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Match Query
editMatch Query
editmatch queries accept text/numerics/dates, analyzes
them, and constructs a query. For example:
GET /_search
{
"query": {
"match" : {
"message" : "this is a test"
}
}
}
Note, message is the name of a field, you can substitute the name of
any field (including _all) instead.
match
editThe match query is of type boolean. It means that the text
provided is analyzed and the analysis process constructs a boolean query
from the provided text. The operator flag can be set to or or and
to control the boolean clauses (defaults to or). The minimum number of
optional should clauses to match can be set using the
minimum_should_match
parameter.
The analyzer can be set to control which analyzer will perform the
analysis process on the text. It defaults to the field explicit mapping
definition, or the default search analyzer.
The lenient parameter can be set to true to ignore exceptions caused by
data-type mismatches, such as trying to query a numeric field with a text
query string. Defaults to false.
Fuzziness
editfuzziness allows fuzzy matching based on the type of field being queried.
See Fuzziness for allowed settings.
The prefix_length and
max_expansions can be set in this case to control the fuzzy process.
If the fuzzy option is set the query will use top_terms_blended_freqs_${max_expansions}
as its rewrite
method the fuzzy_rewrite parameter allows to control how the query will get
rewritten.
Fuzzy transpositions (ab → ba) are allowed by default but can be disabled
by setting fuzzy_transpositions to false.
Here is an example when providing additional parameters (note the slight
change in structure, message is the field name):
GET /_search
{
"query": {
"match" : {
"message" : {
"query" : "this is a test",
"operator" : "and"
}
}
}
}
Zero terms query
editIf the analyzer used removes all tokens in a query like a stop filter
does, the default behavior is to match no documents at all. In order to
change that the zero_terms_query option can be used, which accepts
none (default) and all which corresponds to a match_all query.
GET /_search
{
"query": {
"match" : {
"message" : {
"query" : "to be or not to be",
"operator" : "and",
"zero_terms_query": "all"
}
}
}
}
Cutoff frequency
editThe match query supports a cutoff_frequency that allows
specifying an absolute or relative document frequency where high
frequency terms are moved into an optional subquery and are only scored
if one of the low frequency (below the cutoff) terms in the case of an
or operator or all of the low frequency terms in the case of an and
operator match.
This query allows handling stopwords dynamically at runtime, is domain
independent and doesn’t require a stopword file. It prevents scoring /
iterating high frequency terms and only takes the terms into account if a
more significant / lower frequency term matches a document. Yet, if all
of the query terms are above the given cutoff_frequency the query is
automatically transformed into a pure conjunction (and) query to
ensure fast execution.
The cutoff_frequency can either be relative to the total number of
documents if in the range [0..1) or absolute if greater or equal to
1.0.
Here is an example showing a query composed of stopwords exclusively:
GET /_search
{
"query": {
"match" : {
"message" : {
"query" : "to be or not to be",
"cutoff_frequency" : 0.001
}
}
}
}
The cutoff_frequency option operates on a per-shard-level. This means
that when trying it out on test indexes with low document numbers you
should follow the advice in Relevance is broken.