Elasticsearch Server 3rd

While reading this book, you will be taken on a journey to the wonderful world of fulltext search provided by the Elasticsearch server. We will start with a general introduction to Elasticsearch, which covers how to start and run Elasticsearch, its basic concepts, and how to index and search your data in the most basic way. This book will also discuss the query language, so called Query DSL, that allows you to create complicated queries and filter returned results. In addition to all of this, youll see how you can use the aggregation framework to calculate aggregated data based on the results returned by your queries. We will implement the autocomplete functionality together and learn how to use Elasticsearch spatial capabilities and prospective search.

Elasticsearch Server Third Edition Leverage Elasticsearch to create a robust, fast, and flexible search solution with ease Rafał Kuć Marek Rogoziński BIRMINGHAM - MUMBAI Elasticsearch Server Third Edition Copyright © 2016 Packt Publishing All rights reserved No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews Every effort has been made in the preparation of this book to ensure the accuracy of the information presented However, the information contained in this book is sold without warranty, either express or implied Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals However, Packt Publishing cannot guarantee the accuracy of this information First published: October 2013 Second edition: February 2015 Third edition: February 2016 Production reference: 1230216 Published by Packt Publishing Ltd Livery Place 35 Livery Street Birmingham B3 2PB, UK ISBN 978-1-78588-881-6 www.packtpub.com Credits Authors Rafał Kuć Project Coordinator Nidhi Joshi Marek Rogoziński Proofreader Reviewer Safis Editing Paige Cook Indexer Commissioning Editor Rekha Nair Nadeem Bagban Graphics Acquisition Editor Jason Monteiro Divya Poojari Production Coordinator Content Development Editor Manu Joseph Kirti Patil Cover Work Technical Editor Utkarsha S Kadam Copy Editor Alpha Singh Manu Joseph About the Authors Rafał Kuć is a software engineer, trainer, speaker and consultant He is working as a consultant and software engineer at Sematext Group Inc where he concentrates on open source technologies such as Apache Lucene, Solr, and Elasticsearch He has more than 14 years of experience in various software domains—from banking software to e–commerce products He is mainly focused on Java; however, he is open to every tool and programming language that might help him to achieve his goals easily and quickly Rafał is also one of the founders of the solr.pl site, where he tries to share his knowledge and help people solve their Solr and Lucene problems He is also a speaker at various conferences around the world such as Lucene Eurocon, Berlin Buzzwords, ApacheCon, Lucene/Solr Revolution, Velocity, and DevOps Days Rafał began his journey with Lucene in 2002; however, it wasn't love at first sight When he came back to Lucene in late 2003, he revised his thoughts about the framework and saw the potential in search technologies Then Solr came and that was it He started working with Elasticsearch in the middle of 2010 At present, Lucene, Solr, Elasticsearch, and information retrieval are his main areas of interest Rafał is also the author of the Solr Cookbook series, ElasticSearch Server and its second edition, and the first and second editions of Mastering ElasticSearch, all published by Packt Publishing Marek Rogoziński is a software architect and consultant with more than 10 years of experience His specialization concerns solutions based on open source search engines, such as Solr and Elasticsearch, and the software stack for big data analytics including Hadoop, Hbase, and Twitter Storm He is also a cofounder of the solr.pl site, which publishes information and tutorials about Solr and Lucene libraries He is the coauthor of ElasticSearch Server and its second edition, and the first and second editions of Mastering ElasticSearch, all published by Packt Publishing He is currently the chief technology officer and lead architect at ZenCard, a company that processes and analyzes large quantities of payment transactions in real time, allowing automatic and anonymous identification of retail