In this article, by the authors, Amol Fasale and Nirmal Kumar , of the book, YARN Essentials , you will learn about what YARN is and how it's implemented with Hadoop. YARN. YARN stands for Yet Another Resource Negotiator . YARN is a generic resource platform to manage resources in a typical cluster. YARN was introduced with Hadoop 2.0, which is an open source distributed processing framework from the Apache Software Foundation. In 2012, YARN became one of the subprojects of the larger Apache Hadoop project. YARN is also coined by the name of MapReduce 2.0. This is since Apache Hadoop MapReduce has been re-architectured from the ground up to Apache Hadoop YARN. Think of YARN as a generic computing fabric to support MapReduce and other application paradigms within the same Hadoop cluster; earlier, this was limited to batch processing using MapReduce. This really changed the game to recast Apache Hadoop as a much more powerful data processing system. With the advent of YARN, Hadoop now looks very different compared to the way it was only a year ago. YARN enables multiple applications to run simultaneously on the same shared cluster and allows applications to negotiate resources based on need. Therefore, resource allocation/management is central to YARN. YARN has been thoroughly tested at Yahoo! since September 2012. It has been in production across 30,000 nodes and 325 PB of data since January 2013. Recently, Apache Hadoop YARN won the Best Paper Award at ACM Symposium on Cloud Computing ( SoCC ) in 2013!
In this article by Patrick Espake , author of the book Learning Heroku Postgres , you will learn how to install and set up PostgreSQL and how to create an app using Postgres.
In this article by Richard Grimmett , author of the book Intel Galileo Essentials ,let's graduate from a simple DC motor to a wheeled platform. There are several simple, two-wheeled robotics platforms. In this example, you'll use one that is available on several online electronics stores. It is called the Magician Chassis, sourced by SparkFun. The following image shows this:
As an application developer, you have almost certainly worked with databases extensively. You must have built products using relational databases like MySQL and PostgreSQL, and perhaps experimented with a document store like MongoDB or a key-value database like Redis. While each of these tools has its strengths, you will now consider whether a distributed database like Cassandra might be the best choice for the task at hand. In this article by Mat Brown , author of the book Learning Apache Cassandra , we'll talk about the major reasons to choose Cassandra from among the many database options available to you. Having established that Cassandra is a great choice, we'll go through the nuts and bolts of getting a local Cassandra installation up and running. By the end of this article, you'll know: When and why Cassandra is a good choice for your application How to install Cassandra on your development machine How to interact with Cassandra using cqlsh How to create a keyspace
In this article by William Confer and William Roberts , author of the book, Exploring SE for Android , we will learn once we have an SE for Android system, we need to see how we can make use of it, and get it into a usable state. In this article, we will: Modify the log level to gain more details while debugging Follow the boot process relative to the policy loader Investigate SELinux APIs and SELinuxFS Correct issues with the maximum policy version number Apply patches to load and verify an NSA policy