Book Image

Apache Hadoop 3 Quick Start Guide

By : Hrishikesh Vijay Karambelkar
Book Image

Apache Hadoop 3 Quick Start Guide

By: Hrishikesh Vijay Karambelkar

Overview of this book

Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS. The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems. The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring. You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.
Table of Contents (10 chapters)

Running Hadoop in standalone mode

Now that you have successfully unzipped Hadoop, let's try and run a Hadoop program in standalone mode. As we mentioned in the introduction, Hadoop's standalone mode does not require any runtime; you can directly run your MapReduce program by running your compiled jar. We will look at how you can write MapReduce programs in the Chapter 4, Developing MapReduce Applications. For now, it's time to run a program we have already prepared. To download, compile, and run the sample program, simply take the following steps:

Please note that this is not a mandatory requirement for setting up Apache Hadoop. You do not need a Maven or Git repository setup to compile or run Hadoop. We are doing this to run some simple examples.
  1. You will need Maven and Git on your machine to proceed. Apache Maven can be set up with the following command: