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)

Summary

In this chapter, we have learned all the popular data ingestion tools used in production environments. Sqoop is mainly used to import and export data in and out of RDBMS data stores. Apache Flume is used in real-time systems to import data, mainly from files sources. It supports a wide variety of sources and sinks. Apache NiFi is a fairly new tool and getting very popular these days. It also supports GUI-based ETL development. Hortonworks has started supporting this tool since their HDP 2.4 release. Apache Kafka Connect is another popular tool in the market. It is also a part of the Confluent Data Platform. Kafka Connect can ingest entire databases or collect metrics from all your application servers into Kafka topics, making the data available for stream processing with low latency.

Since we so far know how to build Hadoop clusters and how to ingest data in them, we will...