Book Image

Elasticsearch 8.x Cookbook - Fifth Edition

By : Alberto Paro
Book Image

Elasticsearch 8.x Cookbook - Fifth Edition

By: Alberto Paro

Overview of this book

Elasticsearch is a Lucene-based distributed search engine at the heart of the Elastic Stack that allows you to index and search unstructured content with petabytes of data. With this updated fifth edition, you'll cover comprehensive recipes relating to what's new in Elasticsearch 8.x and see how to create and run complex queries and analytics. The recipes will guide you through performing index mapping, aggregation, working with queries, and scripting using Elasticsearch. You'll focus on numerous solutions and quick techniques for performing both common and uncommon tasks such as deploying Elasticsearch nodes, using the ingest module, working with X-Pack, and creating different visualizations. As you advance, you'll learn how to manage various clusters, restore data, and install Kibana to monitor a cluster and extend it using a variety of plugins. Furthermore, you'll understand how to integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this Elasticsearch cookbook, you'll have gained in-depth knowledge of implementing the Elasticsearch architecture and be able to manage, search, and store data efficiently and effectively using Elasticsearch.
Table of Contents (20 chapters)

Setting up an NFS share for backups

Managing the repository (where the data is stored) is the most crucial part of Elasticsearch backup management. Due to its native distributed architecture, the snapshot and the restoration process are designed in a cluster style.

During a snapshot, the shards are copied to the defined repository. If this repository is local to the nodes, then the backup data is spread across all the nodes. For this reason, it's necessary to have shared repository storage if you have a multi-node cluster.

A common approach is to use an NFS, as it's very easy to set up, and it's a very quick solution (additionally, standard Windows Samba shares can be used).

Getting ready

We have a network with the following nodes:

  • Host server: 192.168.1.30 (where we will store the backup data)
  • Elasticsearch master node 1: 192.168.1.40
  • Elasticsearch data node 1: 192.168.1.50
  • Elasticsearch data node 2: 192.168.1.51

You will need...