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)

Apache Hive

Hive is a data processing tool in Hadoop. As we have learned in the previous chapter, data ingestion tools load data and generate HDFS files in Hadoop; we need to query that data based on our business requirements. We can access the data using MapReduce programming. But data access with MapReduce is extremely slow. To access a few lines of HDFS files, we have to write separate mapper, reducer, and driver code. So, in order to avoid this complexity, Apache introduced Hive. Hive supports an SQL-like interface that helps access the same lines of HDFS files using SQL commands. Hive was initially developed by Facebook but was later taken over by Apache.

Apache Hive and RDBMS

I mentioned that Hive provides an SQL-like...