Full-Text Search Internals
A presentation at DataOps in in Barcelona, Spain by Philipp Krenn
Who is using databases?
Who is using search?
Developer
Store
Apache Lucene Elasticsearch
https://cloud.elastic.co
—version: ‘2’ services: elasticsearch: image: docker.elastic.co/elasticsearch/elasticsearch:$ELASTIC_VERSION environment: - bootstrap.memory_lock=true - “ES_JAVA_OPTS=-Xms512m -Xmx512m” - discovery.type=single-node ulimits: memlock: soft: -1 hard: -1 mem_limit: 1g volumes: - esdata1:/usr/share/elasticsearch/data ports: - 9200:9200 kibana: image: docker.elastic.co/kibana/kibana:$ELASTIC_VERSION links: - elasticsearch ports: - 5601:5601 volumes: esdata1: driver: local
Example These are <em>not</em> the droids you are looking for.
html_strip Char Filter These are not the droids you are looking for.
standard Tokenizer These are not the droids you looking for are
lowercase Token Filter these are not the droids looking for you are
stop Token Filter droids you looking
snowball Token Filter droid you look
Analyze
GET /_analyze { “analyzer”: “english”, “text”: “These are not the droids you are looking for.” }
{ } “tokens”: [ { “token”: “droid”, “start_offset”: 18, “end_offset”: 24, “type”: “<ALPHANUM>”, “position”: 4 }, { “token”: “you”, “start_offset”: 25, “end_offset”: 28, “type”: “<ALPHANUM>”, “position”: 5 }, … ]
GET /_analyze { “char_filter”: [ “html_strip” ], “tokenizer”: “standard”, “filter”: [ “lowercase”, “stop”, “snowball” ], “text”: “These are <em>not</em> the droids you are looking for.” }
{ } “tokens”: [ { “token”: “droid”, “start_offset”: 27, “end_offset”: 33, “type”: “<ALPHANUM>”, “position”: 4 }, { “token”: “you”, “start_offset”: 34, “end_offset”: 37, “type”: “<ALPHANUM>”, “position”: 5 }, … ]
Stop Words a an and are as at be but by for if in into is it no not of on or such that the their then there these they this to was will with https://github.com/apache/lucene-solr/blob/master/lucene/ core/src/java/org/apache/lucene/analysis/standard/ StandardAnalyzer.java#L44-L50
Always Use Stop Words?
To be, or not to be.
Languages Arabic, Armenian, Basque, Brazilian, Bulgarian, Catalan, CJK, Czech, Danish, Dutch, English, Finnish, French, Galician, German, Greek, Hindi, Hungarian, Indonesian, Irish, Italian, Latvian, Lithuanian, Norwegian, Persian, Portuguese, Romanian, Russian, Sorani, Spanish, Swedish, Turkish, Thai
More Language Plugins Core: ICU (Asian languages), Kuromoji (advanced Japanese), Phonetic, SmartCN, Stempel (better Polish stemming), Ukrainian (stemming) Community: Hebrew, Vietnamese, Network Address Analysis, String2Integer,…
Language Rules English: Philipp’s → philipp French: l’église → eglis German: äußerst → ausserst
Spanish Éstos no son los androides que estáis buscando.
Spanish est android buscand
Spanish with the English Analyzer
Another Example Obi-Wan never told you what happened to your father.
Another Example obi wan never told you what happen your father
Another Example <b>No</b>. I am your father.
