I'm not sure what you want here-- there is a mechanism to force the planner to run stages sequentially (even if the input to stage 2 does not directly depend directly on the output from stage 1) by using ParallelDoOptions to introduce such a dependency, as I indicated before:
SourceTarget marker = ...; HBase.read() doSomeChangesOnData dummyDoFnToCreateMarker HBase.write() marker.write() HBase.read().parallelDo(DoFn, PType, ParallelDoOptions.builder().sourceTarget(marker).build()); That's less of a hint to the planner and more of a command. Another option would be to set the maximum number of simultaneously running jobs in Crunch to 1 using the crunch.max.running.jobs configuration parameter, which would run everything in the pipeline sequentially, one job at a time. On Wed, Feb 12, 2014 at 9:15 AM, Jinal Shah <[email protected]> wrote: > Can I get some comment on this? > > > On Thu, Feb 6, 2014 at 11:00 AM, Jinal Shah <[email protected]> > wrote: > > > Hi Josh and Micah, > > > > In both the scenerios I can easily do a Pipeline.run() and get going from > > there. But my main question would be why should I do a pipeline.run() in > > between just to make the planner run something in a sequential format > > rather than the way it would have planned otherwise. What I'm getting at > is > > that there should some mechanism that will tell the Planner to do > something > > in a certain way to some extend like you can take example of Apache Hive, > > till 0.7 release Hive use to provide a mechanism called HINT which would > > tell the query planner to run something as indicated in the HINT rather > > than the way it would have been otherwise. I know that you might say it > > might not create optimized plan but at this point the consumer is more > > focused on the way it should be planned rather than the optimization. > > > > May be there might be option already there in Crunch that I might have > not > > explored but just wanted to put my point out there. If there is an > option I > > would love to learn about it. > > > > > > On Thu, Feb 6, 2014 at 10:44 AM, Josh Wills <[email protected]> > wrote: > > > >> Hey Jinal, > >> > >> On scenario 2, the easiest way to do this is to force a run() between > the > >> write and the second read, ala: > >> > >> HBase.read() > >> doSomeChangesOnData > >> HBase.write() > >> Pipeline.run() > >> HBase.read() > >> > >> If that isn't possible for some reason, you'll need to add an output > file > >> to the first phase that can be used to indicate that the HBase.write is > >> complete, and then have the second read depend on that file existing > >> before > >> it can run, which can be done via ParallelDoOptions, e.g., > >> > >> SourceTarget marker = ...; > >> HBase.read() > >> doSomeChangesOnData > >> dummyDoFnToCreateMarker > >> HBase.write() > >> marker.write() > >> HBase.read().parallelDo(DoFn, PType, > >> ParallelDoOptions.builder().sourceTarget(marker).build()); > >> > >> but that's obviously uglier and more complicated. > >> > >> J > >> > >> > >> On Wed, Feb 5, 2014 at 7:14 PM, Jinal Shah <[email protected]> > >> wrote: > >> > >> > Hi Josh, > >> > > >> > Here is a small example of what I am looking for. So here is what I'm > >> doing > >> > > >> > Scenario 1: > >> > > >> > PCollection<Something> s = FunctionDoingSomething(); > >> > pipeline.write(s, path); > >> > doSomeFilteringOn(s); > >> > > >> > I want that when I do some filtering this should be done in the map > >> phase > >> > instead it is doing it in the Reduce phase due to which I have to > >> introduce > >> > a pipeline.run() and now this is what the code looks like > >> > > >> > PCollection<Something> s = FunctionDoingSomething(); > >> > pipeline.write(s, path); > >> > pipeline.run() > >> > doSomeFilteringOn(s); > >> > > >> > Scenerio 2: > >> > > >> > I'm doing an operation on HBase and here is how it looks. > >> > > >> > Hbase.read() > >> > doSomeChangesOnData > >> > HBase.write() > >> > HBase.read() > >> > > >> > Now Crunch at this points considers both the reads as separate and > >> tries to > >> > run it in parallel so now before I even write my changes it reads > those > >> > changes so I have to again put a pipeline.run() in order to break it > >> into 2 > >> > separate flow and execute them in sequence. > >> > > >> > So I'm asking is there any way to send an HINT to the Planner that how > >> it > >> > create the Plan instead of it deciding by itself or someway to have > more > >> > control how to make a planner understand in certain situations. > >> > > >> > Thanks > >> > Jinal > >> > > >> > > >> > On Thu, Jan 30, 2014 at 11:10 AM, Josh Wills <[email protected]> > >> wrote: > >> > > >> > > On Thu, Jan 30, 2014 at 7:09 AM, Jinal Shah < > [email protected]> > >> > > wrote: > >> > > > >> > > > Hi everyone, > >> > > > > >> > > > This is Jinal Shah, I'm new to the group. I had a question about > >> > > Execution > >> > > > Control in Crunch. Is there any way we can force Crunch to do > >> certain > >> > > > operations in parallel or certain operations in sequential ways. > For > >> > > > example, let's say if we want the pipeline to executed a > particular > >> > DoFn > >> > > > function in the Map phase instead of the Reduce phase or > >> vice-versa. Or > >> > > > Execute a particular Flow only after a particular flow is > completed > >> as > >> > > > oppose to running it in parallel. > >> > > > > >> > > > >> > > Forcing a DoFn to operate in a map or reduce phase is tough for the > >> > planner > >> > > to do right now; we sort of rely on the developer to have a mental > >> model > >> > of > >> > > how the jobs will proceed. The place where you usually want to > force a > >> > DoFn > >> > > to execute in the reduce vs. the map phase is when you have > dependent > >> > > groupByKey operations, and you can use cache() or materialize() on > the > >> > > intermediate output that you want to split on, and the planner will > >> > respect > >> > > that. > >> > > > >> > > On the latter question, the thing to look for is > >> > > org.apache.crunch.ParallelDoOptions, which isn't something I've > doc'd > >> in > >> > > the user guide yet (it's on the todo list, I promise.) You can give > a > >> > > parallelDo call an additional argument that specifies one or more > >> > > SourceTargets that have to exist before a particular DoFn is allowed > >> to > >> > > run. In this way, you can force aspects of the pipeline to be > >> sequential > >> > > instead of parallel. We make use of ParallelDoOptions inside of the > >> > > MapsideJoinStrategy code, to ensure that the data set that we'll be > >> > loading > >> > > in-memory actually exists in the file system before we run the code > >> that > >> > > reads it into memory. > >> > > > >> > > > >> > > > > >> > > > Maybe this might be asked before so sorry if it came again. If you > >> guys > >> > > > have further question on the details do let me know > >> > > > > >> > > > > >> > > > Thanks everyone and Have a great day. > >> > > > > >> > > > Thanks > >> > > > Jinal > >> > > > > >> > > > >> > > > >> > > > >> > > -- > >> > > Director of Data Science > >> > > Cloudera <http://www.cloudera.com> > >> > > Twitter: @josh_wills <http://twitter.com/josh_wills> > >> > > > >> > > >> > > > > > -- Director of Data Science Cloudera <http://www.cloudera.com> Twitter: @josh_wills <http://twitter.com/josh_wills>
