Elasticsearch indexing :: improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! /
Annotation
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Birmingham :
Packt Publishing,
2015.
|
Schriftenreihe: | Community experience distilled.
|
Schlagworte: | |
Online-Zugang: | Volltext |
Zusammenfassung: | Annotation |
Beschreibung: | Includes index. |
Beschreibung: | 1 online resource : illustrations |
ISBN: | 9781783987030 1783987030 1783987022 9781783987023 |
Internformat
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520 | 8 | |a Annotation |b Improve search experiences with ElasticSearch's powerful indexing functionality learn how with this practical ElasticSearch tutorial, packed with tips!About This Book Improve user's search experience with the correct configuration Deliver relevant search results fast! Save time and system resources by creating stable clustersWho This Book Is ForIf you understand the importance of a great search experience this book will show you exactly how to build one with ElasticSearch, one of the world's leading search servers. What You Will Learn Learn how ElasticSearch efficiently stores data and find out how it can reduce costs Control document metadata with the correct mapping strategies and by configuring indices Use ElasticSearch analysis and analyzers to incorporate greater intelligence and organization across your documents and data Find out how an ElasticSearch cluster works and learn the best way to configure it Perform high-speed indexing with low system resource cost Improve query relevance with appropriate mapping, suggest API, and other ElasticSearch functionalitiesIn DetailBeginning with an overview of the way ElasticSearch stores data, you'll begin to extend your knowledge to tackle indexing and mapping, and learn how to configure ElasticSearch to meet your users' needs. You'll then find out how to use analysis and analyzers for greater intelligence in how you organize and pull up search results to guarantee that every search query is met with the relevant results! You'll explore the anatomy of an ElasticSearch cluster, and learn how to set up configurations that give you optimum availability as well as scalability. Once you've learned how these elements work, you'll find real-world solutions to help you improve indexing performance, as well as tips and guidance on safety so you can back up and restore data. Once you've learned each component outlined throughout, you will be confident that you can help to deliver an improved search experience exactly what modern users demand and expect. Style and approachThis is a comprehensive guide to performing efficient indexing and providing relevant search results using mapping, analyzers, and other ElasticSearch functionalities. | |
505 | 0 | |a Cover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to Efficient Indexing; Getting started; Understanding the document storage strategy; The _source field; The difference between the storable and searchable field; Analysis; Summary; Chapter 2: What is an Elasticsearch Index; Nature of the Elasticsearch index; Indices; Mapping; Types; Document; Denormalization; Inverted index; Summary; Chapter 3: Basic Concepts of Mapping; Basic concepts and definitions; Metadata fields; _source; _all; _timestamp; _ttl; Types. | |
505 | 8 | |a Object typeRoot object type; Attachment type; The relationship between mapping and relevant search results; Understanding the schema-less; Summary; Chapter 4: Analysis and Analyzers; Introducing analysis; Process of analysis; Built-in analyzers; Building blocks of Analyzer; Character filters; HTML Strip Char filter; Pattern Replace Char filter; Tokenizer; Token filters; What's text normalization?; ICU analysis plugin; ASCII Folding Token filter; An Analyzer pPipeline; Specifying the analyzer for a field in the mapping; Creating a custom analyzer; Summary. | |
505 | 8 | |a Chapter 5: Anatomy of an Elasticsearch ClusterBasic concepts; Node; Non-data nodes; Dedicated master nodes; Client nodes; Tribe node; Shards; Replicas; Explaining the architecture of distribution; Correctly configuring the cluster; Choosing the right amount of shards and replicas; Summary; Chapter 6: Improving Indexing Performance; Configuration; Memory configuration; The ES_HEAP_SIZE environment variable; Avoiding swapping; Mlockall property; Garbage collector; The structure of JVM memory; What is the problem?; Monitoring garbage collection; VisualVM. | |
505 | 8 | |a Different strategies among garbage collectorsProcess of deallocating memory; Types of garbage collector; File descriptors; Increasing FD limit on Unix systems; Optimization of mapping definition; Norms; Feature index_option of string type; Exclude unnecessary fields; Extension of the automatic index refresh time; Segments and merging policies; Choosing the right merge policy; Tiered policy; log_byte_size policy; Log_doc policy; The optimize API; Store module; Store types; Simple filesystem store; New IO filesystem store; MMap filesystem store; Hybrid filesystem store. | |
