Elasticsearch Server - Third Edition.

Leverage Elasticsearch to create a robust, fast, and flexible search solution with easeAbout This Book Boost the searching capabilities of your system through synonyms, multilingual data handling, nested objects and parent-child documents Deep dive into the world of data aggregation and data analysi...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Kuc, Rafal (Autor), Rogozinski, Marek (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited Feb. 2016.
Edición:3rd ed.
Temas:
Application software.
Application software > Development.
Client/server computing.
Web site > Design.
Electronic information resource searching.
Logiciels d'application.
Logiciels d'application > Développement.
Architecture client-serveur (Informatique)
Recherche de l'information électronique.
COMPUTERS > Data Processing.
COMPUTERS > Programming > Object Oriented.
Application software
Application software > Development
Client/server computing
Electronic information resource searching
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Copyright
  • Credits
  • About the Authors
  • About the Reviewer
  • www.PacktPub.com
  • 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
  • Index
  • Document
  • Document type
  • Mapping
  • 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
  • Manipulating data with the REST API
  • Understanding the REST API
  • Storing data in Elasticsearch
  • Creating a new document
  • Retrieving documents
  • Updating documents
  • Dealing with non-existing documents
  • Adding partial documents
  • Deleting documents
  • Versioning
  • Usage example
  • Versioning from external systems
  • Searching with the URI request query
  • Sample data
  • URI search
  • Elasticsearch query response
  • Query analysis
  • URI query string parameters
  • The query
  • The default search field
  • Analyzer
  • The default operator property
  • Query explanation
  • The fields returned
  • Sorting the results
  • The search timeout
  • The results window
  • Limiting per-shard results
  • Ignoring unavailable indices
  • The search type
  • Lowercasing term expansion
  • Wildcard and prefix analysis
  • Lucene query syntax
  • Summary
  • Chapter 2: Indexing Your Data.
  • Elasticsearch indexing
  • Shards and replicas
  • Write consistency
  • Creating indices
  • Altering automatic index creation
  • Settings for a newly created index
  • Index deletion
  • Mappings configuration
  • Type determining mechanism
  • Disabling the type determining mechanism
  • Tuning the type determining mechanism for numeric types
  • Tuning the type determining mechanism for dates
  • Index structure mapping
  • Type and types definition
  • Fields
  • Core types
  • Multi fields
  • The IP address type
  • Token count type
  • Using analyzers
  • Out-of-the-box analyzers
  • Defining your own analyzers
  • Default analyzers
  • Different similarity models
  • Setting per-field similarity
  • Available similarity models
  • Batch indexing to speed up your indexing process
  • Preparing data for bulk indexing
  • Indexing the data
  • The _all field
  • The _source field
  • Additional internal fields
  • Introduction to segment merging
  • Segment merging
  • The need for segment merging
  • The merge policy
  • The merge scheduler
  • Throttling
  • Introduction to routing
  • Default indexing
  • Default searching
  • Routing
  • The routing parameters
  • Routing fields
  • Summary
  • Chapter 3: Searching Your Data
  • Querying Elasticsearch
  • The example data
  • A simple query
  • Paging and result size
  • Returning the version value
  • Limiting the score
  • Choosing the fields that we want to return
  • Source filtering
  • Using the script fields
  • Passing parameters to the script fields
  • Understanding the querying process
  • Query logic
  • Search type
  • Search execution preference
  • Search shards API
  • Basic queries
  • The term query
  • The terms query
  • The match all query
  • The type query
  • The exists query
  • The missing query
  • The common terms query
  • The match query
  • The Boolean match query
  • The phrase match query
  • The match phrase prefix query.
  • The multi match query
  • The query string query
  • Running the query string query against multiple fields
  • The simple query string query
  • The identifiers query
  • The prefix query
  • The fuzzy query
  • The wildcard query
  • The range query
  • Regular expression query
  • The more like this query
  • Compound queries
  • The bool query
  • The dis_max query
  • The boosting query
  • The constant_score query
  • The indices query
  • Using span queries
  • A span
  • Span term query
  • Span first query
  • Span near query
  • Span or query
  • Span not query
  • Span within query
  • Span containing query
  • Span multi query
  • Performance considerations
  • Choosing the right query
  • The use cases
  • Limiting results to given tags
  • Searching for values in a range
  • Boosting some of the matched documents
  • Ignoring lower scoring partial queries
  • Using Lucene query syntax in queries
  • Handling user queries without errors
  • Autocomplete using prefixes
  • Finding terms similar to a given one
  • Matching phrases
  • Spans, spans everywhere
  • Summary
  • Chapter 4: Extending Your Querying Knowledge
  • Filtering your results
  • The context is the key
  • Explicit filtering with bool query
  • Highlighting
  • Getting started with highlighting
  • Field configuration
  • Under the hood
  • Forcing highlighter type
  • Configuring HTML tags
  • Controlling highlighted fragments
  • Global and local settings
  • Require matching
  • Custom highlighting query
  • The Postings highlighter
  • Validating your queries
  • Using the Validate API
  • Sorting data
  • Default sorting
  • Selecting fields used for sorting
  • Sorting mode
  • Specifying behavior for missing fields
  • Dynamic criteria
  • Calculate scoring when sorting
  • Query rewrite
  • Prefix query as an example
  • Getting back to Apache Lucene
  • Query rewrite properties
  • Summary.
