)and If HDFS is used, there will be one extra JVM per node (DataNode) plus one or two Namenode global processes. Hadoop is very fond of JVMs. Cheers, Gustavo On Mon, Mar 17, 2014 at 4:06 PM, Alan Field <afield(a)redhat.com&gt; wrote: For Map/Reduce v1 this is definitely the case: https://hadoop.apache.org/docs/r1.2.1/mapred_tutorial.html#Task+Execution... "The TaskTracker executes the Mapper/ Reducer task as a child process in a separate jvm." I believe this is also the case for Map/Reduce v2, but I haven't found a definitive reference in the docs yet. YARN is architected to split resource management and job scheduling/monitoring into different pieces, but I think task execution is the same as MRv1. Thanks, Alan From: "Emmanuel Bernard" <emmanuel(a)hibernate.org&gt; To: "infinispan -Dev List" <infinispan-dev(a)lists.jboss.org&gt; Sent: Monday, March 17, 2014 11:31:34 AM Subject: Re: [infinispan-dev] Infinispan - Hadoop integration Got it now. That being said, if Alan is correct (one JVM per M/R task run per node), we will need to implement C/S local key and keyset lookup. Emmanuel On 14 Mar 2014, at 12:34, Sanne Grinovero <sanne(a)infinispan.org&gt; wrote: On 14 March 2014 09:06, Emmanuel Bernard <emmanuel(a)hibernate.org&gt; wrote: On 13 mars 2014, at 23:39, Sanne Grinovero <sanne(a)infinispan.org&gt; wrote: On 13 March 2014 22:19, Mircea Markus <mmarkus(a)redhat.com&gt; wrote: On Mar 13, 2014, at 22:17, Sanne Grinovero <sanne(a)infinispan.org&gt; wrote: On 13 March 2014 22:05, Mircea Markus <mmarkus(a)redhat.com&gt; wrote: On Mar 13, 2014, at 20:59, Ales Justin <ales.justin(a)gmail.com&gt; wrote: - also important to notice that we will have both an Hadoop and an Infinispan cluster running in parallel: the user will interact with the former in order to run M/R tasks. Hadoop will use Infinispan (integration achieved through InputFormat and OutputFormat ) in order to get the data to be processed. Would this be 2 JVMs, or you can trick Hadoop to start Infinispan as well -- hence 1JVM? good point, ideally it should be a single VM: reduced serialization cost (in vm access) and simpler architecture. That's if you're not using C/S mode, of course. ? Don't try confusing us again on that :-) I think we agreed that the job would *always* run in strict locality with the datacontainer (i.e. in the same JVM). Sure, an Hadoop client would be connecting from somewhere else but that's unrelated. we did discuss the possibility of running it over hotrod though, do you see a problem with that? No of course not, we discussed that. I just mean I think that needs to be clarified on the list that the Hadoop engine will always run in the same JVM. Clients (be it Hot Rod via new custom commands or Hadoop native clients, or Hadoop clients over Hot Rod) can indeed connect remotely, but it's important to clarify that the processing itself will take advantage of locality in all configurations. In other words, to clarify that the serialization cost you mention for clients is just to transfer the job definition and optionally the final processing result. Not quite. The serialization cost Mircea mentions I think is between the Hadoop vm and the Infinispan vm on a single node. The serialization does not require network traffic but is still shuffling data between two processes basically. We could eliminate this by starting both Hadoop and Infinispan from the same VM but that requires more work than necessary for a prototype. Ok so there was indeed confusion on terminology: I don't agree with that design. From an implementor's effort perspective having to setup an Hot Rod client rather than embedding an Infinispan node is approximately the same work, or slightly more as you have to start both. Also to test it, embedded mode it easier. Hot Rod is not meant to be used on the same node, especially not if you only want to access data in strict locality; for example it wouldn't be able to iterated on all keys of the current server node (and limiting to those keys only). I might be wrong as I'm not too familiar with Hot Rod, but I think it might not even be able to iterate on keys at all; maybe today it can actually via some trick, but the point is this is a conceptual mismatch for it. Where you say this doesn't require nework traffic you need to consider that while it's true this might not be using the physical network wire being localhost, it would still be transferred over a costly network stream, as we don't do off-heap buffer sharing yet. So to clarify, we will have a cluster of nodes where each node contains two JVM, one running an Hadoop process, one running an Infinispan process. The Hadoop process would only read the data from the Infinispan process in the same node during a normal M/R execution. So we discussed two use cases: - engage Infinispan to accelerate an existing Hadoop deployment - engage Hadoop to run an Hadoop job on existing data in Infinispan In neither case I see why I'd run them in separate JVMs: seems less effective and more work to get done, and no benefit unless you're thinking about independent JVM tuning? That might be something to consider, but I doubt tuning independence would ever offset the cost of serialized transfer of each entry. The second use case could be used via Hot Rod too, but that's a different discussion, actually just a nice side effect of Hadoop being language agnostic that we would take advantage of. Sanne _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev