[jira] [Closed] (TINKERPOP-1801) OLAP profile() step return incorrect timing

["Marko A. Rodriguez (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/TINKERPOP-1801?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Marko A. Rodriguez closed TINKERPOP-1801.
-----------------------------------------
       Resolution: Fixed
         Assignee: Marko A. Rodriguez
    Fix Version/s: 3.3.1
                   3.2.7

>  OLAP profile() step return incorrect timing
> --------------------------------------------
>
>                 Key: TINKERPOP-1801
>                 URL: https://issues.apache.org/jira/browse/TINKERPOP-1801
>             Project: TinkerPop
>          Issue Type: Bug
>          Components: hadoop
>    Affects Versions: 3.3.0, 3.2.6
>            Reporter: Artem Aliev
>            Assignee: Marko A. Rodriguez
>             Fix For: 3.2.7, 3.3.1
>
>
> Graph ProfileStep calculates time of next()/hasNext() calls, expecting recursion.
> But Message passing/RDD joins is used by GraphComputer.
> So next() does not recursively call next steps, but message is generated. And most of the time is taken by message passing (RDD join). 
> Thus on graph computer the time between ProfileStep should be measured, not inside it.
> The other approach is to get Spark statistics with SparkListener and add spark stages timings into profiler metrics. that will work only for spark but will give better representation of step costs.
> The simple fix is measuring time between OLAP iterations and add it to the profiler step.
> This will not take into account computer setup time, but will be precise enough for long running queries.
> To reproduce:
> tinkerPop 3.2.6 gremlin:
> {code}
> plugin activated: tinkerpop.server
> plugin activated: tinkerpop.utilities
> plugin activated: tinkerpop.spark
> plugin activated: tinkerpop.tinkergraph
> gremlin> graph = GraphFactory.open('conf/hadoop/hadoop-grateful-gryo.properties')
> gremlin> g = graph.traversal().withComputer(SparkGraphComputer)
> ==>graphtraversalsource[hadoopgraph[gryoinputformat->gryooutputformat], sparkgraphcomputer]
> gremlin> g.V().out().out().count().profile()
> ==>Traversal Metrics
> Step                                                               Count  Traversers       Time (ms)    % Dur
> =============================================================================================================
> GraphStep(vertex,[])                                                 808         808           2.025    18.35
> VertexStep(OUT,vertex)                                              8049         562           4.430    40.14
> VertexStep(OUT,edge)                                              327370        7551           4.581    41.50
> CountGlobalStep                                                        1           1           0.001     0.01
>                                             >TOTAL                     -           -          11.038        -
> gremlin> clock(1){g.V().out().out().count().next() }
> ==>3421.92758
> gremlin>
> {code}



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