customers on all retailer channels (m-commerce/e-commerce/brick&mortar) and giving retailers a customer retention and loyalty tool About the Reviewer Paige Cook works as a software architect for Videa, part of the Cox Family of Companies, and lives near Atlanta, Georgia He has twenty years of experience in software development, primarily with the Microsoft NET Framework His career has been largely focused on building enterprise solutions for the media and entertainment industry He is especially interested in search technologies using the Apache Lucene search engine and has experience with both Elasticsearch and Apache Solr Apart from his work, he enjoys DIY home projects and spending time with his wife and two daughters www.PacktPub.com eBooks, discount offers, and more Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? 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PacktLib is Packt's online digital book library Here, you can search, access, and read Packt's entire library of books Why subscribe? • Fully searchable across every book published by Packt • Copy and paste, print, and bookmark content • On demand and accessible via a web browser Table of Contents Preface Chapter 1: Getting Started with Elasticsearch Cluster Full text searching The Lucene glossary and architecture Input data analysis Indexing and querying Scoring and query relevance The basics of Elasticsearch Key concepts of Elasticsearch xv 2 6 Index Document Document type Mapping 8 Key concepts of the Elasticsearch infrastructure Nodes and clusters Shards Replicas Gateway Indexing and searching Installing and configuring your cluster Installing Java Installing Elasticsearch Running Elasticsearch Shutting down Elasticsearch The directory layout Configuring Elasticsearch The system-specific installation and configuration Installing Elasticsearch on Linux Configuring Elasticsearch as a system service on Linux Elasticsearch as a system service on Windows [i] 9 9 10 10 12 12 12 13 15 15 16 18 18 20 20 index indexing 10, 11, 50 installing 12 installing, with DEB package 19 installing, with RPM package 18 key concepts Kibana, URL 504 mapping monitoring 502 paging 101, 102 parameters, passing to script fields 110, 111 plugins 408 querying 97-101 reference documentation, URL 376 result size, controlling 101, 102 return fields, selecting 105, 106 running 13, 14 score, limiting 104 script fields, using 108, 110 scripting capabilities 230 searching 10, 11 shutting down 15 source filtering 106, 107 spatial capabilities 355 URL 12, 78 version value, returning 103, 104 Elasticsearch cluster preparing, for high indexing 492 preparing, for high querying 492 Elasticsearch HQ tool using 503 Elasticsearch indexing about 50 indices, creating 52 replicas 50, 51 shards 50, 51 Elasticsearch infrastructure cluster gateway 10 key concepts node replica shard Elasticsearch, monitoring about 502 Elasticsearch HQ tool, using 502, 503 Marvel tool, using 504 SPM tool, using 505 Elasticsearch time machine about 421 old snapshots, deleting 427 parameters 426 snapshot repository, creating 422, 423 snapshot, restoring 425, 426 snapshots, creating 424 exists query 119 Explain API URL 272 explain information about 267 field analysis 267-269 query, explaining 269-272 F factors, for score property calculation coord 228 document boost 228 field boost 228 inverse document frequency 228 length norm 228 query norm 228 term frequency 228 FastVectorHighlighter URL 172 Fedora Linux URL 18 fielddata cache about 412 circuit breakers 413 size, controlling 412 filtering about 449 exclude parameter 450 include parameter 450 require parameter 450 filters language stemming filters lowercase filter synonyms filter [ 511 ] full text searching about Apache Lucene, architecture 2-4 Apache Lucene, glossary 2-4 indexing 5, input data analysis 4, querying 5, query relevance scoring function score query about 255 decay functions 261 field_value_factor function 258 random_score function 260 script_score function 259 structure 256, 257 weight factor function 258 function_score query URL 262 fuzzy query 130 G gateway about 10 recovery options 401 general preparations, single Elasticsearch node about 478 file descriptors 479 swapping, avoiding 478 virtual memory 479, 480 Geo 292 geo distance aggregations 313, 314 