I've installed ES on 2 nodes, configured them to run in the same cluster but got no gain in performance (on my test cases I've actually got an average 6% increase in search duration).
I used queries that range from 10ms to 3.5s on average.
The slow queries run aggregations and are from what I see cpu bound.
I've checked everything with Marvel and the distribution of the data nodes in the cluster seem fine ( tried 1 or 0 replicas ).
I'm running ES 2.3.1 on ubuntu 14.04.
What are the possible pitfalls when running a cluster? Is this to be expected ?
Mapping
{
"locations" : {
"mappings" : {
"doc_type_1" : {
"properties" : {
"coordsField" : {
"type" : "geo_point",
"lat_lon" : true
},
"field8" : {
"properties" : {
"prop1" : {
"type" : "string",
"index" : "not_analyzed"
},
"prop2" : {
"type" : "date",
"format" : "yyyy-MM-dd"
},
"prop3" : {
"type" : "boolean"
},
"prop4" : {
"type" : "string"
},
"prop5" : {
"type" : "date",
"format" : "yyyy-MM-dd"
},
"prop6" : {
"type" : "string"
}
}
},
"field7" : {
"properties" : {
"prop1" : {
"type" : "string",
"index" : "not_analyzed"
},
"prop2" : {
"type" : "boolean"
},
"prop3" : {
"type" : "string"
},
"prop4" : {
"type" : "string"
}
}
},
"field6" : {
"type" : "string",
"index" : "not_analyzed"
},
"field5" : {
"properties" : {
"market" : {
"type" : "string"
},
"niche_market" : {
"type" : "string"
},
"sub_market" : {
"type" : "string"
}
}
},
"field4" : {
"type" : "boolean"
},
"field3" : {
"properties" : {
"prop1" : {
"type" : "string"
}
}
},
"field2" : {
"type" : "boolean"
},
"field1" : {
"properties" : {
"prop_1" : {
"properties" : {
"prop_1_1" : {
"properties" : {
"prop_1_1_1" : {
"type" : "double"
}
}
},
"prop_1_2" : {
"properties" : {
"prop_1_2_1" : {
"type" : "string"
},
"prop_1_2_2" : {
"type" : "string"
}
}
}
}
}
}
},
// ... 1000 more lines of mappings
}
}
}
}
}
Node stats
Memory: 2GB / 5GB
Documents: 22,996,755
Data: 13GB
Version: 2.3.1
Index settings
8 shards + replica
Documents: 18.8m
Data: 11.5GB