Haystack and ElasticSearch only exact search

Haystack and ElasticSearch only exact search

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partial word search with haystack/elasticsearch

Tag : python , By : yatil
Date : March 29 2020, 07:55 AM
To fix the issue you can do I think there's a bug in haystack in elasticsearch_backend.py which is not using pyelasticsearch properly line 868 looks like:
self.conn.put_mapping('modelresult', current_mapping, index=self.index_name)
self.conn.put_mapping(doc_type='modelresult', mapping=current_mapping, index=self.index_name)

How can I do a fuzzy search using django-haystack and the elasticsearch backend?

Tag : django , By : beebob
Date : March 29 2020, 07:55 AM
wish helps you No need to fork Haystack, you can update that method in your own backend (for more details, see Stretching Haystack's ElasticSearch Backend). The build_search_kwargs method returns a dictionary so you can just modify the original return value.
Disclaimer: this code is just an example of how you could update your own backend, not how to implement fuzzy search.
class FuzzyBackend(ElasticsearchSearchBackend):
    def build_search_kwargs(self, query_string, **kwargs):
        fuzzy = kwargs.pop('fuzzy', False)
        fuzzy_field = kwargs.pop('min_similarity', '')
        search_kwargs = super(FuzzyBackend, self).build_search_kwargs(
                query_string, kwargs)
        if fuzzy:
            search_kwargs = {'fuzzy': {fuzzy_field: query_string}}
        return search_kwargs

Search for multiple words elasticsearch haystack

Tag : elasticsearch , By : chudq7
Date : March 29 2020, 07:55 AM
this one helps. I fell into this issue during this month.
In order to perform the correct query you'll need override some haystack objects. I found this article very helpful Extending Haystack’s Elasticsearch backend. Quite complicated at the beginning, but once understand how it works... it works :-)
# -*- coding: utf-8 -*-
from __future__ import absolute_import

from django.conf import settings

from haystack.backends.elasticsearch_backend import (
    ElasticsearchSearchBackend, ElasticsearchSearchEngine, ElasticsearchSearchQuery)
from haystack.query import SearchQuerySet

class ElasticsearchEngineBackendCustom(ElasticsearchSearchBackend):
    DEFAULT_ANALYZER = "snowball"

    def __init__(self, connection_alias, **connection_options):
        super(ElasticsearchEngineBackendCustom, self).__init__(connection_alias, **connection_options)

        user_settings = getattr(settings, 'ELASTICSEARCH_INDEX_SETTINGS', {})
        if user_settings:
            setattr(self, 'DEFAULT_SETTINGS', user_settings)

        user_analyzer = getattr(settings, 'ELASTICSEARCH_DEFAULT_ANALYZER', '')
        if user_analyzer:
            setattr(self, 'DEFAULT_ANALYZER', user_analyzer)

    def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None,
                            fields='', highlight=False, facets=None,
                            date_facets=None, query_facets=None,
                            narrow_queries=None, spelling_query=None,
                            within=None, dwithin=None, distance_point=None,
                            models=None, limit_to_registered_models=None,
                            result_class=None, multi_match=None):

        out = super(ElasticsearchEngineBackendCustom, self).build_search_kwargs(query_string, sort_by, start_offset,
                                                                                fields, highlight, facets,
                                                                                date_facets, query_facets,
                                                                                narrow_queries, spelling_query,
                                                                                within, dwithin, distance_point,
                                                                                models, limit_to_registered_models,

        if multi_match:
             out['query'] = {
                'multi_match': {
                    'query': multi_match['query'],
                    'fields': multi_match['fields'],
                    'tie_breaker': multi_match['tie_breaker'],
                    'minimum_should_match': multi_match['minimum_should_match'],

        return out

    def build_schema(self, fields):
        content_field_name, mapping = super(ElasticsearchEngineBackendCustom, self).build_schema(fields)

        for field_name, field_class in fields.items():
            field_mapping = mapping[field_class.index_fieldname]

            if field_mapping['type'] == 'string' and field_class.indexed:
                if not hasattr(field_class, 'facet_for') or field_class.field_type in ('ngram', 'edge_ngram'):
                    field_mapping['analyzer'] = getattr(field_class, 'analyzer', self.DEFAULT_ANALYZER)
            mapping.update({field_class.index_fieldname: field_mapping})

        return content_field_name, mapping

    def multi_match_run(self, query, fields, minimum_should_match, tie_breaker):
        from elasticsearch_dsl import Search
        from elasticsearch_dsl.query import MultiMatch

        raw = Search().using(self.conn).query(
            MultiMatch(query=u'{}'.format(query), fields=fields, minimum_should_match=minimum_should_match, tie_breaker=tie_breaker)

        return self._process_results(raw)

class ElasticsearchSearchQueryCustom(ElasticsearchSearchQuery):
    def multi_match(self, query, fields, minimum_should_match, tie_breaker):
        results = self.backend.multi_match_run(query, fields, minimum_should_match, tie_breaker)
        self._results = results.get('results', [])
        self._hit_count = results.get('hits', 0)

    def add_multi_match_query(self, query, fields, minimum_should_match, tie_breaker):
        self.multi_match_query = {
            'query': query,
            'fields': fields,
            'minimum_should_match': minimum_should_match,
            'tie_breaker': tie_breaker

    def build_params(self, spelling_query=None, **kwargs):
        search_kwargs = super(ElasticsearchSearchQueryCustom, self).build_params(spelling_query, **kwargs)
        if self.multi_match_query:
            search_kwargs['multi_match'] = self.multi_match_query

        return search_kwargs

class ElasticsearchSearchQuerySetCustom(SearchQuerySet):
    def multi_match(self, query, fields, minimum_should_match="35%", tie_breaker=0.3):
        clone = self._clone()
        clone.query.add_multi_match_query(query, fields, minimum_should_match, tie_breaker)
        clone.query.multi_match(query, fields, minimum_should_match, tie_breaker)
        return clone

class ElasticsearchEngineCustom(ElasticsearchSearchEngine):
    backend = ElasticsearchEngineBackendCustom
    query = ElasticsearchSearchQueryCustom
    "settings": {[...]}
# -*- coding: utf-8 -*-
from __future__ import absolute_import

from haystack.forms import SearchForm

from .backend import ElasticsearchSearchQuerySetCustom

class SearchFormCustom(SearchForm):
    def search(self):
        query = self.searchqueryset.query.clean(self.cleaned_data.get('q'))
        if not self.is_valid() or not query:
            return self.no_query_found()

        sqs = ElasticsearchSearchQuerySetCustom().multi_match(query, ['title^8', 'text^0.5'])

        return sqs
urlpatterns = patterns(
    url('^$', search_view_factory(form_class=SearchFormCustom), name='haystack-search'),

Using django-haystack +Elasticsearch how can I search subsets of a word?

Tag : python , By : smbrant
Date : March 29 2020, 07:55 AM
I wish did fix the issue. If you want results like "xyzapplexyz", then you would need to use ngram analyzer instead of EdgeNGram or you could use both depending on your requirements. EdgeNGram generates tokens only from the beginning.
with NGram apple will be one of the generated tokens for term xyzapplexyz assuming max_gram >=5 and you will get expected results, also search_analyzer needs to be different or you will get weird results.

Highlight exact phrase with haystack/elasticsearch in Django

Tag : python , By : algoRhythm99
Date : March 29 2020, 07:55 AM
it fixes the issue You can build your own highlighter class as documentation states if default highlighter implementation doesn't work for you.
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