geo_field properties 357 geohash grid aggregation about 315 URL 315 GitHub automatic store throttling, URL 494 URL 411 global aggregation 315, 316 Groovy URL 230 H hardware preparations, for running Elasticsearch about 473 cloud 474, 475 cost cutting 477 CPU 475 mass storage 476 network 476 physical servers 474, 475 RAM memory 475 servers counting 476 HDFS URL 423 highlighted fragments controlling 175 highlighter type selecting 172, 173 highlighting about 169, 170 Apache Lucene, using 172 custom query 179, 180 field configuration 172 global settings 175, 176 highlighter type, selecting 172, 173 HTML tags,, configuring 173, 175 local settings 175, 176 matching need 176-178 Postings highlighter 180-183 using 170, 171 horizontal expansion about 483-485 continues upgrades 488 cost and performance flexibility 488 designated nodes roles for larger clusters 490 high availability 486, 487 multiple Elasticsearch instances, on single physical machine 489 redundancy 486, 487 reference 487 replicas, automatic creation 486 HTTP module properties, URL 399 [ 512 ] HTTP transport settings, adjusting HTTP, disabling 398 HTTP host 399 HTTP port 398 node 398 HyperLogLog++ algorithm URL 283 I identifiers query 129 index about segments speeding up, batch indexing used 80 structure, modifying, with update API 221 index alias about 465 and routing 470 and zero downtime reindexing 470 commands, combining 467 creating 466 defining 466 filtering 469 modifying 467 removing 469 retrieving 468, 469 indexation indexing related advices about 492 automatic store throttling 494 bulk indexing 497, 498 data distribution 495-497 index refresh rate 493 multiple data paths 495 RAM buffer, used for indexing 498 thread pools, tuning 493 time-based data, handling 494 index structure mapping about 61, 62 core types 63 fields 63 IP address type 70 multi fields 70 token count type 71 types 62, 63 types definition 62, 63 index structure, modifying existing index fields, modifying 223, 224 mappings 222 new field, adding 222 index structure, parent-child relationship about 214 child mappings 214 children documents 215 parent document 215 parent mappings 214 index-time boosting defining, in mappings 263 using 262 indices, Elasticsearch indexing automatic creation, altering 53, 54 creating 52 deleting 55 newly created index, settings 55 indices query 141, 142 indices settings API 418, 419 indices stats API about 430 defining 432 docs 431 get 431, 432 indexing 431, 432 search 431, 432 store 431 internal fields _field_names 86 _id 86 _type 86 _uid 86 inverted index about URL J Java installing 12 URL JavaScript Object Notation (JSON) URL 8, 13 Java threads URL 482 [ 513 ] Java Virtual Machine (JVM) 17 JMeter URL 417 Joda Time library URL 307 K Kibana about 504 URL 504 L language analyzer URL 72 language detection URL 244 Levenshtein algorithm URL 122 Linux Elasticsearch, configuring as system service 20 Elasticsearch, installing 18 Logstash URL 465 Lucene Javadocs URL 229 Lucene query syntax 47, 48 M mappings about 8, 206 analyzers, using 71 configuration 56 field of existing index, modifying 223, 224 final mappings 207 index structure mapping 61 new field, adding to existing index 222, 223 sending, to Elasticsearch 207 similarity models 76 type determining mechanism 56 Marvel tool using 504 master node 392, 393 match all query 118 matching pattern, dynamic templates match 408 unmatch 408 match query about 121 Boolean match query 121, 122 match phrase prefix query 124 phrase match query 123 Maven URL 411 merge policy about 87 properties 87, 88 merge scheduler 88 metrics aggregations about 278 avg 278, 279 extended statistics 281, 282 field cardinality aggregation 283 field value statistics 281, 282 geo bounds aggregation 292 max 278, 279 278, 279 missing values 279 percentile ranks aggregation 286 percentiles aggregation 284, 285 scripted metrics aggregation 292, 293 scripts, using 280 sum 278, 279 top hits aggregation 287-291 value count aggregation 283 Microsoft Windows platform file handles, URL 17 missing query 119 more like this query 134, 136 moving avg aggregation about 341 future buckets, predicting 342 models 343 models, URL 343 URL 341 multi match query 124, 125 [ 514 ] multiple Elasticsearch instances, on single physical machine about 489 replicas, preventing on same