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)

Data wrangling

If you have some experience working on data of some sort, you will recollect that most of the time data needs to be preprocessed so that we can further use it as part of a bigger analysis. This process is called data wrangling.

Let's see what the typical flow in this process looks like:

  • Data acquisition
  • Data structure analysis
  • Information extraction
  • Unwanted data removal
  • Data transformation
  • Data standardization

Let's try to understand these in detail.

Data acquisition

Even though not a part of data wrangling, this phase deals with the process of acquiring data from somewhere. Typically, all data is generated and stored in a central location or is available in files located on some shared storage...