505 | 8 | |a Throttling I/O operationsThrottling type; Bulk API; Bulk sizing; Notes; Summary; Chapter 7: Snapshot and Restore; Snapshot repository; Repository types; Shared filesystem repository; URL repository; Cloud repository; HDFS filesystem repository; Snapshot; Restore; Overriding index settings during restore; How does the snapshot process works?; Summary; Chapter 8: Improving the User Search Experience; Correction of users' spelling mistakes; Suggesters; Using the _suggest REST endpoint; Suggest object inclusion in the query; Term suggester; Configuring the term suggester; The phrase suggester. | |
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contents | Cover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to Efficient Indexing; Getting started; Understanding the document storage strategy; The _source field; The difference between the storable and searchable field; Analysis; Summary; Chapter 2: What is an Elasticsearch Index; Nature of the Elasticsearch index; Indices; Mapping; Types; Document; Denormalization; Inverted index; Summary; Chapter 3: Basic Concepts of Mapping; Basic concepts and definitions; Metadata fields; _source; _all; _timestamp; _ttl; Types. Object typeRoot object type; Attachment type; The relationship between mapping and relevant search results; Understanding the schema-less; Summary; Chapter 4: Analysis and Analyzers; Introducing analysis; Process of analysis; Built-in analyzers; Building blocks of Analyzer; Character filters; HTML Strip Char filter; Pattern Replace Char filter; Tokenizer; Token filters; What's text normalization?; ICU analysis plugin; ASCII Folding Token filter; An Analyzer pPipeline; Specifying the analyzer for a field in the mapping; Creating a custom analyzer; Summary. Chapter 5: Anatomy of an Elasticsearch ClusterBasic concepts; Node; Non-data nodes; Dedicated master nodes; Client nodes; Tribe node; Shards; Replicas; Explaining the architecture of distribution; Correctly configuring the cluster; Choosing the right amount of shards and replicas; Summary; Chapter 6: Improving Indexing Performance; Configuration; Memory configuration; The ES_HEAP_SIZE environment variable; Avoiding swapping; Mlockall property; Garbage collector; The structure of JVM memory; What is the problem?; Monitoring garbage collection; VisualVM. Different strategies among garbage collectorsProcess of deallocating memory; Types of garbage collector; File descriptors; Increasing FD limit on Unix systems; Optimization of mapping definition; Norms; Feature index_option of string type; Exclude unnecessary fields; Extension of the automatic index refresh time; Segments and merging policies; Choosing the right merge policy; Tiered policy; log_byte_size policy; Log_doc policy; The optimize API; Store module; Store types; Simple filesystem store; New IO filesystem store; MMap filesystem store; Hybrid filesystem store. Throttling I/O operationsThrottling type; Bulk API; Bulk sizing; Notes; Summary; Chapter 7: Snapshot and Restore; Snapshot repository; Repository types; Shared filesystem repository; URL repository; Cloud repository; HDFS filesystem repository; Snapshot; Restore; Overriding index settings during restore; How does the snapshot process works?; Summary; Chapter 8: Improving the User Search Experience; Correction of users' spelling mistakes; Suggesters; Using the _suggest REST endpoint; Suggest object inclusion in the query; Term suggester; Configuring the term suggester; The phrase suggester. |
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dewey-search | 651.5 |
dewey-sort | 3651.5 |
dewey-tens | 650 - Management and auxiliary services |
discipline | Wirtschaftswissenschaften |
format | Electronic eBook |
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indexdate | 2024-11-27T13:27:00Z |
institution | BVB |
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language | English |
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series | Community experience distilled. |
series2 | Community experience distilled |
spelling | Akdoğan, Hüseyin, author. http://id.loc.gov/authorities/names/no2012001398 Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / Hüseyin Akdoǧan. Birmingham : Packt Publishing, 2015. 