node 489 shard, preventing on same node 489, 490 multiple indices URL 37 multiterm 193 multivalued field Mustache URL 230 N native code, using factory implementation 238, 239 native script implementation 239, 240 plugin definition 240, 241 plugin, installing 242 script, running 242 nested aggregation 323, 324 nested objects nested queries 213 score_mode property, setting 213 URL 209 using 209-213 nesting aggregations 326-329 network attached storage (NAS) 476 node about cluster name, setting 394 discovery about 392 HTTP transport settings, adjusting 398 roles 392 types 392 Zen discovery 395 node roles client node 393 configuring 394 data node 392, 393 master node 392, 393 nodes info API about 433 extensive information, returning 434 requisites 433 NoSQL URL 21 number, index structure mapping byte 67 double 68 double, URL 68 float 68 integer 67 long 67 short 67 O object indexing disabling 209 official repository URL 409 OpenJDK URL 12 optimistic locking URL 32 options, term suggester lowercase_terms 373 max_edits 373 min_word_len 374 prefix_len 374 shard_size 374 out-of-the-box analyzers keyword 72 language 72 pattern 72 simple 72 snowball 72 standard 72 stop 72 whitespace 72 P parameters, Boolean match query analyzer 121 cero_terms_query 122 fuzziness 122 lenient 122 max_expansions 122 operator 121 [ 515 ] prefix_length 122 zero_terms_query 122 parameters, fuzzy query boost 131 fuzziness 131 max_expansions 132 prefix_length 132 value 131 parameters, more like this query analyzer 135 boost 135 boost_terms 135 fields 135 include 135 in_term_freq 135 like 135 max_query_terms 135 max_word_len 135 min_doc_freq 135 minimum_should_match 135 min_word_len 135 stop_words 135 unlike 135 parameters, query string query allow_leading_wildcard 126 analyzer 126 analyze_wildcard 127 auto_generate_phrase_queries 127 boost 127 default_field 126 default_operator 126 enable_position_increments 126 fuzziness 127 fuzzy_max_expansions 126 fuzzy_prefix_length 126 lenient 127 locale 127 lowercase_expand_terms 126 max_determined_states 127 minimum_should_match 127 phrase_slop 127 query 126 time_zone 127 parameters, range query gt 133 gte 133 lt 133 lte 133 parent aggregations 330 parent-child relationship data indexing 214 index structure 214 performance considerations 221 querying 216 using 213 pattern analyzer URL 72 percolator about 345 combining, with other functionalities 353, 354 exploring 350, 351 index 346 indexed documents percolation 355 matching queries count, obtaining 354 preparing 347-349 returned results size, controlling 352 using, for and score calculation 352, 353 phrase match query analyzer 123 slop 123 phrase suggester about 374, 375 configuration 376 pipeline aggregations about 330 data, gaps 330 other aggregations, referencing 330 parent aggregation family 330 sibling aggregation family 330 types 330, 331 URL 330 pipeline aggregations, types average bucket aggregations 331, 332 bucket script aggregation 336, 337 bucket selector aggregation 334, 335 cumulative sum aggregation 333, 334 [ 516 ] derivative aggregation 340 max_bucket 331, 332 min_bucket 331, 332 moving avg aggregation 341 serial differencing aggregation 338-340 sum_bucket 331, 332 plugins about 408 basics 409 installing 409, 411 removing 411 PostingsHighlighter about 180-182 URL 172 prefix query 129 Q queries selecting, for warming 464, 465 query boosts about 250 adding, to queries 250-253 applying, to document 250 score, modifying 254 used, for influencing scores 250 querying process about 111 data, in child documents 216-218 data, in parent documents 219, 220 query logic 111, 112 search execution preference, specifying 113, 114 search shards API, specifying 114-116 search type, specifying 112 query parser URL 48 query rewrite about 193 Apache Lucene, using 195-197 prefix query, example 193, 194 properties 197-199 query string query about 125, 126 running, against multiple fields 128 R Rackspace URL 488 RAID URL 476 range aggregation about 301, 302 keyed buckets 303 range query 133 recovery process about 400 delayed allocation 403, 404 gateway recovery options 401 index recovery prioritization 404 indices recovery API 401, 403 regular expression query about 134 URL 134 replicas, Elasticsearch indexing about 50, 51 write consistency, controlling 52 REST API about 21, 22 