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Apache Hadoop 3 Quick Start Guide

You're reading from  Apache Hadoop 3 Quick Start Guide

Product type Book
Published in Oct 2018
Publisher Packt
ISBN-13 9781788999830
Pages 220 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Profile icon Hrishikesh Vijay Karambelkar
LinkedIn
Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
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Table of Contents (10) Chapters

Preface Hadoop 3.0 - Background and Introduction Planning and Setting Up Hadoop Clusters Deep Dive into the Hadoop Distributed File System Developing MapReduce Applications Building Rich YARN Applications Monitoring and Administration of a Hadoop Cluster Demystifying Hadoop Ecosystem Components Advanced Topics in Apache Hadoop Other Books You May Enjoy

How MapReduce works

MapReduce is a programming methodology used for writing programs on Apache Hadoop. It allows the programs to run on a large scalable cluster of servers. MapReduce was inspired by functional programming (https://en.wikipedia.org/wiki/Functional_programming). Functional Programming (FP) offers amazing unique features when compared to today's popular programming paradigms such as object-oriented (Java and JavaScript), declarative (SQL and CSS), or procedural (C, PHP, and Python). You can look at a comparison between multiple programming paradigms here. While we see a lot of interest in functional programming in academics, we rarely see equivalent enthusiasm from the developer community. Many developers and mentors claim that MapReduce is not actually a functional programming paradigm. Higher order functions in FP are functions that can take a function as...

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Authors (1)

Profile icon Hrishikesh Vijay Karambelkar
LinkedIn
Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
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See other products by Hrishikesh Vijay Karambelkar

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