Hey all, I have a 3 node Elasticsearch 1.0.1 cluster running on Windows Server 2012 (in Azure). There's about 20 million documents that take up a total of 40GB (including replicas). There's about 400 indexes in total, with some having millions of documents and some having just a few. Each index is set to have 3 shards and 1 replica. The main cluster is running on three 4 core machines with 7GB of ram. The min/max JVM heap size is set to 4GB.
The primary use case for this cluster is faceting/aggregations over the documents. There's almost no full text searching, so everything is pretty much based on exact values (which are stored but not analyzed at index time) When doing some term facets on a few of these indexes (the biggest one contains about 8 million documents) I'm seeing really long response times (> 5 sec). There are potentially thousands of distinct values for the term I'm faceting on, but I would have still expected faster performance. So my goal is to speed up these queries to get the responses sub second if possible. To that end I had some questions: 1) Would switching to Linux give me better performance in general? 2) I could collapse almost all of these 400 indexes in to a single big index and use aliases + filters instead. Would this be advisable? 3) Would mucking with the field data cache yield any better results? If I can add any more data to this discussion please let me know! Thanks! Eric -- 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 elasticsearch+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/eb5fb6bf-be2c-4d5f-b73a-edc1ef5813f1%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
