Can you share your queries and a query plan?

Also do you have constraints for the merge properties?

Are any of the nodes you insert or connect to heavily contended?

Michael 

Von meinem iPhone gesendet

> Am 19.04.2016 um 15:23 schrieb [email protected]:
> 
> We're loading 20 million abstracts into Neo4J.  The rate has been about 2.5 
> million abstracts per week.  For comparison, we can load all 20 million 
> abstracts into Solr Cloud in less than 24 hours.  The abstracts average about 
> 400-500 words each.  For each abstract, we have 5 additional entity nodes 
> with a relationship between the abstract and these entities.   We're looking 
> for any advice on speeding up the load times for Neo4J.
> 
> In our attempts to get better performance when ingesting the abstracts, we 
> have tried combinations of py2neo version 2 and 3, and Neo4J version 2 and 3 
> Enterprise.  Our platform is a 2 processor 12 core Linux server with 32GB of 
> memory.  We use the default Neo4J configuration.  We prefer merge() to ensure 
> only one node per unique article ID but have tried create().  We utilize 
> batches of 1000 articles.  We minimize round trips to the server with 
> transactions, first the entities and then the relationships.  No find() or 
> find_one() calls are necessary.  The script itself runs quickly and then 
> lingers during the commit suggesting the slowdown is coming from the Neo4J 
> server.  During our trials, we discovered and reported that py2neo 3 hangs 
> indefinitely 99% of the time for merge() with the Bolt transaction.  It also 
> hangs for the HTTP transactions, but its rare.
> 
> Once we get a reasonable single-threaded ingestion rate, we can consider 
> running the load in parallel but since Neo4J is single threaded when updating 
> (correct?), we're not sure that will help much.
> 
> Eventually we will be loading from a variety of sources in parallel so we 
> must avoid solutions that wipe the Neo4J database first.
> 
> Has anyone else experience such slow load times?  Is there some best 
> practices we've overloaded (other than writing directly in Java) that might 
> help increase load performance?
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