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From Ben Juhn <benjij...@gmail.com>
Subject Re: Processing many map only collections in single pipeline with spark
Date Sat, 16 Jul 2016 20:29:11 GMT
Hey David,

I have 100 active executors, each job typically only uses a few.  It’s running on yarn.

Thanks,
Ben

> On Jul 16, 2016, at 12:53 PM, David Ortiz <dpo5003@gmail.com> wrote:
> 
> What are the cluster resources available vs what a single map uses?
> 
> 
> On Sat, Jul 16, 2016, 3:04 PM Ben Juhn <benjijuhn@gmail.com <mailto:benjijuhn@gmail.com>>
wrote:
> I enabled FAIR scheduling hoping that would help but only one job is showing up a time.
> 
> Thanks,
> Ben
> 
>> On Jul 15, 2016, at 8:17 PM, Ben Juhn <benjijuhn@gmail.com <mailto:benjijuhn@gmail.com>>
wrote:
>> 
>> Each input is of a different format, and the DoFn implementation handles them depending
on instantiation parameters.
>> 
>> Thanks,
>> Ben
>> 
>>> On Jul 15, 2016, at 7:09 PM, Stephen Durfey <sjdurfey@gmail.com <mailto:sjdurfey@gmail.com>>
wrote:
>>> 
>>> Instead of using readTextFile on the pipeline, try using the read method and
use the TextFileSource, which can accept in a collection of paths. 
>>> 
>>> https://github.com/apache/crunch/blob/master/crunch-core/src/main/java/org/apache/crunch/io/text/TextFileSource.java
<https://github.com/apache/crunch/blob/master/crunch-core/src/main/java/org/apache/crunch/io/text/TextFileSource.java>
>>> 
>>> 
>>> 
>>> 
>>> On Fri, Jul 15, 2016 at 8:53 PM -0500, "Ben Juhn" <benjijuhn@gmail.com <mailto:benjijuhn@gmail.com>>
wrote:
>>> 
>>> Hello,
>>> 
>>> I have a job configured the following way:
>>> for (String path : paths) {
>>>     PCollection<String> col = pipeline.readTextFile(path);
>>>     col.parallelDo(new MyDoFn(path), Writables.strings()).write(To.textFile(“out/“
+ path), Target.WriteMode.APPEND);
>>> }
>>> pipeline.done();
>>> It results in one spark job for each path, and the jobs run in sequence even
though there are no dependencies.  Is it possible to have the jobs run in parallel?
>>> Thanks,
>>> Ben
>>> 
>> 
> 


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