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Boosting Query Clauses
editBoosting Query Clauses
editOf course, the bool
query isn’t restricted to combining simple one-word
match
queries. It can combine any other query, including other bool
queries. It is commonly used to fine-tune the relevance _score
for each
document by combining the scores from several distinct queries.
Imagine that we want to search for documents about "full-text search," but we
want to give more weight to documents that also mention "Elasticsearch" or
"Lucene." By more weight, we mean that documents mentioning
"Elasticsearch" or "Lucene" will receive a higher relevance _score
than
those that don’t, which means that they will appear higher in the list of
results.
A simple bool
query allows us to write this fairly complex logic as follows:
GET /_search { "query": { "bool": { "must": { "match": { "content": { "query": "full text search", "operator": "and" } } }, "should": [ { "match": { "content": "Elasticsearch" }}, { "match": { "content": "Lucene" }} ] } } }
The |
|
If the |
The more should
clauses that match, the more relevant the document. So far,
so good.
But what if we want to give more weight to the docs that contain Lucene
and
even more weight to the docs containing Elasticsearch
?
We can control the relative weight of any query clause by specifying a boost
value, which defaults to 1
. A boost
value greater than 1
increases the
relative weight of that clause. So we could rewrite the preceding query as
follows:
GET /_search { "query": { "bool": { "must": { "match": { "content": { "query": "full text search", "operator": "and" } } }, "should": [ { "match": { "content": { "query": "Elasticsearch", "boost": 3 } }}, { "match": { "content": { "query": "Lucene", "boost": 2 } }} ] } } }
These clauses use the default |
|
This clause is the most important, as it has the highest |
|
This clause is more important than the default, but not as important
as the |
The boost
parameter is used to increase the relative weight of a clause
(with a boost
greater than 1
) or decrease the relative weight (with a
boost
between 0
and 1
), but the increase or decrease is not linear. In
other words, a boost
of 2
does not result in double the _score
.
Instead, the new _score
is normalized after the boost is applied. Each
type of query has its own normalization algorithm, and the details are beyond
the scope of this book. Suffice to say that a higher boost
value results in
a higher _score
.
If you are implementing your own scoring model not based on TF/IDF and you
need more control over the boosting process, you can use the
function_score
query to manipulate a document’s
boost without the normalization step.
We present other ways of combining queries in the next chapter, Multifield Search. But first, let’s take a look at the other important feature of queries: text analysis.