[[multi-query-strings]] === Multiple Query Strings
The simplest multifield query to deal with is the ((("multifield search", "multiple query strings")))one where we can map
search terms to specific fields. If we know that War and Peace is the
title, and Leo Tolstoy is the author, it is easy to write each of these
conditions as a match clause ((("match clause, mapping search terms to specific fields")))((("bool query", "mapping search terms to specific fields in match clause")))and to combine them with a <<bool-query,bool
query>>:
GET /_search { "query": { "bool": { "should": [ { "match": { "title": "War and Peace" }}, { "match": { "author": "Leo Tolstoy" }} ] } } }
// SENSE: 110_Multi_Field_Search/05_Multiple_query_strings.json
The bool query takes a more-matches-is-better approach, so the score from
each match clause will be added together to provide the final _score for
each document. Documents that match both clauses will score higher than
documents that match just one clause.
Of course, you're not restricted to using just match clauses: the bool
query can wrap any other query type, ((("bool query", "nested bool query in")))including other bool queries. We could
add a clause to specify that we prefer to see versions of the book that have
been translated by specific translators:
GET /_search { "query": { "bool": { "should": [ { "match": { "title": "War and Peace" }}, { "match": { "author": "Leo Tolstoy" }}, { "bool": { "should": [ { "match": { "translator": "Constance Garnett" }}, { "match": { "translator": "Louise Maude" }} ] }} ] } } }
// SENSE: 110_Multi_Field_Search/05_Multiple_query_strings.json
Why did we put the translator clauses inside a separate bool query? All four
match queries are should clauses, so why didn't we just put the translator
clauses at the same level as the title and author clauses?
The answer lies in how the score is calculated.((("relevance scores", "calculation in bool queries"))) The bool query runs each
match query, adds their scores together, then multiplies by the number of
matching clauses, and divides by the total number of clauses. Each clause at
the same level has the same weight. In the preceding query, the bool query
containing the translator clauses counts for one-third of the total score. If we had
put the translator clauses at the same level as title and author, they
would have reduced the contribution of the title and author clauses to one-quarter each.
[[prioritising-clauses]] ==== Prioritizing Clauses
It is likely that an even one-third split between clauses is not what we need for the preceding query. ((("multifield search", "multiple query strings", "prioritizing query clauses")))((("bool query", "prioritizing clauses"))) Probably we're more interested in the title and author clauses then we are in the translator clauses. We need to tune the query to make the title and author clauses relatively more important.
The simplest weapon in our tuning arsenal is the boost parameter. To
increase the weight of the title and author fields, give ((("boost parameter", "using to prioritize query clauses")))((("weight", "using boost parameter to prioritize query clauses")))them a boost
value higher than 1:
GET /_search { "query": { "bool": { "should": [ { "match": { <1> "title": { "query": "War and Peace", "boost": 2 }}}, { "match": { <1> "author": { "query": "Leo Tolstoy", "boost": 2 }}}, { "bool": { <2> "should": [ { "match": { "translator": "Constance Garnett" }}, { "match": { "translator": "Louise Maude" }} ] }} ] } } }
// SENSE: 110_Multi_Field_Search/05_Multiple_query_strings.json
<1> The title and author clauses have a boost value of 2.
<2> The nested bool clause has the default boost of 1.
The ``best'' value for the boost parameter is most easily determined by
trial and error: set a `boost` value, run test queries, repeat. A reasonable
range for `boost` lies between `1` and `10`, maybe `15`. Boosts higher than
that have little more impact because scores are
<<boost-normalization,normalized>>.