Another Example i am your father
Inverted Index am droid father happen i look never obi told wan what you your ID 1 0 1[4] 0 0 0 1[7] 0 0 0 0 0 1[5] 0 ID 2 0 0 1[9] 1[6] 0 0 1[2] 1[0] 1[3] 1[1] 1[5] 1[4] 1[8] ID 3 1[2] 0 1[4] 0 1[1] 0 0 0 0 0 0 0 1[3]
To / The Index
PUT /starwars { “settings”: { “analysis”: { “filter”: { “my_synonym_filter”: { “type”: “synonym”, “synonyms”: [ “father,dad”, “droid => droid,machine” ] } },
}, } “analyzer”: { “my_analyzer”: { “char_filter”: [ “html_strip” ], “tokenizer”: “standard”, “filter”: [ “lowercase”, “stop”, “snowball”, “my_synonym_filter” ] } }
} “mappings”: { “properties”: { “quote”: { “type”: “text”, “analyzer”: “my_analyzer” } } }
PUT /starwars/_doc/1 { “quote”: “These are <em>not</em> the droids you are looking for.” } PUT /starwars/_doc/2 { “quote”: “Obi-Wan never told you what happened to your father.” } PUT /starwars/_doc/3 { “quote”: “<b>No</b>. I am your father.” }
GET /starwars/_doc/1 GET /starwars/_source/1
Search
POST /starwars/_search { “query”: { “match_all”: { } } }
GET vs POST
{ “took”: 1, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 3, “max_score”: 1, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 1, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } }, …
POST /starwars/_search { “query”: { “match”: { “quote”: “Droid” } } }
{ } “took”: 2, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 0.39556286, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “1”, “_score”: 0.39556286, “_source”: { “quote”: “These are <em>not</em> the droids you are looking for.” } } ] }
POST /starwars/_search { “query”: { “match”: { “quote”: “dad” } } }
… “hits”: { “total”: 2, “max_score”: 0.41913947, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.41913947, “_source”: { “quote”: “<b>No</b>. I am your father.” } }, { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.39291072, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } } ] } }
POST /starwars/_search { “query”: { “match”: { “quote”: “machine” } } }
{ } “took”: 2, “timed_out”: false, “_shards”: { “total”: 1, “successful”: 1, “skipped”: 0, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 1.2499592, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “1”, “_score”: 1.2499592, “_source”: { “quote”: “These are <em>not</em> the droids you are looking for.” } } ] }
POST /starwars/_search { “query”: { “match_phrase”: { “quote”: “I am your father” } } }
{ } “took”: 3, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 1.5665855, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 1.5665855, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] }
POST /starwars/_search { “query”: { “match_phrase”: { “quote”: { “query”: “I am father”, “slop”: 1 } } } }
{ } “took”: 16, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 0.8327639, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.8327639, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] }
POST /starwars/_search { “query”: { “match_phrase”: { “quote”: { “query”: “I am not your father”, “slop”: 1 } } } }
{ } “took”: 5, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 1.0409548, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 1.0409548, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] }
POST /starwars/_search { “query”: { “match”: { “quote”: { “query”: “van”, “fuzziness”: “AUTO” } } } }
{ } “took”: 14, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 0.18155496, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.18155496, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } } ] }
POST /starwars/_search { “query”: { “match”: { “quote”: { “query”: “ovi-van”, “fuzziness”: 1 } } } }
{ } “took”: 109, “timed_out”: false, “_shards”: { “total”: 5, “successful”: 5, “failed”: 0 }, “hits”: { “total”: 1, “max_score”: 0.3798467, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.3798467, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } } ] }
FuzzyQuery History http://blog.mikemccandless.com/2011/03/lucenes-fuzzyquery-is-100-times-faster.html Before: Brute force Now: Levenshtein Automaton
http://blog.notdot.net/2010/07/Damn-Cool-Algorithms-Levenshtein-Automata
SELECT * FROM starwars WHERE quote LIKE “?an” OR quote LIKE “V?n” OR quote LIKE “Va?”
