Mastering elasticsearch : further your knowledge of the elasticsearch server by learning more about its internals, querying, and data handling

Mastering elasticsearch further your knowledge of the elasticsearch server by learning more about its internals, querying, and data handling

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.

Detalles Bibliográficos
Otros Autores: Kuc, Rafał, author (author), Rogozinski, Marek, author (editor), Hussain, Akram, editor, Youe, Rebecca, editor, Srivastava, Stuti, editor, Siddiqui, Sameen, editor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham, England ; Mumbai, [India] : Packt Publishing 2015.
Edición:2nd ed
Colección:Community experience distilled.
Materias:
Application software > Development.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630160306719
Tabla de Contenidos:
  • Cover; Copyright; Credits; About the Author; Acknowledgments; About the Author; Acknowledgments; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to Elasticsearch; Introducing Apache Lucene; Getting familiar with Lucene; Overall architecture; Getting deeper into Lucene index; 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; Type; Mapping; Node; Cluster; Shard; Replica
  • Key concepts behind Elasticsearch architectureWorkings of Elasticsearch; The startup process; Failure detection; Communicating with Elasticsearch; Indexing data; Querying data; The story; Summary; Chapter 2: Power User Query DSL; Default Apache Lucene scoring explained; When a document is matched; TF/IDF scoring formula; Lucene conceptual scoring formula; Lucene practical scoring formula; Elasticsearch point of view; An example; Query rewrite explained; Prefix query as an example ; Getting back to Apache Lucene; Query rewrite properties; Query templates; Introducing query templates
  • Templates as stringsThe Mustache template engine; Conditional expressions; Loops; Default values; Storing templates in files; Handling filters and why it matters; Filters and query relevance; How filters work; Bool or and/or/not filters; Performance considerations; Post filtering and filtered query; Choosing the right filtering method ; Choosing the right query for the job; Query categorization; Basic queries; Compound queries; Not analyzed queries; Full text search queries; Pattern queries; Similarity supporting queries; Score altering queries; Position aware queries
  • Structure aware queries The use cases; Example data; Basic queries use cases; Compound queries use cases; Not analyzed queries use cases; Full text search queries use cases; Pattern queries use cases; Similarity supporting queries use cases; Score altering queries use cases; Pattern queries use cases; Structure aware queries use cases; Summary; Chapter 3: Not Only Full Text Search; Query rescoring; What is query rescoring?; An example query; Structure of the rescore query; Rescore parameters; Choosing the scoring mode; To sum up; Controlling multimatching; Multimatch types
  • Best fields matchingCross fields matching; Most fields matching; Phrase matching; Phrase with prefixes matching; Significant terms aggregation; An example; Choosing significant terms; Multiple values analysis; Significant terms aggregation and full text search fields; Additional configuration options; Controlling the number of returned buckets; Background set filtering; Minimum document count; Execution hint; More options; There are limits; Memory consumption; Shouldn't be used as top level aggregation; Counts are approximated; Floating point fields are not allowed; Documents grouping
  • Top hits aggregation

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