Leading wildcards are really expensive. Maybe you can try creating a copy
of your "content" field that reverses the tokens using reverse token filter
[1]. By doing this you turn those expensive leading wildcards into
trailing wildcards which should give you better performance. I think your
query would look something like this:
{
"query": {
"constant_score": {
"query": {
"bool": {
"should": [
{"wildcard": {"content": "Children*Next*"}},
{"wildcard": {"content_rev": "txeN*nerdlihC*"}}
]
}
}
}
}
}
Note that you will need to reverse your query string as the wildcard query
is not analyzed.
[1]
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/analysis-reverse-tokenfilter.html#analysis-reverse-tokenfilter
Thanks,
Matt Weber
On Thu, May 22, 2014 at 11:09 AM, Erik Rose <[email protected]> wrote:
> Martijn took a swing at it just now. He eliminated any scoring-based
> slowdown, like so (constant_score_filter)…
>
> curl -s -XGET 'http://127.0.0.1:9200/dxr_test/line/_search?pretty' -d
> '{
> "query": {
> "filtered": {
> "query": {
> "match_all": {}
> },
> "filter": {
> "and": [
> {
> "query": {
> "match_phrase": {
> "content_trg": "Children"
> }
> }
> },
> {
> "query": {
> "match_phrase": {
> "content_trg": "Next"
> }
> }
> },
> {
> "query": {
> "wildcard": {
> "content": {
> "wildcard": "*Children*Next*",
> "rewrite": "constant_score_filter"
> }
> }
> }
> }
> ]
> }
> }
> }
> }'
>
> …but it didn't make any difference. Somehow, the `and` pipeline isn't
> behaving as we expect. Since ES can't provide any more detailed timing
> ouput, I guess the next step is to go look at the source code for the `and`
> filter and the wildcard query and see what's what.
>
> I think we'd both be fascinated to know what's going on, if anyone has
> anything to add.
>
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Thanks,
Matt Weber
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