Book Image

Modern Big Data Processing with Hadoop

By : V Naresh Kumar, Manoj R Patil, Prashant Shindgikar
Book Image

Modern Big Data Processing with Hadoop

By: V Naresh Kumar, Manoj R Patil, Prashant Shindgikar

Overview of this book

The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems.
Table of Contents (12 chapters)


In this chapter, you looked at the basic concepts and components of an Elasticsearch cluster.

After this, we discussed how Elasticsearch indexes a document using inverted index. We also discussed mapping and analysis techniques. We learned how we can denormalize an event before ingesting into Elasticsearch. We discussed how Elasticsearch uses horizontal scalability and throughput. After learning about Elasticstack components such as Beats, Logstash, and Kibana, we handled a live use case, where we demonstrated how access log events can be ingested into Kafka using Filebeat. We developed a code to pull messages from Kafka and ingest into Elasticsearch using Logstash. At the end, we learned data visualization using Kibana.

In the next chapter, we will see how to build analytics to design data visualization solutions that drive business decisions.