As a Hadoop administrator, one important activity that you need to do is to ensure that all of the resources are used in the most optimal manner inside the cluster. When I refer to a resource, I mean the CPU time, the memory allocated to jobs, the network bandwidth utilization, and storage space consumed. Administrators can achieve that by balancing workloads on the jobs that are running in the cluster environment. When a cluster is set up, it may run different types of jobs, requiring different levels of time- and complexity-based SLAs. Fortunately, Apache Hadoop provides a built-in scheduler for scheduling jobs to allow administrators to prioritize different jobs as per the SLAs defined. So, overall resources can be managed by resource scheduling. All schedulers used in Hadoop use job queues to line up the jobs for prioritization. Among all, the...
Apache Hadoop 3 Quick Start Guide
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Apache Hadoop 3 Quick Start Guide
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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)
Preface
Free Chapter
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
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