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{
""match"" : {
""message"" : ""this is a test""
}
}
Note, message is the name of a field, you can subsitute the name of any field (including _all) instead.
'''
instance = cls(match={field: {'query': query}})
if operator is not None:
instance['match'][field]['operator'] = operator
return instance"
761,"def bool(cls, must=None, should=None, must_not=None, minimum_number_should_match=None, boost=None):
'''
http://www.elasticsearch.org/guide/reference/query-dsl/bool-query.html
A query that matches documents matching boolean combinations of other queris. The bool query maps to Lucene BooleanQuery. It is built using one of more boolean clauses, each clause with a typed occurrence. The occurrence types are:
'must' - The clause(query) must appear in matching documents.
'should' - The clause(query) should appear in the matching document. A boolean query with no 'must' clauses, one or more 'should' clauses must match a document. The minimum number of 'should' clauses to match can be set using 'minimum_number_should_match' parameter.
'must_not' - The clause(query) must not appear in the matching documents. Note that it is not possible to search on documents that only consists of a 'must_not' clause(s).
'minimum_number_should_match' - Minimum number of documents that should match
'boost' - boost value
> term = ElasticQuery()
> term.term(user='kimchy')
> query = ElasticQuery()
> query.bool(should=term)
> query.query()
{ 'bool' : { 'should' : { 'term' : {'user':'kimchy'}}}}
'''
instance = cls(bool={})
if must is not None:
instance['bool']['must'] = must
if should is not None:
instance['bool']['should'] = should
if must_not is not None:
instance['bool']['must_not'] = must_not
if minimum_number_should_match is not None:
instance['bool']['minimum_number_should_match'] = minimum_number_should_match
if boost is not None:
instance['bool']['boost'] = boost
return instance"
762,"def fuzzy(cls, field, value, boost=None, min_similarity=None, prefix_length=None):
'''
http://www.elasticsearch.org/guide/reference/query-dsl/fuzzy-query.html
A fuzzy based query that uses similarity based on Levenshtein (edit distance) algorithm.
'''
instance = cls(fuzzy={field: {'value': value}})
if boost is not None:
instance['fuzzy'][field]['boost'] = boost
if min_similarity is not None:
instance['fuzzy'][field]['min_similarity'] = min_similarity
if prefix_length is not None:
instance['fuzzy'][field]['prefix_length'] = prefix_length
return instance"
763,"def fuzzy_like_this(cls, like_text, fields=None, ignore_tf=None, max_query_terms=None, min_similarity=None, prefix_length=None, boost=None, analyzer=None):
'''
http://www.elasticsearch.org/guide/reference/query-dsl/flt-query.html
Fuzzy like this query find documents that are ""like"" provided text by running it against one or more fields.
> query = ElasticQuery().fuzzy_like_this('text like this one', fields=['name.first', 'name.last'], max_query_terms=12)
> query
{'fuzze_like_this': {'boost': 1.0,
'fields': ['name.first', 'name.last'],
'ifgnore_tf': False,
'like_text': 'text like this one',
'max_query_terms': 12,
'min_similarity': 0.5,
'prefix_length': 0}}
'''
instance = cls(fuzzy_like_this={'like_text': like_text})
if fields is not None:
instance['fuzzy_like_this']['fields'] = fields
if ignore_tf is not None:
instance['fuzzy_like_this']['ignore_tf'] = ignore_tf
if max_query_terms is not None:
instance['fuzzy_like_this']['max_query_terms'] = max_query_terms
if min_similarity is not None:
instance['fuzzy_like_this']['min_similarity'] = min_similarity
if prefix_length is not None:
instance['fuzzy_like_this']['prefix_length'] = prefix_length
if boost is not None:
instance['fuzzy_like_this']['boost'] = boost
if analyzer is not None:
instance['fuzzy_like_this']['analyzer'] = analyzer
return instance"
764,"def has_child(cls, child_type, query):
'''
http://www.elasticsearch.org/guide/reference/query-dsl/has-child-query.html
The has_child query accepts a query and the child type to run against, and results in parent documents that have child docs matching the query.
> child_query = ElasticQuery().term(tag='something')
> query = ElasticQuery().has_Child('blog_tag', child_query)
'''
instance = cls(has_child={'type': child_type, 'query': query})