Massive JSON responses could indeed be a problem. I think you can easily see if CPU, Disk, or Network are the bottleneck using really any monitoring tool. Even dstat --cpu --mem --disk --net will give you an idea. :)
Otis -- Performance Monitoring * Log Analytics * Search Analytics Solr & Elasticsearch Support * http://sematext.com/ On Tuesday, May 27, 2014 6:44:45 AM UTC-4, [email protected] wrote: > > Thank you for your reply. > > Here are some observations from a couple of days testing: > > - Setting up routing manually reduced the aggregation time about 40%! > - ... however, manual routing caused data to distribute unevenly. I assume > we could have taken steps to improve the distribution, but we didn't > investigate any further > - Upgrading from 1.1.0 to 1.2.0 didn't seem to improve speed nor memory > usage, although we didn't do any accurate measurements of RAM usage > - Changing the compression value for percentiles did indeed have an effect > - Increasing number of nodes from 3 to 5 didn't seem to improve performance > > Since adding additional nodes didn't seem to improve the performance, > there seem to be a bottleneck somewhere. The result of the aggregation is > very large (as a JSON-result, it results in about a million lines of text), > so maybe data transfer or constructing the result can be a bottleneck? > -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/ade6258f-18bb-46bd-9d69-502ea64d3db2%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
