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https://issues.apache.org/jira/browse/TINKERPOP-1218?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Marko A. Rodriguez closed TINKERPOP-1218.
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Resolution: Fixed
Assignee: Marko A. Rodriguez
Fix Version/s: 3.1.2-incubating
3.2.0-incubating
This was a simple fix. This is both in tp31/ and master/.
> Usage of toLocalIterator Produces large amount of Spark Jobs
> ------------------------------------------------------------
>
> Key: TINKERPOP-1218
> URL: https://issues.apache.org/jira/browse/TINKERPOP-1218
> Project: TinkerPop
> Issue Type: Improvement
> Components: hadoop
> Affects Versions: 3.1.1-incubating
> Reporter: Russell Alexander Spitzer
> Assignee: Marko A. Rodriguez
> Fix For: 3.2.0-incubating, 3.1.2-incubating
>
>
> https://github.com/apache/incubator-tinkerpop/blob/master/spark-gremlin/src/main/java/org/apache/tinkerpop/gremlin/spark/structure/io/PersistedOutputRDD.java#L72
> Will end up creating a separate Spark Job for every task in the RDD. This
> will overwhelm the UI with un-important information and shouldn't be relevant
> to users attempting diagnostics. Since this RDD is relatively small we should
> be fine switching this line to a `.collect` call which will pull the entire
> RDD down to the driver in 1 Job.
> So as long as the total size of this RDD is on the scale of megabytes we can
> make a readable user interface with
> {code}
> return IteratorUtils.map(memoryRDD.collect().iterator(), tuple -> new
> KeyValue<>(tuple._1(), tuple._2()));
> {code}
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