1 online resource : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file Community experience distilled Online resource; title from PDF title page (EBSCO, viewed May 3, 2016). Includes index. Annotation Improve search experiences with ElasticSearch's powerful indexing functionality learn how with this practical ElasticSearch tutorial, packed with tips!About This Book Improve user's search experience with the correct configuration Deliver relevant search results fast! Save time and system resources by creating stable clustersWho This Book Is ForIf you understand the importance of a great search experience this book will show you exactly how to build one with ElasticSearch, one of the world's leading search servers. What You Will Learn Learn how ElasticSearch efficiently stores data and find out how it can reduce costs Control document metadata with the correct mapping strategies and by configuring indices Use ElasticSearch analysis and analyzers to incorporate greater intelligence and organization across your documents and data Find out how an ElasticSearch cluster works and learn the best way to configure it Perform high-speed indexing with low system resource cost Improve query relevance with appropriate mapping, suggest API, and other ElasticSearch functionalitiesIn DetailBeginning with an overview of the way ElasticSearch stores data, you'll begin to extend your knowledge to tackle indexing and mapping, and learn how to configure ElasticSearch to meet your users' needs. You'll then find out how to use analysis and analyzers for greater intelligence in how you organize and pull up search results to guarantee that every search query is met with the relevant results! You'll explore the anatomy of an ElasticSearch cluster, and learn how to set up configurations that give you optimum availability as well as scalability. Once you've learned how these elements work, you'll find real-world solutions to help you improve indexing performance, as well as tips and guidance on safety so you can back up and restore data. Once you've learned each component outlined throughout, you will be confident that you can help to deliver an improved search experience exactly what modern users demand and expect. Style and approachThis is a comprehensive guide to performing efficient indexing and providing relevant search results using mapping, analyzers, and other ElasticSearch functionalities. Cover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to Efficient Indexing; Getting started; Understanding the document storage strategy; The _source field; The difference between the storable and searchable field; Analysis; Summary; Chapter 2: What is an Elasticsearch Index; Nature of the Elasticsearch index; Indices; Mapping; Types; Document; Denormalization; Inverted index; Summary; Chapter 3: Basic Concepts of Mapping; Basic concepts and definitions; Metadata fields; _source; _all; _timestamp; _ttl; Types. Object typeRoot object type; Attachment type; The relationship between mapping and relevant search results; Understanding the schema-less; Summary; Chapter 4: Analysis and Analyzers; Introducing analysis; Process of analysis; Built-in analyzers; Building blocks of Analyzer; Character filters; HTML Strip Char filter; Pattern Replace Char filter; Tokenizer; Token filters; What's text normalization?; ICU analysis plugin; ASCII Folding Token filter; An Analyzer pPipeline; Specifying the analyzer for a field in the mapping; Creating a custom analyzer; Summary. Chapter 5: Anatomy of an Elasticsearch ClusterBasic concepts; Node; Non-data nodes; Dedicated master nodes; Client nodes; Tribe node; Shards; Replicas; Explaining the architecture of distribution; Correctly configuring the cluster; Choosing the right amount of shards and replicas; Summary; Chapter 6: Improving Indexing Performance; Configuration; Memory configuration; The ES_HEAP_SIZE environment variable; Avoiding swapping; Mlockall property; Garbage collector; The structure of JVM memory; What is the problem?; Monitoring garbage collection; VisualVM. Different strategies among garbage collectorsProcess of deallocating memory; Types of garbage collector; File descriptors; Increasing FD limit on Unix systems; Optimization of mapping definition; Norms; Feature index_option of string type; Exclude unnecessary fields; Extension of the automatic index refresh time; Segments and merging policies; Choosing the right merge policy; Tiered policy; log_byte_size policy; Log_doc policy; The optimize API; Store module; Store types; Simple filesystem store; New IO filesystem store; MMap filesystem store; Hybrid filesystem store. Throttling I/O operationsThrottling type; Bulk API; Bulk sizing; Notes; Summary; Chapter 7: Snapshot and Restore; Snapshot repository; Repository types; Shared filesystem repository; URL repository; Cloud repository; HDFS filesystem repository; Snapshot; Restore; Overriding index settings during restore; How does the snapshot process works?; Summary; Chapter 8: Improving the User Search Experience; Correction of users' spelling mistakes; Suggesters; Using the _suggest REST endpoint; Suggest object inclusion in the query; Term suggester; Configuring the term suggester; The phrase suggester. Indexing. http://id.loc.gov/authorities/subjects/sh85064867 Business records Management. Indexation (Documentation) Gestion des documents. BUSINESS & ECONOMICS General. bisacsh Business records Management fast Indexing fast has work: Elasticsearch indexing (Text) https://id.oclc.org/worldcat/entity/E39PCH6qR6BD96pBdpKKYVhfv3 https://id.oclc.org/worldcat/ontology/hasWork Print version: Akdoğan, Hüseyin. Elasticsearch Indexing. Birmingham : Packt Publishing, ©2015 Community experience distilled. http://id.loc.gov/authorities/names/no2011030603 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1134876 Volltext |
