Book Image

Mastering Elasticsearch 5.x - Third Edition

By : Bharvi Dixit
Book Image

Mastering Elasticsearch 5.x - Third Edition

By: Bharvi Dixit

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.
Table of Contents (13 chapters)

NRT, flush, refresh, and transaction log


In an ideal search solution, when new data is indexed, it is instantly available for searching. When you start Elasticsearch, this is exactly how it works even in distributed environments. However, this is not the whole truth, and we will show you why it is like this.

Let's start by indexing an example document to the newly created index using the following command:


curl -XPOST localhost:9200/test/test/1 -d '{ "title": "test" }'

Now, let's replace this document, and let's try to find it immediately. In order to do this, we'll use the following command chain:

curl -XPOST localhost:9200/test/test/1 -d '{ "title": "test2" }' ; 
curl -XGET 'localhost:9200/test/test/_search?pretty'

The preceding command will probably result in a response that is very similar to the following one:

{"_index":"test","_type":"test","_id":"1","_version":2,"result":"updated","_shards":{"total":2,"successful":1,"failed":0},"created":false} 
{ 
  "took" : 6, 
 ...