Kenneth this is great news (I am talking about the addtional services), I was just discussing with JB the other day, about how nice it would be to have this kind of tests, with the right infrastructure, since we are working on new IOs, e.g. to test certain particular behaviors with Kafka or other systems, how do the IO react to failure, etc.
It is nice to know that this can be supported. Any concrete plans of how will to make this work ? Do you intend to deploy such systems via containers or just having them in some test cluster ? As Aljoscha mentions just kafka or yarn both need quite a bit of 'extra' dependencies at deploy time. Thanks again for this idea, Ismael. On Thu, Jul 28, 2016 at 6:48 PM, Aljoscha Krettek <[email protected]> wrote: > For Flink, Yarn is fine and I guess it's the common denominator for all > runners (except DataflowRunner, of course). > > @Kenn IMHO the common deployment is Kafka (running standalone, because it > only works that way), which also requires Zookeeper (if I'm not mistaken) > and YARN, which all runners should be able to run on. > > On Thu, 28 Jul 2016 at 18:36 Kenneth Knowles <[email protected]> > wrote: > > > Presumably we'll eventually also run additional services alongside (like > > Kafka) to have true integration tests for I/O connectors. What is the > > common deployment in this case? > > > > On Jul 28, 2016 06:35, "Amit Sela" <[email protected]> wrote: > > > > > So what would be the preferred resource manager to test Flink on ? > > > > > > On Thu, Jul 28, 2016, 16:34 Aljoscha Krettek <[email protected]> > > wrote: > > > > > > > Flink also has a standalone mode. > > > > > > > > On Thu, 28 Jul 2016 at 13:42 Ismaël Mejía <[email protected]> wrote: > > > > > > > > > Good subject, YARN is the de-facto standard at least from the > point > > of > > > > > view of the Big Data Distributions (Cloudera, Hortonworks, etc) and > > > Cloud > > > > > offers, e.g. AWS EMR, Azure HDInsight and Google Dataproc), and > given > > > > that > > > > > it is supported by both Spark and Flink I think it is valuable to > > test > > > > the > > > > > support for YARN. The question is, should the tests be run on > > > > 'Standalone' > > > > > OR YARN' or maybe we can have tests for 'Standalone AND YARN' ? > > > > > > > > > > Ismael. > > > > > > > > > > > > > > > > > > > > > > > > > On Thu, Jul 28, 2016 at 12:24 PM, Amit Sela <[email protected]> > > > > wrote: > > > > > > > > > > > Following a discussion I had with Kenneth and Dan here > > > > > > <https://github.com/apache/incubator-beam/pull/711>. I want to > > raise > > > > the > > > > > > issue of which resource manager we should use for on going tests > > that > > > > > will > > > > > > run on actual clusters (on top of local/in-mem tests). > > > > > > If we plan to test all runners on all their supported resource > > > > managers, > > > > > > great! But I guess this won't be the case, at least not at the > > > > beginning. > > > > > > > > > > > > Spark can run it's own (Standalone Mode) resource manager, use > YARN > > > or > > > > > use > > > > > > Mesos. According to the latest survey > > > > > > < > > > > > > > > > > > > > > > > > > > > > http://go.databricks.com/hubfs/DataBricks_Surveys_-_Content/Spark-Survey-2015-Infographic.pdf > > > > > > > > > > > > > by > > > > > > Databricks Standalone is in the lead (48%), with YARN tailing it > > > > > > (40%) while Mesos looks like the least favourite. > > > > > > For Spark, I'd vote for Standalone as it is the most popular use > > > case + > > > > > it > > > > > > avoids the additional complexity of maintaining YARN on this > > cluster. > > > > > > Having said that, AFAIK Flink is a "first-class" YARN citizen > > (right > > > ?) > > > > > and > > > > > > I don't know what available resource managers can be used by > other > > > > > runners, > > > > > > so I think runner authors should give their input here. > > > > > > > > > > > > *Summary:* > > > > > > *Spark* - StandaloneMode or YARN (in that order). > > > > > > *Flink * - ? > > > > > > *Others* - ? > > > > > > > > > > > > Thanks, > > > > > > Amit > > > > > > > > > > > > > > > > > > > > >