data, storing in Elasticsearch 22 documents, deleting 31 documents, retrieving 25, 26 documents, updating 26, 27 URL 22 used, for data manipulation 21 versioning 32 results explicit filtering, bool query used 165-169 filtering 164 query context 165 reverse nested aggregation 324, 325 rewrite property, values constant_score 197 constant_score_boolean 197 scoring_boolean 197 top_terms 198 top_terms_blended freqs 198 top_terms_boost_N 198 right query results, limiting to given tags 152 selecting 151 [ 517 ] use cases 152 values in range, searching 152 routing about 89-93 default indexing 90 default searching 90, 91 fields 94, 95 parameters 93, 94 RPM package used, for installing Elasticsearch 18 S sample bounding box filtering 360-362 distance-based sorting 358, 360 distance, limiting 362 sampler aggregation 321, 322 score about 227 influencing, with query boosts 250 modifying 254 score_mode parameter about 257 avg value 257 first value 257 max value 257 value 257 multiple value 257 sum value 257 score, modifying about 254 boosting query 255 constant_score query 254 function score query 255 script fields parameters, passing to 110 selecting 108, 110 scripting capabilities about 230 languages, Groovy 237 native code, using 238 other than embedded languages, using 237 parameters, using 236 querying, scripts used 235 script execution, available objects 230-232 script, types 232 script properties file 235 id 235 inline 235 lang 235 params 235 script 235 scripts, scripted metrics aggregation combine_script 292 init_script 292 map_script 292 reduce_script 292 script types about 232 indexed scripts 234, 235 in file scripts 232, 233 inline scripts 232, 233 Scroll API about 388 problem definition 388 problem definition, solution 388, 389 searching 90, 91 segment merging about 86, 87 merge policy 87 merge policy, basic properties 87 merge scheduler 88 need for 87 throttling 89 shard allocation cancelling 452 forcing 452 IP address, using for 443 multiple commands per HTTP request 453 operations, allowing on primary shards 453 shard and replica allocation allocation throttling 445, 446 cluster wide allocation 446, 447 configuration 441 controlling 440 controlling, explicitly 440 index, creating 441, 442 [ 518 ] node attributes, requiring 443 node parameters, specifying 441 nodes, excluding 442 number of shards and replicas per node 445 rolling restarts, handling 453, 454 shards and replicas, moving manually 451 shard request cache about 414 configuring 414, 415 enabling 414, 415 per request shard request cache, disabling 415 usage monitoring 415 shards about 7-9, 50, 51 moving 451 write consistency, controlling 52 sibling aggregations 330 significant terms aggregation about 317, 318 multiple value, analyzing 319, 320 significant terms, selecting 319 similarity models about 76 BM25 similarity, configuring 79 default similarity, configuring 78 DFR similarity, configuring 79 IB similarity, configuring 80 information-based model 78 Okapi BM25 model 78 per-field similarity, setting 77 randomness model, divergence 78 simple query string query about 128 URL 128 single Elasticsearch node circuit, breaking 480 doc values, using 481 field data cache 480 general preparations 478 index refresh rate 481 RAM buffer, used for indexing 481 thread pools 482, 483 tuning 477 snapshots additional parameters 425 creating 424 snowball analyzer URL 72 Software as a Service (SaaS) 505 source filtering 106 span queries performance considerations 151 span 143 span containing query 150 span first query 144 span multi query 151 span near query 145, 147 span not query 148, 149 span or query 147 span term query 143 span within query 149 using 142 spatial capabilities about 355 example data 356 geo_field properties 357 mappings preparation 356 SPM tool URL 505 standard analyzer URL 72 state and health, cluster cluster health API 428 cluster state API 435 cluster stats API 436 indices recovery API 437, 438 indices segments API 439 indices shard stores API 439 indices stats API 430 monitoring 427 nodes info API 433, 434 nodes stats API 434, 435 pending tasks API 436 status code definition URL 84 stemming URL 73 stop analyzer URL 72 [ 519 ] stop words URL 119 suggesters freq property 372 response 371, 372 score property 372 suggestions, including 370 text property 372 types 