Book Image

Mastering Elasticsearch 5.x - Third Edition

Book Image

Mastering Elasticsearch 5.x - Third Edition

Overview of this book

Elasticsearch is a modern, fast, distributed, scalable, fault tolerant, and open source search and analytics engine. Elasticsearch leverages the capabilities of Apache Lucene, and provides a new level of control over how you can index and search even huge sets of data. This book will give you a brief recap of the basics and also introduce you to the new features of Elasticsearch 5. We will guide you through the intermediate and advanced functionalities of Elasticsearch, such as querying, indexing, searching, and modifying data. We’ll also explore advanced concepts, including aggregation, index control, sharding, replication, and clustering. We’ll show you the modules of monitoring and administration available in Elasticsearch, and will also cover backup and recovery. You will get an understanding of how you can scale your Elasticsearch cluster to contextualize it and improve its performance. We’ll also show you how you can create your own analysis plugin in Elasticsearch. By the end of the book, you will have all the knowledge necessary to master Elasticsearch and put it to efficient use.

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Table of Contents (20 chapters)
Mastering Elasticsearch 5.x - Third Edition
Mastering Elasticsearch 5.x - Third Edition
Credits
Credits
About the Author
About the Author
Acknowledgements
Acknowledgements
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Revisiting Elasticsearch and the Changes
Revisiting Elasticsearch and the Changes
An overview of Lucene
Introducing Elasticsearch 5.x
Summary
2
The Improved Query DSL
The Improved Query DSL
The changed default text scoring in Lucene - BM25
Re-factored Query DSL
Choosing the right query for the job
Query rewrite explained
Query templates
Summary
3
Beyond Full Text Search
Beyond Full Text Search
Controlling multimatching
Multimatch types
Controlling scores using the function score query
Built-in functions under the function score query
Query rescoring
Structure of the rescore query
Elasticsearch scripting
Painless - the new default scripting language
Lucene expressions
Summary
4
Data Modeling and Analytics
Data Modeling and Analytics
Data modeling techniques in Elasticsearch
Managing relational data in Elasticsearch
Data analytics using aggregations
Summary
5
Improving the User Search Experience
Improving the User Search Experience
Correcting user spelling mistakes
Suggesters
Implementing your own auto-completion
Working with synonyms
Summary
6
The Index Distribution Architecture
The Index Distribution Architecture
Configuring an example multi-node cluster
Choosing the right amount of shards and replicas
Routing explained
Shard allocation control
Query execution preference
Stripping data on multiple paths
Index versus type - a revised approach for creating indices
Summary
7
Low-Level Index Control
Low-Level Index Control
Altering Apache Lucene scoring
Available similarity models
Setting a per-field similarity
Similarity model configuration
Choosing the default similarity model
Choosing the right directory implementation - the store module
The store type
NRT, flush, refresh, and transaction log
Segment merging under control
Understanding Elasticsearch caching
Summary
8
Elasticsearch Administration
Elasticsearch Administration
Node types in Elasticsearch
Discovery and recovery modules
The human-friendly status API - using the cat API
Backing up
Restoring snapshots
Summary
9
Data Transformation and Federated Search
Data Transformation and Federated Search
Preprocessing data within Elasticsearch with ingest nodes
Federated search
Summary
10
Improving Performance
Improving Performance
Query validation and profiling
Very hot threads
Scaling Elasticsearch
Managing time-based indices efficiently using shrink and rollover APIs
Summary
11
Developing Elasticsearch Plugins
Developing Elasticsearch Plugins
Creating the Apache Maven project structure
Creating a custom REST action
Creating the custom analysis plugin
Summary
12
Introducing Elastic Stack 5.0
Introducing Elastic Stack 5.0
Overview of Elastic Stack 5.0
Introducing Logstash, Beats, and Kibana
Summary

Multimatch types

In this section, we will cover the different flavors of multi-match queries, which are mainly controlled using the type property. The following are the available types:

  • The best_fields type

  • The most_fields type

  • The cross_fields type

  • The phrase type

  • The phrase_prefix type

Best fields matching

To use the best_fields type matching, one needs to set the type property of the multi_match query to the best_fields query. This type of multimatching will generate a match query for each field specified in the fields property and it is best used for searching for multiple words in the same best matching field. For example, let's look at the following query:

curl -XGET 'localhost:9200/library/_search?pretty' -d '{ 
  "query" : { 
    "multi_match" : { 
      "query" : "complete conan doyle", 
      "fields" : [ "title", "author", "characters" ], 
      "type" : "best_fields", 
      "tie_breaker" : 0.8 
    } 
  } 
}'

The preceding query would be translated into a query similar to the following...

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