Scoring
Term Frequency / Inverse Document Frequency (TF/IDF) Search one term
BM25 Default in Elasticsearch 5.0 https://speakerdeck.com/elastic/improved-text-scoring-withbm25
Term Frequency
Inverse Document Frequency
Field-Length Norm
POST /starwars/_search?explain=true { “query”: { “match”: { “quote”: “father” } } }
… “_explanation”: { “value”: 0.41913947, “description”: “weight(Synonym(quote:dad quote:father) in 0) [PerFieldSimilarity], result of:”, “details”: [ { “value”: 0.41913947, “description”: “score(doc=0,freq=2.0 = termFreq=2.0\n), product of:”, “details”: [ { “value”: 0.2876821, “description”: “idf(docFreq=1, docCount=1)”, “details”: [] }, { “value”: 1.4569536, “description”: “tfNorm, computed from:”, “details”: [ { “value”: 2, “description”: “termFreq=2.0”, “details”: [] }, …
Score 0.41913947: i am your father 0.39291072: obi wan never told what happen your father you
Vector Space Model Search multiple terms
Search your father
Coordination Factor Reward multiple terms
Search for 3 terms 1 term: 2 terms: 3 terms:
Practical Scoring Function Putting it all together
score(q,d) = queryNorm(q) · coord(q,d) · ∑ ( tf(t in d) · idf(t)² · t.getBoost() · norm(t,d) ) (t in q)
Function Score Script, weight, random, field value, decay (geo or date)
POST /starwars/_search { “query”: { “function_score”: { “query”: { “match”: { “quote”: “father” } }, “random_score”: {} } } }
Compare Scores “100% perfect” vs a “50%” match
Don’t do this. Seriously. Stop trying to think about your problem this way, it’s not going to end well. — https://wiki.apache.org/lucene-java/ ScoresAsPercentages
GET /starwars/_analyze { “analyzer” : “my_analyzer”, “text”: “These are my father’s machines.” }
{ “tokens”: [ { “token”: “my”, “start_offset”: 10, “end_offset”: 12, “type”: “<ALPHANUM>”, “position”: 2 }, { “token”: “father”, “start_offset”: 13, “end_offset”: 21, “type”: “<ALPHANUM>”, “position”: 3 }, { “token”: “dad”, “start_offset”: 13, “end_offset”: 21, “type”: “SYNONYM”, “position”: 3 }, { “token”: “machin”, “start_offset”: 22, “end_offset”: 30, “type”: “<ALPHANUM>”, “position”: 4 } ] }
PUT /starwars/_doc/4 { “quote”: “These are my father’s machines.” }
POST /starwars/_search { “query”: { “match”: { “quote”: “my father machine” } } }
“hits”: { “total”: 4, “max_score”: 2.92523, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “4”, “_score”: 2.92523, “_source”: { “quote”: “These are my father’s machines.” } }, { “_index”: “starwars”, “_type”: “_doc”, “_id”: “1”, “_score”: 0.8617505, “_source”: { “quote”: “These are <em>not</em> the droids you are looking for.” } }, …
2.92523 == 100%
DELETE /starwars/_doc/4 POST /starwars/_search { “query”: { “match”: { “quote”: “my father machine” } } }
“hits”: { “total”: 3, “max_score”: 1.2499592, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “1”, “_score”: 1.2499592, “_source”: { “quote”: “These are <em>not</em> the droids you are looking for.” } }, …
1.2499592 == 43% or 100%?
PUT /starwars/_doc/4 { “quote”: “These droids are my father’s father’s machines.” } POST /starwars/_search { “query”: { “match”: { “quote”: “my father machine” } } }
“hits”: { “total”: 4, “max_score”: 3.0068164, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “4”, “_score”: 3.0068164, “_source”: { “quote”: “These droids are my father’s father’s machines.” } }, { “_index”: “starwars”, “_type”: “_doc”, “_id”: “1”, “_score”: 0.89701396, “_source”: { “quote”: “These are <em>not</em> the droids you are looking for.” } }, …
3.0068164 == 103%?
