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From "Josh Wills (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (CRUNCH-247) Planner should take advantage of to-be-materialized outputs during planning
Date Wed, 07 Aug 2013 03:52:47 GMT

     [ https://issues.apache.org/jira/browse/CRUNCH-247?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Josh Wills resolved CRUNCH-247.
-------------------------------

    Resolution: Fixed

Pushed to master.
                
> Planner should take advantage of to-be-materialized outputs during planning
> ---------------------------------------------------------------------------
>
>                 Key: CRUNCH-247
>                 URL: https://issues.apache.org/jira/browse/CRUNCH-247
>             Project: Crunch
>          Issue Type: Bug
>          Components: Core
>            Reporter: Josh Wills
>            Assignee: Josh Wills
>             Fix For: 0.8.0
>
>         Attachments: CRUNCH-247.patch
>
>
> In the following pipeline, the Crunch planner will rerun the "op1" step in two independent
map-only jobs, instead of running a single job that executes the op1 step followed by a subsequent
job that consumes that output and runs the op2 step:
>      PCollection<String> in = p.read(From.textFile(inputPath));
>      PTable<String, String> op = in.parallelDo("op1", new DoFn<String, Pair<String,
String>>() {
>       @Override
>       public void process(String input, Emitter<Pair<String, String>> emitter)
{
>         if (input.length() > 5) {
>           emitter.emit(Pair.of(input.substring(0, 3), input));
>         }
>       } 
>      }, tableOf(strings(), strings()));
>      
>      SourceTarget src = (SourceTarget)((MaterializableIterable<Pair<String, String>>)
op.materialize()).getSource();
>      
>      op = op.parallelDo("op2", IdentityFn.<Pair<String,String>>getInstance(),
tableOf(strings(), strings()),
>          ParallelDoOptions.builder().sourceTargets(src).build());
>      
>      PCollection<String> output = op.values();
>      output.write(To.textFile(out));
> The planner should be able to take advantage of the materialized output from op1 to not
re-run that step in the op2 job.

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