Elasticsearch in 20 Minutes

San Francisco Ruby Meetup
November 7, 2013

Transcript

1. Kevin Kluge elasticsearch in 20 minutes
2. Plug & Play
3. Installation $ wget https://download.elasticsearch.org/... $ tar -xf elasticsearch-0.90.6.tar.gz $ ./elasticsearch-0.90.6/bin/elasticsearch -f ... [INFO ][node][Ghost Maker] {0.90.6}[5645]: initializing ...
4. Index a document... $ curl -X PUT localhost:9200/products/product/1 -d '{ "title" : "Welcome!" }'
5. Update a document... $ curl -X PUT localhost:9200/products/product/1 -d '{ "title" : "Welcome to the Ruby meetup!" }'
6. Search for documents.... $ curl -X GET localhost:9200/products/_search?q=welcome
7. Shard & Cluster
8. A curl  -­‐XPUT  'http://localhost:9200/a/'  -­‐d  '{        "settings"  :  {                "index"  :  {                        "number_of_shards"      :  3,                        "number_of_replicas"  :  1                }        } }' Index is partitioned into 3 primary shards, each is duplicated in 1 replica shard A1 A2 A3 Replicas Primaries A1' A2' A3'
9. 1 node 2 nodes 3 nodes "index.routing.allocation.exclude.name"      :  "Node1" "cluster.routing.allocation.exclude.name"  :  "Node3" ...
11. Until you know what to tweak...
12. JSON & HTTP
13. {    "id"        :  "abc123",    "title"  :  "A  JSON  Document",    "body"    :  "A  JSON  document  is  a  ...",    "published_on"  :  "2013/06/27  10:00:00",    "featured"          :  true,        "tags"    :  ["search",  "json"],    "author"  :  {        "first_name"  :  "Clara",        "last_name"    :  "Rice",        "email"            :  "clara@rice.org"    } } Documents as JSON Data structure with basic types, arrays and deep hierarchies
14. http:// Lingua Franca of APIs Also supported: Native Java protocol, Thrift, Memcached
15. Search & Find
16. Terms apple apple  iphone Phrases "apple  iphone" Proximity "apple  safari"~5 Fuzzy apple~0.8 Wildcards app* *pp* Boosting apple^10  safari Range [2011/05/01  TO  2011/05/31] [java  TO  json] Boolean apple  AND  NOT  iphone +apple  -­‐iphone (apple  OR  iphone)  AND  NOT  review Fields title:iphone^15  OR  body:iphone published_on:[2011/05/01  TO  "2011/05/27  10:00:00"] http://lucene.apache.org/java/3_1_0/queryparsersyntax.html $  curl  -­‐X  GET  "http://localhost:9200/_search?q=<YOUR  QUERY>"
17. curl  -­‐X  GET  localhost:9200/articles/_search  -­‐d  '{ "query" : { "filtered" : { "query" : { "bool" : { "must" : { "match" : { "author.first_name" : { "query" : "claire", "fuzziness" : 0.1 } } }, "must" : { "multi_match" : { "query" : "elasticsearch", "fields" : ["title^10", "body"] } } } }, "filter": { "and" : [ { "terms" : { "tags" : ["search"] } }, { "range" : { "published_on": {"from": "2013"} } }, { "term" : { "featured" : true } } ] } } } }' JSON-based Query DSL
18. curl  -­‐X  GET  localhost:9200/articles/_search  -­‐d  '{ "query" : { "filtered" : { "query" : { "bool" : { "must" : { "match" : { "author.first_name" : { "query" : "claire", "fuzziness" : 0.1 } } }, "must" : { "multi_match" : { "query" : "elasticsearch", "fields" : ["title^10", "body"] } } } }, "filter": { "and" : [ { "terms" : { "tags" : ["search"] } }, { "range" : { "published_on": {"from": "2013"} } }, { "term" : { "featured" : true } } ] } } } }' JSON-based Query DSL
19. curl  -­‐X  GET  localhost:9200/articles/_search  -­‐d  '{ "query" : { "filtered" : { "query" : { "bool" : { "must" : { "match" : { "author.first_name" : { "query" : "claire", "fuzziness" : 0.1 } } }, "must" : { "multi_match" : { "query" : "elasticsearch", "fields" : ["title^10", "body"] } } } }, "filter": { "and" : [ { "terms" : { "tags" : ["search"] } }, { "range" : { "published_on": {"from": "2013"} } }, { "term" : { "featured" : true } } ] } } } }' JSON-based Query DSL
20. curl  -­‐X  GET  localhost:9200/articles/_search  -­‐d  '{ "query" : { "filtered" : { "query" : { "bool" : { "must" : { "match" : { "author.first_name" : { "query" : "claire", "fuzziness" : 0.1 } } }, "must" : { "multi_match" : { "query" : "elasticsearch", "fields" : ["title^10", "body"] } } } }, "filter": { "and" : [ { "terms" : { "tags" : ["search"] } }, { "range" : { "published_on": {"from": "2013"} } }, { "term" : { "featured" : true } } ] } } } }' JSON-based Query DSL