Performance
Conclusion
Indexing Formatting Tokenize Lowercase, Stop Words, Stemming Synonyms
Scoring Term Frequency Inverse Document Frequency Field-Length Norm Vector Space Model
Thank You! Questions? Philipp Krenn PS: Stickers @xeraa
The End
More
POST /starwars/_search { “query”: { “match”: { “quote”: “father” } }, “highlight”: { “type”: “unified”, “pre_tags”: [ “<tag>” ], “post_tags”: [ “</tag>” ], “fields”: { “quote”: {} } } }
… “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.41913947, “_source”: { “quote”: “<b>No</b>. I am your father.” }, “highlight”: { “quote”: [ “<b>No</b>. I am your <tag>father</tag>.” ] } }, …
Boolean Queries must must_not should filter
POST /starwars/_search { “query”: { “bool”: { “must”: { “match”: { “quote”: “father” } }, “should”: [ { “match”: { “quote”: “your” } }, { “match”: { “quote”: “obi” } } ] } } }
… “hits”: { “total”: 2, “max_score”: 0.96268076, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.96268076, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } }, { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.73245656, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] } }
POST /starwars/_search { “query”: { “bool”: { “filter”: { “match”: { “quote”: “father” } }, “should”: [ { “match”: { “quote”: “your” } }, { “match”: { “quote”: “obi” } } ] } } }
… “hits”: { “total”: 2, “max_score”: 0.56977004, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.56977004, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } }, { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.31331712, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] } }
Named Queries & minimum_should_match
POST /starwars/_search { “query”: { “bool”: { “must”: { “match”: { “quote”: “father” } }, “should”: [ { “match”: { “quote”: { “query”: “your”, “_name”: “quote-your” } } }, { “match”: { “quote”: { “query”: “obi”, “_name”: “quote-obi” } } }, { “match”: { “quote”: { “query”: “droid”, “_name”: “quote-droid” } } } ], “minimum_should_match”: 2 } } }
… “hits”: { “total”: 1, “max_score”: 1.8154771, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 1.8154771, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” }, “matched_queries”: [ “quote-obi”, “quote-your” ] } ] } }
Boosting >1 increase, <1 decrease, <0 punish
POST /starwars/_search { “query”: { “bool”: { “must”: { “match”: { “quote”: “father” } }, “should”: [ { “match”: { “quote”: “your” } }, { “match”: { “quote”: { “query”: “obi”, “boost”: 3 } } } ] } } }
… “hits”: { “total”: 2, “max_score”: 1.5324509, “hits”: [ { “_index”: “starwars”, “_type”: “_doc”, “_id”: “2”, “_score”: 1.5324509, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } }, { “_index”: “starwars”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.73245656, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] } }
Suggestion Suggest a similar text _search end point _suggest deprecated since 5.0
POST /starwars/_search { “query”: { “match”: { “quote”: “drui” } }, “suggest”: { “my_suggestion” : { “text” : “drui”, “term” : { “field” : “quote” } } } }
… “hits”: { “total”: 0, “max_score”: null, “hits”: [] }, “suggest”: { “my_suggestion”: [ { “text”: “drui”, “offset”: 0, “length”: 4, “options”: [ { “text”: “droid”, “score”: 0.5, “freq”: 1 } ] } ] } }
NGram Partial matches Trigram Edge Gram
GET /_analyze { “char_filter”: [ “html_strip” ], “tokenizer”: { “type”: “ngram”, “min_gram”: “3”, “max_gram”: “3”, “token_chars”: [ “letter” ] }, “filter”: [ “lowercase” ], “text”: “These are <em>not</em> the droids you are looking for.” }
{ “tokens”: [ { “token”: “the”, “start_offset”: 0, “end_offset”: 3, “type”: “word”, “position”: 0 }, { “token”: “hes”, “start_offset”: 1, “end_offset”: 4, “type”: “word”, “position”: 1 }, { “token”: “ese”, “start_offset”: 2, “end_offset”: 5, “type”: “word”, “position”: 2 }, { “token”: “are”, “start_offset”: 6, “end_offset”: 9, “type”: “word”, “position”: 3 }, …
