Book Image

Mastering Hadoop 3

By : Chanchal Singh, Manish Kumar
Book Image

Mastering Hadoop 3

By: Chanchal Singh, Manish Kumar

Overview of this book

Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines.
Table of Contents (23 chapters)
Title Page
Dedication
About Packt
Foreword
Contributors
Preface
Index

Data governance


Data governance is the process of ensuring  high quality, high availability, usability, integrity, and security of the data that's used across the organization. Data governance helps the organization to efficiently manage the data it has and get more value from that data, along with making the important value of that data visible to users. 

Data governance enables and encourages good behavior about data and also limits any behavior that create risks. This objective is similar, irrespective of whether we are in a big data environment or a traditional data management environment. It helps the organization identify who is responsible for the data, collaborate to set policies and decisions, analyse how the data is used and what it is for, understand how and where metrics and information are derived, and determines the impact of any change in data on the business.

Data governance pillars

There are multiple definitions you will find about data governance pillars; we have defined three...