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Preprocess ES terms for better literal matching
This commit adds a new .exact subfield to display_name, which holds a barely-filtered version of the original title we can do "literal" matching against. This is not real substring matching, but quoting terms now actually does something! Implements a simple preprocessor for the search terms to extract quoted parts from the search terms, optionally prefixed with - to negate them. The preprocessor will create a query that'll join all three query-types: the simple_query_string, must-phrases and must-not-phrases.
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@ -23,6 +23,11 @@ settings:
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- my_ngram
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- word_delimit
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- trim_zero
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# For exact matching - simple lowercase + whitespace delimiter
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exact_analyzer:
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tokenizer: whitespace
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filter:
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- lowercase
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# For matching full words longer than the ngram limit (15 chars)
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my_fullword_index_analyzer:
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type: custom
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@ -91,6 +96,10 @@ mappings:
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fullword:
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type: text
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analyzer: my_fullword_index_analyzer
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# Stored for exact phrase matching
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exact:
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type: text
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analyzer: exact_analyzer
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created_time:
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type: date
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# Only in the ES index for generating magnet links
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@ -69,6 +69,79 @@ def _generate_query_string(term, category, filter, user):
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return params
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# For preprocessing ES search terms in _parse_es_search_terms
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QUOTED_LITERAL_REGEX = re.compile(r'(?i)(-)?"(.*?)"')
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def _es_name_exact_phrase(literal):
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''' Returns a Query for a phrase match on the display_name for a given literal '''
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return Q({
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'match_phrase': {
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'display_name.exact': {
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'query': literal,
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'analyzer': 'exact_analyzer'
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}
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}
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})
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def _parse_es_search_terms(search, search_terms):
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''' Parse search terms into a query with properly handled literal phrases
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(the simple_query_string is not so great with exact results).
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For example:
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foo bar "hello world" -"exclude this"
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will become a must simple_query_string for "foo bar", a must phrase_match for
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"hello world" and a must_not for "exclude this".
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Returns the search with the generated bool-query added to it. '''
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# Literal must and must-not sets
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must_set = set()
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must_not_set = set()
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def literal_matcher(match):
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negated = bool(match.group(1))
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literal = match.group(2)
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if negated:
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must_not_set.add(literal)
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else:
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must_set.add(literal)
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# Remove the parsed literal from search terms
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return ''
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# Remove quoted parts (optionally prepended with -) and store them in the sets
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parsed_search_terms = QUOTED_LITERAL_REGEX.sub(literal_matcher, search_terms).strip()
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# Create phrase matches (if any)
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must_queries = [_es_name_exact_phrase(lit) for lit in must_set]
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must_not_queries = [_es_name_exact_phrase(lit) for lit in must_not_set]
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if parsed_search_terms:
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# Normal text search without the quoted parts
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must_queries.append(
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Q(
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'simple_query_string',
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# Query both fields, latter for words with >15 chars
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fields=['display_name', 'display_name.fullword'],
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analyzer='my_search_analyzer',
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default_operator="AND",
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query=parsed_search_terms
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)
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)
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if must_queries or must_not_queries:
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# Create a combined Query with the positive and negative matches
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combined_search_query = Q(
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'bool',
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must=must_queries,
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must_not=must_not_queries
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)
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search = search.query(combined_search_query)
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return search
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def search_elastic(term='', user=None, sort='id', order='desc',
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category='0_0', quality_filter='0', page=1,
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rss=False, admin=False, logged_in_user=None,
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@ -165,12 +238,8 @@ def search_elastic(term='', user=None, sort='id', order='desc',
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# Apply search term
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if term:
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s = s.query('simple_query_string',
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# Query both fields, latter for words with >15 chars
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fields=['display_name', 'display_name.fullword'],
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analyzer='my_search_analyzer',
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default_operator="AND",
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query=term)
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# Do some preprocessing on the search terms for literal "" matching
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s = _parse_es_search_terms(s, term)
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# User view (/user/username)
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if user:
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