Book Image

Elasticsearch 5.x Cookbook - Third Edition

By : Alberto Paro
Book Image

Elasticsearch 5.x Cookbook - Third Edition

By: Alberto Paro

Overview of this book

Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. This book is your one-stop guide to master the complete Elasticsearch ecosystem. We’ll guide you through comprehensive recipes on what’s new in Elasticsearch 5.x, showing you how to create complex queries and analytics, and perform index mapping, aggregation, and scripting. Further on, you will explore the modules of Cluster and Node monitoring and see ways to back up and restore a snapshot of an index. You will understand how to install Kibana to monitor a cluster and also to extend Kibana for plugins. Finally, you will also see how you can integrate your Java, Scala, Python, and Big Data applications such as Apache Spark and Pig with Elasticsearch, and add enhanced functionalities with custom plugins. By the end of this book, you will have an in-depth knowledge of the implementation of the Elasticsearch architecture and will be able to manage data efficiently and effectively with Elasticsearch.
Table of Contents (25 chapters)
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Dedication
Preface

Introduction


In Elasticsearch ecosystem, it can be immensely useful to monitor nodes and cluster to manage and improve their performance and state. There are several issues that can arise at cluster level, such as:

  • Node overheads, where some nodes can have too many shards allocated and can become a bottleneck for the entire cluster

  • Node shutdown can happen due to many reasons, for example, full disks, hardware failures, and power problems

  • Shard relocation problems or corruptions, in which some shards are unable to get an online status

  • Too large shards happens when a shard is too big; the index performance decreases due to Lucene massive segments merging

  • Empty indices and shards waste memory and resources, but because every shard has a lot of active threads if there is a huge number of unused indices and shards, the general cluster performance is degraded

  • Node problems such as high CPU usage or disk full

Detecting malfunction or bad performances can be done via API or via some frontends that are...