Too many shards may result in querying performance.
daveey daveey@gmail.com编写：
I just upgraded to ES 1.0.1 from ES 0.9.2 and am seeing huge performance problems.
I traced them to what I think is the post_filter.
Here is the query that we used to run against ES 0.9.2
{
filter": {"and": [
{ "terms": { "index_ids": [ 2134616789944 ] } }, { "or": [ { "term": { "trashed_at": 0 } }, { "not": { "exists": { "field": "trashed_at" } } } ] }]
}
}
This used to take the 0.9 cluster about 150ms to execute
The same query takes about 2.5s for the 1.0 cluster.
I rewrote it to conform to my understanding of the changes in 1.0, using a filtered query, however, that didn't help.
I then tried to figure out which parts were slow. I now have the following query
{
"query": {"filtered": {
"query": { "match_all": {} }, "filter": { "terms": { "index_ids": [ 2134616789944 ]} }}
},
"post_filter": {
"or": [
{"term": {"trashed_at": 0}}, {"not": {"exists": {"field": "trashed_at"}}} ]}}
It takes 2.5 s and returns 34 hits. However, removing the "post_filter" clause:
{
"query": {"filtered": {
"query": { "match_all": {} }, "filter": { "terms": { "index_ids": [ 2134616789944 ] } }}
}
}
Makes it take 50ms and return 34 results.
My conclusion is that it's taking 2.5 seconds to filter 34 results, and that's confusing.
The cluster uses 3 machines, 50 shards, 2 replicas per shard. This means that each machine has the entire copy of the index. We use the ?routing= parameter, and are always hitting a single shard for the query.
Help?
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