  • Chapter 5: Extending Your Index Structure
  • Indexing tree-like structures
  • Data structure
  • Analysis
  • Indexing data that is not flat
  • Data
  • Objects
  • Arrays
  • Mappings
  • Final mappings
  • Sending the mappings to Elasticsearch
  • To be or not to be dynamic
  • Disabling object indexing
  • Using nested objects
  • Scoring and nested queries
  • Using the parent-child relationship
  • Index structure and data indexing
  • Child mappings
  • Parent mappings
  • The parent document
  • Child documents
  • Querying
  • Querying data in the child documents
  • Querying data in the parent documents
  • Performance considerations
  • Modifying your index structure with the update API
  • The mappings
  • Adding a new field to the existing index
  • Modifying fields of an existing index
  • Summary
  • Chapter 6: Make Your Search Better
  • Introduction to Apache Lucene scoring
  • When a document is matched
  • Default scoring formula
  • Relevancy matters
  • Scripting capabilities of Elasticsearch
  • Objects available during script execution
  • Script types
  • In file scripts
  • Inline scripts
  • Indexed scripts
  • Querying with scripts
  • Scripting with parameters
  • Script languages
  • Using other than embedded languages
  • Using native code
  • The factory implementation
  • Implementing the native script
  • The plugin definition
  • Installing the plugin
  • Running the script
  • Searching content in different languages
  • Handling languages differently
  • Handling multiple languages
  • Detecting the language of the document
  • Sample document
  • The mappings
  • Querying
  • Queries with an identified language
  • Queries with an unknown language
  • Combining queries
  • Influencing scores with query boosts
  • The boost
  • Adding the boost to queries
  • Modifying the score
  • Constant score query
  • Boosting query
  • The function score query.
  • When does index-time boosting make sense?
  • Defining boosting in the mappings
  • Words with the same meaning
  • Synonym filter
  • Synonyms in the mappings
  • Synonyms stored on the file system
  • Defining synonym rules
  • Using Apache Solr synonyms
  • Using WordNet synonyms
  • Query or index-time synonym expansion
  • Understanding the explain information
  • Understanding field analysis
  • Explaining the query
  • Summary
  • Chapter 7: Aggregations for Data Analysis
  • Aggregations
  • General query structure
  • Inside the aggregations engine
  • Aggregation types
  • Metrics aggregations
  • Minimum, maximum, average, and sum
  • Field value statistics and extended statistics
  • Value count
  • Field cardinality
  • Percentiles
  • Percentile ranks
  • Top hits aggregation
  • Geo bounds aggregation
  • Scripted metrics aggregation
  • Buckets aggregations
  • Filter aggregation
  • Filters aggregation
  • Terms aggregation
  • Range aggregation
  • Date range aggregation
  • IPv4 range aggregation
  • Missing aggregation
  • Histogram aggregation
  • Date histogram aggregation
  • Time zones
  • Geo distance aggregations
  • Geohash grid aggregation
  • Global aggregation
  • Significant terms aggregation
  • Choosing significant terms
  • Multiple value analysis
  • Sampler aggregation
  • Children aggregation
  • Nested aggregation
  • Reverse nested aggregation
  • Nesting aggregations and ordering buckets
  • Buckets ordering
  • Pipeline aggregations
  • Available types
  • Referencing other aggregations
  • Gaps in the data
  • Pipeline aggregation types
  • Summary
  • Chapter 8: Beyond Full-text Searching
  • Percolator
  • The index
  • Percolator preparation
  • Getting deeper
  • Controlling the size of returned results
  • Percolator and score calculation
  • Combining percolators with other functionalities
  • Getting the number of matching queries
  • Indexed document percolation.

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