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)

What this book covers

Chapter 1, Enterprise Data Architecture Principles, shows how to store and model data in Hadoop clusters.

Chapter 2, Hadoop Life Cycle Management, covers various data life cycle stages, including when the data is created, shared, maintained, archived, retained, and deleted. It also further details data security tools and patterns.

Chapter 3, Hadoop Design Considerations, covers key data architecture principles and practices. The reader will learn how modern data architects adapt to big data architect use cases.

Chapter 4, Data Movement Techniques, covers different methods to transfer data to and from our Hadoop cluster to utilize its real power.

Chapter 5, Data Modeling in Hadoop, shows how to build enterprise applications using cloud infrastructure.

Chapter 6, Designing Real-Time Streaming Data Pipelines, covers different tools and techniques of designing real-time data analytics.

Chapter 7, Large-Scale Data Processing Frameworks, describes the architecture principles of enterprise data and the importance of governing and securing that data.

Chapter 8, Building an Enterprise Search Platform, gives a detailed architecture design to build search solutions using Elasticsearch.

Chapter 9, Designing Data Visualization Solutions, shows how to deploy your Hadoop cluster using Apache Ambari.

Chapter 10, Developing Applications Using the Cloud, covers different ways to visualize your data and the factors involved in choosing the correct visualization method.

Chapter 11, Production Hadoop Cluster Deployment, covers different data processing solutions to derive value out of our data.