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https://issues.apache.org/jira/browse/TINKERPOP-1585?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15795276#comment-15795276
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Marko A. Rodriguez commented on TINKERPOP-1585:
-----------------------------------------------
Note that my runtimes are not as egregious as yours. I'm using TinkerPop
3.2.3-SNAPSHOT. (tp32/).
{code}
[0.289296, 1000000]
[832.118614, 570723]
[3041.492602, 1000000]
[3351.8494579999997, 570723]
{code}
This is a 10x difference.
Question: Are your runtimes above with respect to using {{TinkerGraphComputer}}
or {{SparkGraphComputer}}?
> OLAP dedup over non elements
> ----------------------------
>
> Key: TINKERPOP-1585
> URL: https://issues.apache.org/jira/browse/TINKERPOP-1585
> Project: TinkerPop
> Issue Type: Bug
> Components: hadoop, process
> Affects Versions: 3.2.3
> Reporter: Daniel Kuppitz
> Assignee: Marko A. Rodriguez
>
> OLAP {{dedup()}} is highly inefficient when it's fed with non elements.
> In a customer project a query similar tho the following returned a result in
> slightly more than 6 seconds:
> {noformat}
> persistedRDD.
> V().hasLabel("label1","label2").
> inE("edgeLabel1","edgeLabel2").outV().
> id().count()
> {noformat}
> The same query with {{dedup()}} added:
> {noformat}
> persistedRDD.
> V().hasLabel("label1","label2").
> inE("edgeLabel1","edgeLabel2").outV().
> id().dedup().count()
> {noformat}
> ...took more than 120 seconds.
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