WARNING: The 2.x versions of Elasticsearch have passed their EOL dates. If you are running a 2.x version, we strongly advise you to upgrade.
This documentation is no longer maintained and may be removed. For the latest information, see the current Elasticsearch documentation.
Manipulating Relevance with Query Structure
editManipulating Relevance with Query Structure
editThe Elasticsearch query DSL is immensely flexible. You can move individual query clauses up and down the query hierarchy to make a clause more or less important. For instance, imagine the following query:
quick OR brown OR red OR fox
We could write this as a bool
query with all terms at the same level:
GET /_search { "query": { "bool": { "should": [ { "term": { "text": "quick" }}, { "term": { "text": "brown" }}, { "term": { "text": "red" }}, { "term": { "text": "fox" }} ] } } }
But this query might score a document that contains quick
, red
, and
brown
the same as another document that contains quick
, red
, and fox
.
Red and brown are synonyms and we probably only need one of them to match.
Perhaps we really want to express the query as follows:
quick OR (brown OR red) OR fox
According to standard Boolean logic, this is exactly the same as the original
query, but as we have already seen in Combining Queries, a bool
query does not concern itself only with whether a document matches, but also with how
well it matches.
A better way to write this query is as follows:
GET /_search { "query": { "bool": { "should": [ { "term": { "text": "quick" }}, { "term": { "text": "fox" }}, { "bool": { "should": [ { "term": { "text": "brown" }}, { "term": { "text": "red" }} ] } } ] } } }
Now, red
and brown
compete with each other at their own level, and quick
,
fox
, and red OR brown
are the top-level competitive terms.
We have already discussed how the match
,
multi_match
, term
,
bool
, and dis_max
queries can be used
to manipulate scoring. In the rest of this chapter, we present
three other scoring-related queries: the boosting
query, the
constant_score
query, and the function_score
query.