369 URL 369, 374 using 369 synonym rules Apache Solr synonyms, using 265 defining 265 WordNet synonyms, using 267 synonyms about 263 filtering 263 index-time synonyms expansion 267 in mappings 264 query-time synonym expansion 267 rules, defining 265 storing, in filesystem 265 synonyms filter using 263 system-specific installation and configuration about 18 Elasticsearch, configuring as system service on Linux 20 Elasticsearch, installing on Linux 18 Elasticsearch, using as system service on Windows 20 T T-Digest algorithm URL 284 templates about 405 example 405, 406 term query 116 terms aggregation about 298, 299 approximate counts 299 minimum document count 300 terms query 117 term suggester about 372 configuration options 373 options 373, 374 thread pools about 482 bulk 482 generic 482 get 482 index 482 percolate 482 search 482 suggest 482 throttling 89 time zones URL 313 tree-like structures analysis 203, 204 data structure 202 indexing 201 type determining mechanism about 56 disabling 57, 58 tuning, for dates 59-61 tuning, for numeric types 58, 59 type property, values fvh 173 plain 172 postins 173 type query 118 types, suggesters completion 369, 376 context 369, 381 phrase 369, 374 term 369, 372 U Unicast URL 392 update API used, for modifying index structure 221 update settings API about 417 cluster settings API 418 indices settings API 418, 419 [ 520 ] URI query string parameters about 41 analyzer property 42 analyze_wildcard property 47 default operator 42 default search field 42 explain parameter 42, 43 fields returned 45 lowercasing terms expansion 46 per shard results, limiting 46 prefix queries analysis 47 query 42 results, sorting 45 results window 46 search timeout 45 search type 46 unavailable indices, ignoring 46 wildcard queries analysis 47 URI request query analyzing 40, 41 Lucene query syntax 47, 48 parameters 41 sample data 34 URI search 35-37 used, for searching 34 URI search about 35, 37 Elasticsearch query response 38, 39 URL 47 V Validate API using 183-186 values, has_child query parameter avg 217 max 217 217 none 217 sum 217 values, in range lower scoring partial queries, ignoring 154-156 Lucene query syntax, using in queries 157 matched documents, boosting 153 prefixes, used for providing autocomplete functionality 159 searching 152 similar terms, finding 160 spans 160-162 user queries without errors, handling 157-159 values, score_mode property avg 213 max 213 213 none 213 sum 213 versioning about 32 from external system 33 usage example 32, 33 vertical scaling 477 W warming query about 460 defined warming queries, retrieving 462, 463 defining 461, 462 deleting 463 warming up functionality, disabling 464 wildcard query 132 Windows Elasticsearch, configuring as system service 20 WordNet URL 267 Z Zen discovery about 395 cluster state updates control 397 fault detection ping settings 397 master election configuration 395, 396 master unavailability, dealing with 398 unicast, configuring 396 [ 521 ] Thank you for buying Elasticsearch Server Third Edition About Packt Publishing Packt, pronounced 'packed', published its first book, Mastering phpMyAdmin for Effective MySQL Management, in April 2004, and subsequently continued to specialize in publishing highly focused books on specific technologies and solutions Our books and publications share the experiences of your fellow IT professionals in adapting and customizing today's systems, applications, and frameworks Our solution-based books give you the knowledge and power to customize the software and technologies you're using to get the job done Packt books are more specific and less general than 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Mobile ArcGIS Server Applications with JavaScript ISBN: 978-1-84969-796-5 Paperback: 274 pages Master the ArcGIS API for JavaScript, and build exciting, custom web and mobile GIS applications with the ArcGIS Server Develop ArcGIS Server applications with JavaScript, both for traditional web browsers as well as the mobile platform Acquire in-demand GIS skills sought by many employers Step-by-step instructions, examples, and handson practice designed to help you learn the key features and design considerations for building custom ArcGIS Server applications Please check www.PacktPub.com for information on our titles