GET /_analyze { “char_filter”: [ “html_strip” ], “tokenizer”: { “type”: “edge_ngram”, “min_gram”: “1”, “max_gram”: “3”, “token_chars”: [ “letter” ] }, “filter”: [ “lowercase” ], “text”: “These are <em>not</em> the droids you are looking for.” }
{ “tokens”: [ { “token”: “t”, “start_offset”: 0, “end_offset”: 1, “type”: “word”, “position”: 0 }, { “token”: “th”, “start_offset”: 0, “end_offset”: 2, “type”: “word”, “position”: 1 }, { “token”: “the”, “start_offset”: 0, “end_offset”: 3, “type”: “word”, “position”: 2 }, { “token”: “a”, “start_offset”: 6, “end_offset”: 7, “type”: “word”, “position”: 3 }, { “token”: “ar”, “start_offset”: 6, “end_offset”: 8, “type”: “word”, “position”: 4 }, …
Combining Analyzers Reindex Store multiple times Combine scores
PUT /starwars_v42 { “settings”: { “analysis”: { “filter”: { “my_synonym_filter”: { “type”: “synonym”, “synonyms”: [ “droid,machine”, “father,dad” ] }, “my_ngram_filter”: { “type”: “ngram”, “min_gram”: “3”, “max_gram”: “3”, “token_chars”: [ “letter” ] } },
“analyzer”: { “my_lowercase_analyzer”: { “char_filter”: [ “html_strip” ], “tokenizer”: “whitespace”, “filter”: [ “lowercase” ] }, “my_full_analyzer”: { “char_filter”: [ “html_strip” ], “tokenizer”: “standard”, “filter”: [ “lowercase”, “stop”, “snowball”, “my_synonym_filter” ] },
}, } } “my_ngram_analyzer”: { “char_filter”: [ “html_strip” ], “tokenizer”: “whitespace”, “filter”: [ “lowercase”, “stop”, “my_ngram_filter” ] }
} “mappings”: { “properties”: { “quote”: { “type”: “text”, “fields”: { “lowercase”: { “type”: “text”, “analyzer”: “my_lowercase_analyzer” }, “full”: { “type”: “text”, “analyzer”: “my_full_analyzer” }, “ngram”: { “type”: “text”, “analyzer”: “my_ngram_analyzer” } } } } }
POST /_reindex { “source”: { “index”: “starwars” }, “dest”: { “index”: “starwars_v42” } }
PUT _alias { “actions”: [ { “add”: { “index”: “starwars_v42”, “alias”: “starwars_extended” } } ] }
Aliases Atomic remove and add Point to multiple indices (read-only)
POST /starwars_extended/_search?explain=true { “query”: { “multi_match”: { “query”: “obiwan”, “fields”: [ “quote”, “quote.lowercase”, “quote.full”, “quote.ngram” ], “type”: “most_fields” } } }
… “hits”: { “total”: 1, “max_score”: 0.4912064, “hits”: [ { “_shard”: “[starwars_v42][2]”, “_node”: “BCDwzJ4WSw2dyoGLTzwlqw”, “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.4912064, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” }, …
Whitespace Tokenizer “weight( Synonym(quote.ngram:biw quote.ngram:iwa quote.ngram:obi quote.ngram:wan) in 0) [PerFieldSimilarity], result of:”
POST /starwars_extended/_search { “query”: { “multi_match”: { “query”: “you”, “fields”: [ “quote”, “quote.lowercase”, “quote.full^5”, “quote.ngram” ], “type”: “best_fields” } } }
“hits”: [ { “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “1”, “_score”: 1.6022799, “_source”: { “quote”: “These are <em>not</em> the droids you are looking for.” } }, { “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “2”, “_score”: 1.4997643, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } }, { “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.38650417, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ]
Multi Match Type best_fields Score of the best field (default) cross_fields All terms in at least one field most_fields Score sum of all fields phrase
Different Analyzers for Indexing and Searching Per query In the mapping
POST /starwars_extended/_search { “query”: { “match”: { “quote.ngram”: { “query”: “the”, “analyzer”: “standard” } } } }
