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  • Book Overview & Buying Elasticsearch Server: Second Edition
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Elasticsearch Server: Second Edition

Elasticsearch Server: Second Edition

4.3 (13)
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Elasticsearch Server: Second Edition

Elasticsearch Server: Second Edition

4.3 (13)
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Overview of this book

Table of Contents (18 chapters)
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Elasticsearch Server Second Edition
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Elasticsearch Server Second Edition
Credits
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Credits
About the Author
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About the Author
Acknowledgments
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Acknowledgments
About the Author
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About the Author
Acknowledgments
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Acknowledgments
About the Reviewers
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About the Reviewers
www.PacktPub.com
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www.PacktPub.com
Preface
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Preface
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1
Getting Started with the Elasticsearch Cluster
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Getting Started with the Elasticsearch Cluster
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Full-text searching
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The basics of Elasticsearch
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Installing and configuring your cluster
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Manipulating data with the REST API
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Searching with the URI request query
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Summary
2
Indexing Your Data
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Indexing Your Data
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Elasticsearch indexing
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Mappings configuration
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Batch indexing to speed up your indexing process
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Extending your index structure with additional internal information
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Introduction to segment merging
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Introduction to routing
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Summary
3
Searching Your Data
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Searching Your Data
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Querying Elasticsearch
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Understanding the querying process
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Basic queries
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Compound queries
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Filtering your results
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Highlighting
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Validating your queries
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Sorting data
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Query rewrite
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Summary
4
Extending Your Index Structure
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Extending Your Index Structure
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Indexing tree-like structures
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Indexing data that is not flat
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Using nested objects
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Using the parent-child relationship
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Modifying your index structure with the update API
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Summary
5
Make Your Search Better
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Make Your Search Better
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An introduction to Apache Lucene scoring
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Scripting capabilities of Elasticsearch
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Searching content in different languages
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Influencing scores with query boosts
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When does index-time boosting make sense?
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Words with the same meaning
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Understanding the explain information
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Summary
6
Beyond Full-text Searching
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Beyond Full-text Searching
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Aggregations
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Faceting
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Using suggesters
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Percolator
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Handling files
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Geo
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The scroll API
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The terms filter
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Summary
7
Elasticsearch Cluster in Detail
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Elasticsearch Cluster in Detail
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Node discovery
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The gateway and recovery modules
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Preparing Elasticsearch cluster for high query and indexing throughput
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Templates and dynamic templates
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Summary
8
Administrating Your Cluster
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Administrating Your Cluster
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The Elasticsearch time machine
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Monitoring your cluster's state and health
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Controlling cluster rebalancing
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Controlling the shard and replica allocation
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Warming up
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Index aliasing and using it to simplify your everyday work
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Elasticsearch plugins
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The update settings API
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Summary
1
Index
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Index

Searching content in different languages

Till now, when discussing language analysis, we've talked mostly in theory. We didn't see an example regarding language analysis, handling multiple languages that our data can consist of, and so on. Now this will change, as we will discuss how we can handle data in multiple languages.

Handling languages differently

As you already know, Elasticsearch allows us to choose different analyzers for our data. We can have our data divided on the basis of whitespaces, have them lowercased, and so on. This can usually be done with the data regardless of the language—you should have the same tokenization on the basis of whitespaces for English, German, and Polish (that doesn't apply to Chinese, though). However, what if you want to find documents that contain words such as cat and cats by only sending the word cat to Elasticsearch? This is where language analysis comes into play with stemming algorithms for different languages, which allow the analyzed words to...

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Tech Concepts
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Programming languages
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