21. curl  -­‐X  GET  localhost:9200/articles/_search  -­‐d  '{ "query" : { "filtered" : { "query" : { "bool" : { "must" : { "match" : { "author.first_name" : { "query" : "claire", "fuzziness" : 0.1 } } }, "must" : { "multi_match" : { "query" : "elasticsearch", "fields" : ["title^10", "body"] } } } }, "filter": { "and" : [ { "terms" : { "tags" : ["search"] } }, { "range" : { "published_on": {"from": "2013"} } }, { "term" : { "featured" : true } } ] } } } }' JSON-based Query DSL
22. “Find all articles with ‘search’ in their title or body, give matches in titles higher score” Full-text Search “Find all articles from year 2013 tagged ‘search’” Structured Search Use function_score for complex scoring Custom Scoring
23. Fetch document field ➝ Pick configured analyzer ➝ Parse text into tokens ➝ Apply token filters ➝ Store into index How Search Engine Works? Result Results Query How Users See Search?
24. Mapping curl -X PUT localhost:9200/articles/article/_mapping -d '{ "article" : { "properties" : { "title" : { "type" : "string", "analyzer" : "czech" } } } }' Configuring document properties for the search engine
25. _analyze?pretty&format=text&text=ruby+is+cool&analyzer=standard The _analyze API [ruby:0-­‐>4:<ALPHANUM>]\n\n3:   \n[cool:8-­‐>12:<ALPHANUM>]\n" _analyze?pretty&format=text&text=Žluťoučký+kůň+skákal+přes+potok&analyzer=czech [žluťoučk:0-­‐>9:<ALPHANUM>]\n \n2:  \n[koň:10-­‐ >13:<ALPHANUM>]\n\n3:   \n[skákal:14-­‐>20:<ALPHANUM>] \n\n5:  \n[potok:26-­‐ >31:<ALPHANUM>]\n _analyze?text=...&tokenizer=X&filters=A,B,C
26. Slice & Dice
27. Query Facets
28. curl -X POST 'localhost:9200/articles/_search?search_type=count&pretty' -d '{ "facets": { "tag-cloud": { "terms" : { "field" : "tags" } } } }' “Tag Cloud” With the terms Facet "facets"  :  {        "tag-­‐cloud"  :  {            "terms"  :  [  {                "term"  :  "ruby",                "count"  :  3            },  {                "term"  :  "java",                "count"  :  2            },            ...            }  ]        }    } Simplest “map/reduce” aggregation: document count per tag
29. curl -X GET 'localhost:9200/scores/_search/?search_type=count&pretty' -d '{ "facets": { "scores-per-subject" : { "terms_stats" : { "key_field" : "subject", "value_field" : "score" } } } }' Statistics on Student Scores With the terms_stats Facet "facets"  :  {        "scores-­‐per-­‐subject"  :  {            "_type"  :  "terms_stats",            "missing"  :  0,            "terms"  :  [  {                "term"  :  "math",                "count"  :  4,                "total_count"  :  4,                "min"  :  25.0,                "max"  :  92.0,                "total"  :  267.0,                "mean"  :  66.75            },  ...  ]        }    } Aggregating statistics per subject
30. curl -X GET 'localhost:9200/demo-scores/_search/?search_type=count&pretty' -d '{ "query" : { "match" : { "student" : "john" } }, "facets": { "scores-per-subject" : { "terms_stats" : { "key_field" : "subject", "value_field" : "score" } } } }' Statistics on Student Scores With the terms_stats Facet "facets"  :  {        "scores-­‐per-­‐subject"  :  {            "_type"  :  "terms_stats",            "missing"  :  0,            "terms"  :  [  {                "term"  :  "math",                "count"  :  1,                "total_count"  :  1,                "min"  :  85.0,                "max"  :  85.0,                "total"  :  85.0,                "mean"  :  85.0            },  ...  ]        }    } Realtime filtering with queries and filters
31. Facets (and Soon Aggregations) Terms Terms Stats Statistical Range Histogram Date Histogram Filter Query Geo Distance
32. Above & Beyond
33. Above & Beyond Bulk operations (For indexing and search operations) Percolator (“reversed search” — alerts, classification, …) Suggesters (“Did you mean …?”) Index aliases (Grouping, filtering or “renaming” of indices) Index templates (Automatic index configuration) Monitoring API (Amount of memory used, number of operations, …) Upcoming 1.0 Features…
34. Ruby! Tire as one of many clients (Ruby-fied DSL) New client (elasticsearch-ruby) GitHub repo: https://github.com/elasticsearch/elasticsearch-ruby Issues list: https://github.com/elasticsearch/elasticsearch-ruby/issues > gem install elasticsearch Karel Minařík is author; on IRC www.elasticsearch.org @kevinkluge
35. thanks!