… “hits”: [ { “_index”: “starwars_extended”, “_type”: “_doc”, “_id”: “2”, “_score”: 0.38254172, “_source”: { “quote”: “Obi-Wan never told you what happened to your father.” } }, { “_index”: “starwars_extended”, “_type”: “_doc”, “_id”: “3”, “_score”: 0.36165747, “_source”: { “quote”: “<b>No</b>. I am your father.” } } ] …
Edge Gram vs Trigram Extending a mapping Testing a custom mapping
POST /starwars_extended/_close PUT /starwars_extended/_settings { “analysis”: { “filter”: { “my_edgegram_filter”: { “type”: “edge_ngram”, “min_gram”: 3, “max_gram”: 10 } }, “analyzer”: { “my_edgegram_analyzer”: { “char_filter”: [ “html_strip” ], “tokenizer”: “standard”, “filter”: [ “lowercase”, “my_edgegram_filter” ] } } } } POST /starwars_extended/_open
GET starwars_extended/_analyze { “text”: “Father”, “analyzer”: “my_edgegram_analyzer” }
{ } “tokens”: [ { “token”: “fat”, “start_offset”: 0, “end_offset”: 6, “type”: “<ALPHANUM>”, “position”: 0 }, { “token”: “fath”, “start_offset”: 0, “end_offset”: 6, “type”: “<ALPHANUM>”, “position”: 0 }, { “token”: “fathe”, “start_offset”: 0, “end_offset”: 6, “type”: “<ALPHANUM>”, “position”: 0 }, { “token”: “father”, “start_offset”: 0, “end_offset”: 6, “type”: “<ALPHANUM>”, “position”: 0 } ]
PUT /starwars_extended/_mapping { “properties”: { “quote”: { “type”: “text”, “fields”: { “edgegram”: { “type”: “text”, “analyzer”: “my_edgegram_analyzer”, “search_analyzer”: “standard” } } } } }
PUT /starwars_extended/_doc/4 { “quote”: “I find your lack of faith disturbing.” } PUT /starwars_extended/_doc/5 { “quote”: “That… is your failure.” }
GET /starwars_extended/_termvectors/4 { “fields”: [ “quote.edgegram” ], “offsets”: true, “payloads”: true, “positions”: true, “term_statistics”: true, “field_statistics”: true }
{ “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “4”, “_version”: 1, “found”: true, “took”: 3, “term_vectors”: { “quote.edgegram”: { “field_statistics”: { “sum_doc_freq”: 26, “doc_count”: 2, “sum_ttf”: 26 }, “terms”: { “dis”: { “doc_freq”: 1, “ttf”: 1, “term_freq”: 1, “tokens”: [ { “position”: 6, “start_offset”: 26, “end_offset”: 36 } ] }, “dist”: { “doc_freq”: 1, “ttf”: 1, …
POST /starwars_extended/_search { “query”: { “match”: { “quote”: “fail” } } }
POST /starwars_extended/_search { “query”: { “match”: { “quote.lowercase”: “fail” } } }
POST /starwars_extended/_search { “query”: { “match”: { “quote.full”: “fail” } } }
POST /starwars_extended/_search { “query”: { “match”: { “quote.ngram”: “fail” } } }
… “hits”: { “total”: 2, “max_score”: 1.0135446, “hits”: [ { “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “4”, “_score”: 1.0135446, “_source”: { “quote”: “I find your lack of faith disturbing.” } }, { “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “5”, “_score”: 0.50476736, “_source”: { “quote”: “That… is your failure.” } } ] …
POST /starwars_extended/_search { “query”: { “match”: { “quote.edgegram”: “fail” } } }
… “hits”: { “total”: 1, “max_score”: 0.39556286, “hits”: [ { “_index”: “starwars_v42”, “_type”: “_doc”, “_id”: “5”, “_score”: 0.39556286, “_source”: { “quote”: “That… is your failure.” } } ] …
Today’s applications are expected to provide powerful full-text search. But how does that work in general and how do I implement it on my site or in my application? Actually, this is not as hard as it sounds at first. This talk covers:
- How full-text search works in general and what the differences to databases are.
- How the score or quality of a search result is calculated.
- How to handle languages, search for terms and phrases, run boolean queries, add suggestions, work with ngrams, and more with Elasticsearch.
We will run all the queries live and explore the possibilities for your use-case.
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