Book Image

Apache Mesos Essentials

By : Dharmesh Kakadia
Book Image

Apache Mesos Essentials

By: Dharmesh Kakadia

Overview of this book

<p>Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It allows developers to concurrently run the likes of Hadoop, Spark, Storm, and other applications on a dynamically shared pool of nodes. With Mesos, you have the power to manage a wide range of resources in a multi-tenant environment.</p> <p>Starting with the basics, this book will give you an insight into all the features that Mesos has to offer. You will first learn how to set up Mesos in various environments from data centers to the cloud. You will then learn how to implement self-managed Platform as a Service environment with Mesos using various service schedulers, such as Chronos, Aurora, and Marathon. You will then delve into the depths of Mesos fundamentals and learn how to build distributed applications using Mesos primitives.</p> <p>Finally, you will round things off by covering the operational aspects of Mesos including logging, monitoring, high availability, and recovery.</p>
Table of Contents (15 chapters)
Apache Mesos Essentials
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Introducing Spark


Apache Spark is a fast and scalable general data processing framework (http://spark.apache.org). Spark provides a very concise syntax for writing a wide range of data processing applications. Spark became a top-level Apache project in early 2014.

The Spark project was started at Berkeley as part of the Berkeley Data Analytics Stack (https://amplab.cs.berkeley.edu/software), the same project that Mesos comes from. Spark was the first data processing framework built on Mesos and effectively leverages Mesos for resource management. Spark is one of the fastest growing data analysis frameworks and aims to unify all kinds of data analysis under a single unified API. Spark provides a unified API for doing batch, streaming, and iterative data processing.

Spark makes an aggressive use of memory to accelerate computations. Spark's Directed Acyclic Graph (DAG) execution engine is suitable for a wide range of applications, including the interactive and iterative algorithms that often...