├── LICENSE ├── README.md └── custom_elasticsearch.py /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 2, June 1991 3 | 4 | Copyright (C) 1989, 1991 Free Software Foundation, Inc., 5 | 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA 6 | Everyone is permitted to copy and distribute verbatim copies 7 | of this license document, but changing it is not allowed. 8 | 9 | Preamble 10 | 11 | The licenses for most software are designed to take away your 12 | freedom to share and change it. By contrast, the GNU General Public 13 | License is intended to guarantee your freedom to share and change free 14 | software--to make sure the software is free for all its users. This 15 | General Public License applies to most of the Free Software 16 | Foundation's software and to any other program whose authors commit to 17 | using it. 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If this is what you want to do, use the GNU Lesser General 339 | Public License instead of this License. 340 | 341 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # haystack-elasticsearch-raw-query 2 | This python class allows you to use elasticsearch raw queries with django-haystack SearchQuerySet. Most of the code comes from www.stamkracht.com/extending-haystacks-elasticsearch-backend/ 3 | 4 | # Usage 5 | 6 | ```python 7 | import custom_elasticsearch as es 8 | results = es.ConfigurableSearchQuerySet().models(SomeModel) 9 | query = { "bool": { "should": [ { "match": { "text": "milk" } }, { "match": { "text": "yogurt" } } ] } } 10 | results = results.custom_query(query) 11 | ``` 12 | 13 | # Installation 14 | 15 | Just add `custom_elasticsearch.py` to your app's directory and change the `Haystack_Connections` settings in your `settings.py` file as follows where `some_app` is your app's name: 16 | 17 | ```python 18 | HAYSTACK_CONNECTIONS = { 19 | 20 | # this is a custom elastic search engine to extend haystack's elasticsearch 21 | 22 | 'default': { 23 | 'ENGINE': 'some_app.custom_elasticsearch.ConfigurableElasticSearchEngine', 24 | 'PATH': os.path.join(os.path.dirname(__file__), 'elastic_index'), 25 | 'URL': 'http://127.0.0.1:9200/', 26 | 'INDEX_NAME': 'some_app' 27 | } 28 | 29 | } 30 | ``` 31 | -------------------------------------------------------------------------------- /custom_elasticsearch.py: -------------------------------------------------------------------------------- 1 | from haystack.fields import SearchField 2 | from haystack.backends.elasticsearch_backend import ElasticsearchSearchBackend, ElasticsearchSearchQuery 3 | from haystack.backends.elasticsearch_backend import ElasticsearchSearchEngine 4 | from haystack.query import SearchQuerySet 5 | from haystack.constants import DEFAULT_ALIAS, DJANGO_CT 6 | from django.conf import settings 7 | 8 | class TagsField(SearchField): 9 | field_type = "nested" 10 | properties = { 11 | "tag": { 12 | "type": "string", 13 | "index": "not_analyzed", 14 | "omit_norms": True, 15 | "index_options": "docs" 16 | }, 17 | "points": { 18 | "type": "float" 19 | } 20 | } 21 | 22 | 23 | class ConfigurableElasticBackend(ElasticsearchSearchBackend): 24 | 25 | def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None, 26 | fields='', highlight=False, facets=None, 27 | date_facets=None, query_facets=None, 28 | narrow_queries=None, spelling_query=None, 29 | within=None, dwithin=None, distance_point=None, 30 | models=None, limit_to_registered_models=None, 31 | result_class=None,nested=None, custom_query = None): 32 | 33 | out = super(ConfigurableElasticBackend, self).build_search_kwargs(query_string, sort_by, start_offset, end_offset, 34 | fields, highlight, facets, 35 | date_facets, query_facets, 36 | narrow_queries, spelling_query, 37 | within, dwithin, distance_point, 38 | models, limit_to_registered_models, 39 | result_class) 40 | 41 | if nested: 42 | out['query'] = self.nested_query_factory(nested) 43 | 44 | elif custom_query: 45 | out['query'] = custom_query 46 | 47 | return out 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | def nested_query_factory(self, nested): 57 | score_script = "(doc['%s.points'].empty ? 