1. “ Cool, Bonsai, Cool” An introduction to Clinton Gormley, YAPC::EU 2011

2. Why do I need a search engine?

6. Search is how we find stuff

9. How does a search engine work?

11. Acme:: Magic 8Ball Acme:: Magic ::Pony Config:: Magic File:: Magic File::MimeInfo:: Magic File::M Magic ::XS Magic Template Meta::File::M Magic MRO:: Magic Template:: Magic Template:: Magic ::Pager Test:: Magic XS:: Magic Ext XS::Object:: Magic

12. Magic == inverted index + relevance scoring

13. Acme::Magic8Ball Acme::Magic::Pony Config::Magic File::Magic File::MimeInfo::Magic File::MMagic::XS MagicTemplate Meta::File::MMagic MRO::Magic Template::Magic Template::Magic::Pager Test::Magic XS::MagicExt XS::Object::Magic Take some text

14. Acme::Magic8Ball Acme::Magic::Pony Config::Magic File::Magic File::MimeInfo::Magic File::MMagic::XS MagicTemplate Meta::File::MMagic MRO::Magic Template::Magic Template::Magic::Pager Test::Magic XS::MagicExt XS::Object::Magic Tokenise it

15. acme magic 8 ball acme magic pony config magic file magic file mime info magic file m magic xs magic template meta file m magic mro magic template magic template magic pager test magic xs magic ext xs object magic Tokenise it

16. acme magic 8 ball acme magic pony config magic file magic file mime info magic file m magic xs magic template meta file m magic mro magic template magic template magic pager test magic xs magic ext xs object magic Find unique tokens/terms

17. 8 acme ball config ext file info m magic Find unique tokens/terms meta mime mro object pager pony template test xs

18. acme file magic mime template xs Acme::Magic8Ball Acme::Magic::Pony File::Magic File::MimeInfo::Magic MagicTemplate Template::Magic Template::Magic::Pager XS::Object::Magic XS::MagicExt File::MMagic::XS Map terms to documents

19. acme file magic mime template xs Acme::Magic8Ball Acme::Magic::Pony File::Magic File::MimeInfo::Magic MagicTemplate Template::Magic Template::Magic::Pager XS::Object::Magic XS::MagicExt File::MMagic::XS Search for: “ file xs ”

20. Search for: “ file xs ” acme file magic mime template xs Acme::Magic8Ball Acme::Magic::Pony File::Magic File::MimeInfo::Magic MagicTemplate Template::Magic Template::Magic::Pager XS::Object::Magic XS::MagicExt File::MMagic::XS

21. But, not just about finding

23. Sort by RELEVANCE

24. Relevance: How many matching terms does this document contain?

25. Relevance: How often does each term appear in this document, as a % of its length?

26. Relevance: How frequently does each term appear in all your documents ?

27. Relevance: Can be customised

28. Relevance: Can be customised By document or field

29. Relevance: Can be customised By document or field At index or search time

30. Simple as: C an be customised B y document or field A t index or search time

31. FAST!

32. POWERFUL!

33. MAGIC!

37. www.elasticsearch.org

38. elasticsearch is:

41. distributed

43. distributed

44. RESTful

46. distributed

47. RESTful

48. search engine

50. distributed

51. RESTful

52. search engine

53. built on top of Lucene

54. Installing elasticsearch: Latest version at: http://www.elasticsearch.org/download/ wget https://github.com/.../elasticsearch-0.17.6.tar.gz tar -xzf elasticsearch-0.17.6.tar.gz cd elasticsearch-0.17.6/ ./bin/elasticsearch

55. Installing ElasticSearch.pm: Latest version at: https://metacpan.org/module/ElasticSearch cpanm ElasticSearch perl -de 0 > use ElasticSearch; > $e = ElasticSearch->new( trace_calls => 1) > $e->cluster_health

56. Some terminology Relational DB elasticsearch

57. Some terminology Relational DB elasticsearch database ⇒ index

58. Some terminology Relational DB elasticsearch database ⇒ index table ⇒ type

59. Some terminology Relational DB elasticsearch database ⇒ index table ⇒ type row ⇒ document

60. Some terminology Relational DB elasticsearch database ⇒ index table ⇒ type row ⇒ document column ⇒ field

61. Some terminology Relational DB elasticsearch database ⇒ index table ⇒ type row ⇒ document column ⇒ field schema ⇒ mapping

62. Some terminology Relational DB elasticsearch database ⇒ index table ⇒ type row ⇒ document column ⇒ field schema ⇒ mapping index ⇒ everything is indexed

63. Some terminology Relational DB elasticsearch database ⇒ index table ⇒ type row ⇒ document column ⇒ field schema ⇒ mapping index ⇒ everything is indexed SQL ⇒ query DSL

64. Clustering

65. Clustering auto-discovery

66. Clustering single master auto-elected

67. Clustering immediate failover master re-election

68. Clustering index ==

69. Clustering index == 1 or more primary shards

70. Clustering index == 1 or more primary shards + 0 or more replica shards

71. Clustering more primary shards

72. Clustering ⇒ faster indexing ⇒ more scale more primary shards

73. Clustering ⇒ faster indexing ⇒ more scale more primary shards more replicas

74. Clustering ⇒ faster indexing ⇒ more scale ⇒ faster searching ⇒ more failover more primary shards more replicas

75. Clustering Big subject... http://www.elasticsearch.org/videos/2011/08/09/road-to-a-distributed-searchengine-berlinbuzzwords.html http://berlinbuzzwords.de/sites/ berlinbuzzwords.de/files/elasticsearch-bbuzz2011.pdf

