Book Image

Elasticsearch 7.0 Cookbook - Fourth Edition

By : Alberto Paro
Book Image

Elasticsearch 7.0 Cookbook - Fourth 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. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics. Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will 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 book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch.
Table of Contents (23 chapters)
Title Page

Scala Integration

Scala is becoming one of the most used languages in big data scenarios. This language provides a lot of facilities for managing data, such as immutability and functional programming.

In Scala, you can simply use the libraries we saw in the previous chapter for Java, but they are not scalastic as they don't provide type safety (because many of these libraries take a JSON as a string) and it is easy to use asynchronous programming.

In this chapter, we will look at how to use elastic4s, a mature library, to use Elasticsearch in Scala. Its main features are as follows:

  • Type-safe, concise DSL
  • Integrates with standard Scala futures
  • Uses the Scala collections library over Java collections
  • Returns option where the Java methods would return null
  • Uses Scala durations instead of strings/longs for time values
  • Uses typeclass for marshalling and unmarshalling classes...