0 : doc['%s.points'].value)" % \ 58 | (nested['nested_query_path'],nested['nested_query_path']) 59 | query = {"nested": { 60 | "path": nested['nested_query_path'], 61 | "score_mode": "total", 62 | "query": { 63 | "function_score": { 64 | "query": { 65 | "terms": { 66 | nested['nested_query_field']: nested['nested_query_terms'], 67 | "minimum_match" : 1 68 | } 69 | }, 70 | "script_score": { 71 | "script" : score_script, 72 | "lang": "mvel" 73 | }, 74 | "boost_mode": "replace" 75 | } 76 | } 77 | } 78 | } 79 | return query 80 | 81 | 82 | def build_schema(self, fields): 83 | content_field_name = '' 84 | mapping = {} 85 | 86 | for field_name, field_class in fields.items(): 87 | field_mapping = { 88 | 'boost': field_class.boost, 89 | 'index': 'analyzed', 90 | 'store': 'yes', 91 | 'type': 'string', 92 | } 93 | 94 | if field_class.document is True: 95 | content_field_name = field_class.index_fieldname 96 | 97 | if field_class.field_type in ['date', 'datetime']: 98 | field_mapping['type'] = 'date' 99 | elif field_class.field_type == 'integer': 100 | field_mapping['type'] = 'long' 101 | elif field_class.field_type == 'float': 102 | field_mapping['type'] = 'float' 103 | elif field_class.field_type == 'boolean': 104 | field_mapping['type'] = 'boolean' 105 | elif field_class.field_type == 'nested': 106 | field_mapping['type'] = 'nested' 107 | try: 108 | field_mapping['properties'] = field_class.properties 109 | except AttributeError: 110 | pass 111 | elif field_class.field_type == 'ngram': 112 | field_mapping['analyzer'] = "ngram_analyzer" 113 | elif field_class.field_type == 'edge_ngram': 114 | field_mapping['analyzer'] = "edgengram_analyzer" 115 | elif field_class.field_type == 'location': 116 | field_mapping['type'] = 'geo_point' 117 | 118 | if field_class.stored is False: 119 | field_mapping['store'] = 'no' 120 | 121 | # Do this last to override `text` fields. 122 | if field_class.indexed is False or hasattr(field_class, 'facet_for'): 123 | field_mapping['index'] = 'not_analyzed' 124 | 125 | if field_mapping['type'] == 'string' and field_class.indexed: 126 | field_mapping["term_vector"] = "with_positions_offsets" 127 | 128 | if not hasattr(field_class, 'facet_for') and not field_class.field_type in('ngram', 'edge_ngram'): 129 | field_mapping["analyzer"] = "snowball" 130 | 131 | mapping[field_class.index_fieldname] = field_mapping 132 | 133 | return (content_field_name, mapping) 134 | 135 | 136 | class ConfigurableSearchQuerySet(SearchQuerySet): 137 | 138 | def custom_query(self, custom_query = None): 139 | """Adds a custom query""" 140 | clone = self._clone() 141 | clone.query.add_custom_query(custom_query) 142 | return clone 143 | 144 | 145 | def nested(self, terms=None, path="tags", field="tag"): 146 | """Adds arguments for nested to the query""" 147 | clone = self._clone() 148 | clone.query.add_nested(terms, path, field) 149 | return clone 150 | 151 | class ConfigurableElasticsearchSearchQuery(ElasticsearchSearchQuery): 152 | def __init__(self, using=DEFAULT_ALIAS): 153 | out = super(ConfigurableElasticsearchSearchQuery, self).__init__(using) 154 | 155 | self.nested = {} 156 | self.custom_query = {} 157 | 158 | def add_custom_query(self, custom_query = None): 159 | """Adds arguments for custom_score to the query""" 160 | self.custom_query = custom_query 161 | 162 | 163 | 164 | def add_nested(self, terms=None, path=None, field=None): 165 | """Adds arguments for nested to the query""" 166 | self.nested = { 167 | 'nested_query_terms': terms, 168 | 'nested_query_path': path, 169 | 'nested_query_field': field 170 | } 171 | 172 | def build_params(self, spelling_query=None, **kwargs): 173 | """ 174 | Add custom_score and/or nested parameters 175 | """ 176 | search_kwargs = super(ConfigurableElasticsearchSearchQuery, self).build_params(spelling_query, **kwargs) 177 | 178 | if self.nested: 179 | search_kwargs['nested'] = self.nested 180 | if self.custom_query: 181 | search_kwargs['custom_query'] = self.custom_query 182 | 183 | return search_kwargs 184 | 185 | def _clone(self, klass=None, using=None): 186 | clone = super(ConfigurableElasticsearchSearchQuery, self)._clone(klass, using) 187 | 188 | clone.nested = self.nested 189 | clone.custom_query = self.custom_query 190 | return clone 191 | 192 | 193 | class ConfigurableElasticSearchEngine(ElasticsearchSearchEngine): 194 | backend = ConfigurableElasticBackend 195 | query = ConfigurableElasticsearchSearchQuery --------------------------------------------------------------------------------