10

In MySQL I can do something like:

  SELECT id FROM table WHERE field = 'foo' LIMIT 5

If the table has 10,000 rows, then this query is way way faster than if I left out the LIMIT part.

In ElasticSearch, I've got the following:

 {
    "query":{
       "fuzzy_like_this_field":{
          "body":{
             "like_text":"REALLY LONG (snip) TEXT HERE",
             "max_query_terms":1,
             "min_similarity":0.95,
             "ignore_tf":true
          }
       }
    }
 }

When I run this search, it takes a few seconds, whereas mysql can return results for the same query in far, far less time.

If I pass in the size parameter (set to 1), it successfully only returns 1 result, but the query itself isn't any faster than if I had set the size to unlimited and returned all the results. I suspect the query is being run in its entirety and only 1 result is being returned after the query is done processing. This means the "size" attribute is useless for my purposes.

Is there any way to have my search stop searching as soon as it finds a single record that matches the fuzzy search, rather than processing every record in the index before returning a response? Am I misunderstanding something more fundamental about this?

Thanks in advance.

Jemaclus
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1 Answers1

9

You are correct the query is being ran entirely. Queries by default return data sorted by score, so your query is going to score each document. The docs state that the fuzzy query isn't going to scale well, so might want to consider other queries.

A limit filter might give you similar behavior to what your looking for.

A limit filter limits the number of documents (per shard) to execute on

To replicate mysql field='foo' try using a term filter. You should use filters when you don't care about scoring, they are faster and cache-able.

Andy
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