[jira] [Commented] (TINKERPOP-1585) OLAP dedup over non elements

["Daniel Kuppitz (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/TINKERPOP-1585?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15767360#comment-15767360 ] 

Daniel Kuppitz commented on TINKERPOP-1585:
-------------------------------------------

To have rough estimate of how long it should take, I added 1.725.403 Strings to a Set (459.966 unique values). These are numbers from the actual customer project.

{noformat}
gremlin> clockWithResult(1) { s = [] as Set; for (i = 0; i < 1725403; i++) { s << (i%459966).toString()}; s.size() }
==>1396.075091
==>459966
{noformat}

So it doesn't take much more than 1 second to deduplicate 1.7M Strings. I think we can also ignore network limitations, since we're not talking about lots of data.

> 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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