Building enterprise-grade distributed applications and executing systematic search operations calls for a strong understanding of Elasticsearch and expertise in using its core APIs and latest features. This book will help you master the advanced functionalities of Elasticsearch and learn how to develop a sophisticated real-time search engine confidently. In addition to this, you'll also learn how to run machine learning jobs in Elasticsearch to speed up routine tasks.
You'll get started by learning how to use Elasticsearch features on Hadoop and Spark and make search results faster, thereby improving the speed of queries and enhancing customer experience. You'll then get up to speed with analytics by building a metrics pipeline, defining queries, and using Kibana for intuitive visualizations that help provide decision makers with better insights. The book will later guide you through using Logstash to collect, parse, and enrich logs before indexing them into Elasticsearch.
By the end of this book, you will have comprehensive knowledge of advanced topics such as Apache Spark support, machine learning using Elasticsearch and scikit-learn, and real-time analytics, along with the expertise you need to increase business productivity, perform analytics, and get the very best out of Elasticsearch.
You will do the following:
- Pre-process documents before indexing in ingest pipelines
- Learn how to model your data in the real world
- Get to grips with using Elasticsearch for exploratory data analysis
- Understand how to build analytics and RESTful services
- Use Kibana, Logstash, and Beats for dashboard applications
- Get up to speed with Spark and Elasticsearch for real-time analytics
- Explore the Java high/low-level REST client and learn how to index, search, and query in a Spring application