spellingShingle | Akdoğan, Hüseyin Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / Community experience distilled. Cover; Copyright; Credits; About the Author; About the Reviewer; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Introduction to Efficient Indexing; Getting started; Understanding the document storage strategy; The _source field; The difference between the storable and searchable field; Analysis; Summary; Chapter 2: What is an Elasticsearch Index; Nature of the Elasticsearch index; Indices; Mapping; Types; Document; Denormalization; Inverted index; Summary; Chapter 3: Basic Concepts of Mapping; Basic concepts and definitions; Metadata fields; _source; _all; _timestamp; _ttl; Types. Object typeRoot object type; Attachment type; The relationship between mapping and relevant search results; Understanding the schema-less; Summary; Chapter 4: Analysis and Analyzers; Introducing analysis; Process of analysis; Built-in analyzers; Building blocks of Analyzer; Character filters; HTML Strip Char filter; Pattern Replace Char filter; Tokenizer; Token filters; What's text normalization?; ICU analysis plugin; ASCII Folding Token filter; An Analyzer pPipeline; Specifying the analyzer for a field in the mapping; Creating a custom analyzer; Summary. Chapter 5: Anatomy of an Elasticsearch ClusterBasic concepts; Node; Non-data nodes; Dedicated master nodes; Client nodes; Tribe node; Shards; Replicas; Explaining the architecture of distribution; Correctly configuring the cluster; Choosing the right amount of shards and replicas; Summary; Chapter 6: Improving Indexing Performance; Configuration; Memory configuration; The ES_HEAP_SIZE environment variable; Avoiding swapping; Mlockall property; Garbage collector; The structure of JVM memory; What is the problem?; Monitoring garbage collection; VisualVM. Different strategies among garbage collectorsProcess of deallocating memory; Types of garbage collector; File descriptors; Increasing FD limit on Unix systems; Optimization of mapping definition; Norms; Feature index_option of string type; Exclude unnecessary fields; Extension of the automatic index refresh time; Segments and merging policies; Choosing the right merge policy; Tiered policy; log_byte_size policy; Log_doc policy; The optimize API; Store module; Store types; Simple filesystem store; New IO filesystem store; MMap filesystem store; Hybrid filesystem store. Throttling I/O operationsThrottling type; Bulk API; Bulk sizing; Notes; Summary; Chapter 7: Snapshot and Restore; Snapshot repository; Repository types; Shared filesystem repository; URL repository; Cloud repository; HDFS filesystem repository; Snapshot; Restore; Overriding index settings during restore; How does the snapshot process works?; Summary; Chapter 8: Improving the User Search Experience; Correction of users' spelling mistakes; Suggesters; Using the _suggest REST endpoint; Suggest object inclusion in the query; Term suggester; Configuring the term suggester; The phrase suggester. Indexing. http://id.loc.gov/authorities/subjects/sh85064867 Business records Management. Indexation (Documentation) Gestion des documents. BUSINESS & ECONOMICS General. bisacsh Business records Management fast Indexing fast |
subject_GND | http://id.loc.gov/authorities/subjects/sh85064867 |
title | Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / |
title_auth | Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / |
title_exact_search | Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / |
title_full | Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / Hüseyin Akdoǧan. |
title_fullStr | Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / Hüseyin Akdoǧan. |
title_full_unstemmed | Elasticsearch indexing : improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / Hüseyin Akdoǧan. |
title_short | Elasticsearch indexing : |
title_sort | elasticsearch indexing improve search experiences with elasticsearch s powerful indexing functionality learn how with this practical elasticsearch tutorial packed with tips |
title_sub | improve search experiences with Elasticsearch's powerful indexing functionality--learn how with this practical Elasticsearch tutorial packed with tips! / |
topic | Indexing. http://id.loc.gov/authorities/subjects/sh85064867 Business records Management. Indexation (Documentation) Gestion des documents. BUSINESS & ECONOMICS General. bisacsh Business records Management fast Indexing fast |
topic_facet | Indexing. Business records Management. Indexation (Documentation) Gestion des documents. BUSINESS & ECONOMICS General. Business records Management Indexing |
url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1134876 |
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