Re: ES with JG
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Robert Dale <rob...@...>
First, I'm not sure if an index is being used here. Second, my full table scans with 10k vertices is faster. (I'm also using 0.2.0-SNAPSHOT) So you probably have some other issues going on. Is your Cassandra and ES local or over internet? No index, no cache: gremlin> g.V().has('type',textContains('car')).valueMap().profile() 11:15:01 WARN org.janusgraph.graphdb.transaction.StandardJanusGraphTx - Query requires iterating over all vertices [(type textContains car)]. For better performance, use indexes ==>Traversal Metrics Step Count Traversers Time (ms) % Dur ============================================================================================================= JanusGraphStep([],[type.textContains(car)]) 10000 10000 1640.758 95.02 \_condition=(type textContains car) \_isFitted=false \_query=[] \_orders=[] \_isOrdered=true optimization 3.493 scan 0.000 \_condition=VERTEX \_query=[] \_fullscan=true PropertyMapStep(value) 10000 10000 85.950 4.98 >TOTAL - - 1726.709 - With Index, No Cache: gremlin> g.V().has('type',textContains('car')).valueMap().profile() ==>Traversal Metrics Step Count Traversers Time (ms) % Dur ============================================================================================================= JanusGraphStep([],[type.textContains(car)]) 10000 10000 910.588 35.06 \_condition=(type textContains car) \_isFitted=true \_query=[(type textContains car)]:typeIndex \_index=typeIndex \_orders=[] \_isOrdered=true \_index_impl=search optimization 6.669 backend-query 0.000 \_query=typeIndex:[(type textContains car)]:typeIndex backend-query 0.000 \_query=typeIndex:[(type textContains car)]:typeIndex backend-query 0.000 \_query=typeIndex:[(type textContains car)]:typeIndex backend-query 10000 700.633 \_query=typeIndex:[(type textContains car)]:typeIndex PropertyMapStep(value) 10000 10000 1686.415 64.94 >TOTAL - - 2597.003 - On Friday, September 22, 2017 at 10:26:46 AM UTC-4, Suny wrote:
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