76. Document oriented:

77. Document oriented: No ORM required

78. Document oriented: JSON in ⇔ JSON out

79. Schema free Dynamic mapping

80. Schema free Dynamic (or strict) mapping

81. Unknown field?

82. elasticsearch guesses the type

83. elasticsearch guesses the type and indexes it

84. Put data in: $e->index( );

85. Put data in: $e->index( index => 'twitter', );

86. Put data in: $e->index( index => 'twitter', type => 'tweet', );

87. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, );

88. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, # optional );

89. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, # ES always returns the ID );

90. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, data => { } );

91. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, data => { tweet => “ElasticSearch is cool”, } );

92. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, data => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, } );

93. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, data => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, } );

94. Put data in: $e->index( index => 'twitter', type => 'tweet', id => 1, data => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => [“search”,”perl”], } );

95. Realtime GET

96. Retrieve your doc immediately

97. Persistent

98. No commit required

99. Get data out: $e->get( index => 'twitter', type => 'tweet', id => 1);

100. Get data out: $e->get( index => 'twitter', type => 'tweet', id => 1); { _index => 'twitter', _type => 'tweet', _id => 1, }

101. Get data out: $e->get( index => 'twitter', type => 'tweet', id => 1); { _index => 'twitter', _type => 'tweet', _id => 1, _version => 1, }

102. Get data out: $e->get( index => 'twitter', type => 'tweet', id => 1); { _index => 'twitter', _type => 'tweet', _id => 1, _version => 1, _source => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => ['search','perl'], } }

103. bulk-indexing

104. bulk-indexing multi-get

105. bulk-indexing multi-get avoids http latency

106. bulk-indexing multi-get avoids http latency 10x as fast!

107. Versioning

108. Versioning “ Optimistic currency control”

109. Versioning “ Put if absent”

110. Versioning Optional

111. Versioning Can use external version numbers

112. So far, all we have is a NoSQL document store which is fast, reliable, scalable & easy to use

113. So far, all we have is a NoSQL document store which is fast, reliable, scalable & easy to use

115. Simple search $e->search( index => 'twitter', type => 'tweet', );

116. Simple search $e->search( index => ['twitter','facebook'] , type => ['tweet','post'] , );

117. Simple search $e->search( # all indices # all types );

118. Simple search $e->search( index => 'twitter', type => 'tweet', query => { } );

119. Simple search $e->search( index => 'twitter', type => 'tweet', query => { text => { _all => 'clinton' } } );

120. Simple search $e->search( index => 'twitter', type => 'tweet', query b => 'clinton' );

121. Simple search $e->search( index => 'twitter', type => 'tweet', query b => 'clinton' # ElasticSearch::SearchBuilder, # like SQL::Abstract );

122. Search results { took => 1, hits => { total => 1, max_score => 1, hits => [{ _score => 1, _index => 'twitter', _type => 'tweet', _id => 1, _source => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => ['search','perl'], } }], }, ... other information ... }

123. Search results { took => 1, # milliseconds hits => { total => 1, max_score => 1, hits => [{ _score => 1, _index => 'twitter', _type => 'tweet', _id => 1, _source => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => ['search','perl'], } }], }, ... other information ... }

124. Search results { took => 1, hits => { total => 1, # total results max_score => 1, hits => [{ _score => 1, _index => 'twitter', _type => 'tweet', _id => 1, _source => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => ['search','perl'], } }], }, ... other information ... }

125. Search results { took => 1, hits => { total => 1, max_score => 1, hits => [{ _score => 1, _index => 'twitter', _type => 'tweet', _id => 1, _source => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => ['search','perl'], } }], }, ... other information ... }

126. Search results { took => 1, hits => { total => 1, max_score => 1, hits => [{ _score => 1, _index => 'twitter', _type => 'tweet', _id => 1, _source => { tweet => “ElasticSearch is cool”, sent => “2011-08-16 15:15:00”, user => { name => “Clinton”, user_id => 123 }, tags => ['search','perl'], } }], }, ... other information ... }

127. JSON doc included in results

128. No need to fetch from DB

129. Docs visible to search in near-real time (< 1 second)

130. refresh_index() to force

131. What can you do with search?

132. standard text search

133. ...with highlighting

134. stemming

135. stemming arabic, armenian, basque, brazilian, bulgarian, catalan, chinese, cjk, czech, danish, dutch, english, finnish, french, galician, german, german2, greek, hindi, hungarian, indonesian, italian, kp, light_finish, light_french, light_german, light_hungarian, light_italian, light_portuguese, light_russian, light_spanish, light_swedish., lovins, minimal_english, minimal_french, minimal_german, minimal_portuguese, norwegian, persian, porter, porter2, portuguese, possessive_english, romanian, russian, spanish, swedish, thai, turkish

136. ngrams & edge-ngrams

137. auto-complete

138. camelCase

139. camelCase

140. camelCase

141. term facets, date histograms

142. ranges

143. geo bounding box

144. geo distance

145. geo distance ranges

146. geo polygons

149. “‎ Terms of endearment” The ElasticSearch query language explained‎ Thurs. 14:35 - Auditorija 301