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Elasticsearch Server: Second Edition

4.3 (13)

Elasticsearch Server: Second Edition

4.3 (13)

Overview of this book

Elasticsearch Server Second Edition

Elasticsearch Server Second Edition

Credits

Credits

About the Author

About the Author

Acknowledgments

Acknowledgments

About the Author

About the Author

Acknowledgments

Acknowledgments

About the Reviewers

About the Reviewers

www.PacktPub.com

www.PacktPub.com

Preface

Preface

Free Chapter

Getting Started with the Elasticsearch Cluster

Getting Started with the Elasticsearch Cluster

Full-text searching

The basics of Elasticsearch

Installing and configuring your cluster

Manipulating data with the REST API

Searching with the URI request query

Summary

Indexing Your Data

Indexing Your Data

Elasticsearch indexing

Mappings configuration

Batch indexing to speed up your indexing process

Extending your index structure with additional internal information

Introduction to segment merging

Introduction to routing

Summary

Searching Your Data

Searching Your Data

Querying Elasticsearch

Understanding the querying process

Basic queries

Compound queries

Filtering your results

Highlighting

Validating your queries

Sorting data

Query rewrite

Summary

Extending Your Index Structure

Extending Your Index Structure

Indexing tree-like structures

Indexing data that is not flat

Using nested objects

Using the parent-child relationship

Modifying your index structure with the update API

Summary

Make Your Search Better

Make Your Search Better

An introduction to Apache Lucene scoring

Scripting capabilities of Elasticsearch

Searching content in different languages

Influencing scores with query boosts

When does index-time boosting make sense?

Words with the same meaning

Understanding the explain information

Summary

Beyond Full-text Searching

Beyond Full-text Searching

Aggregations

Faceting

Using suggesters

Percolator

Handling files

Geo

The scroll API

The terms filter

Summary

Elasticsearch Cluster in Detail

Elasticsearch Cluster in Detail

Node discovery

The gateway and recovery modules

Preparing Elasticsearch cluster for high query and indexing throughput

Templates and dynamic templates

Summary

Administrating Your Cluster

Administrating Your Cluster

The Elasticsearch time machine

Monitoring your cluster's state and health

Controlling cluster rebalancing

Controlling the shard and replica allocation

Warming up

Index aliasing and using it to simplify your everyday work

Elasticsearch plugins

The update settings API

Summary

Index

Index

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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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