Mastering ElasticSearch : extend your knowledge on ElasticSearch, and querying and data handing, along with its internal workings /

A practical tutorial that covers the difficult design, implementation, and management of search solutions. Mastering ElasticSearch is aimed at to intermediate users who want to extend their knowledge about ElasticSearch. The topics that are described in the book are detailed, but we assume that you...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Kuć, Rafal
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, ©2013.
Colección:Community experience distilled
Temas:
Open source software.
Logiciels libres.
COMPUTERS > Operating Systems > DOS.
COMPUTERS > Operating Systems > Macintosh.
COMPUTERS > Operating Systems > Windows Server & NT.
COMPUTERS > Operating Systems > Windows Workstation.
COMPUTERS > System Administration > Windows Administration.
COMPUTERS > General.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Copyright
  • Credits
  • About the Authors
  • About the Reviewers
  • www.PacktPub.com
  • Table of Contents
  • Preface
  • Chapter 1: Introduction to ElasticSearch
  • Introducing Apache Lucene
  • Getting familiar with Lucene
  • Overall architecture
  • Analyzing your data
  • Indexing and querying
  • Lucene query language
  • Understanding the basics
  • Querying fields
  • Term modifiers
  • Handling special characters
  • Introducing ElasticSearch
  • Basic concepts
  • Index
  • Document
  • Mapping
  • Type
  • Node
  • Cluster
  • Shard
  • Replica
  • GatewayKey concepts behind ElasticSearch architecture
  • Working of ElasticSearch
  • Boostrap process
  • Failure detection
  • Communicating with ElasticSearch
  • Summary
  • Chapter 2: Power User Query DSL
  • Default Apache Lucene scoring explained
  • When a document is matched
  • TF/IDF scoring formula
  • Lucene conceptual formula
  • Lucene practical formula
  • ElasticSearch point of view
  • Query rewrite explained
  • Prefix query as an example
  • Getting back to Apache Lucene
  • Query rewrite properties
  • Rescore
  • Understanding rescore
  • Example DataQuery
  • Structure of the rescore query
  • Rescore parameters
  • To sum up
  • Bulk Operations
  • MultiGet
  • MultiSearch
  • Sorting data
  • Sorting with multivalued fields
  • Sorting with multivalued geo fields
  • Sorting with nested objects
  • Update API
  • Simple field update
  • Conditional modifications using scripting
  • Creating and deleting documents using Update API
  • Using filters to optimize your queries
  • Filters and caching
  • Not all filters are cached by default
  • Changing ElasticSearch caching behavior
  • Why bother naming the key for the cache?When to change ElasticSearch filter caching behavior
  • Terms lookup filter
  • How does it work?
  • Performance considerations
  • Loading terms from inner objects
  • Terms lookup filter cache settings
  • Filter and scopes in ElasticSearch faceting mechanism
  • Example data
  • Faceting and filtering
  • Filter as a part of the query
  • Facet filter
  • Global scope
  • Summary
  • Chapter 3: Low-level Index Control
  • Altering Apache Lucene scoring
  • Available similarity models
  • Setting per-field similarity
  • Similarity model configurationChoosing the default similarity model
  • Configuring the chosen similarity models
  • Configuring TF/IDF similarity
  • Configuring Okapi BM25 similarity
  • Configuring DFR similarity
  • Configuring IB similarity
  • Using codecs
  • Simple use case
  • Let's see how it works
  • Available posting formats
  • Configuring the codec behavior
  • Default codec properties
  • Direct codec properties
  • Memory codec properties
  • Pulsing codec properties
  • Bloom filter based codec properties
  • NRT, flush, refresh, and transaction log

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