Understand the tenets of Cassandra's column-oriented structure Learn how to write, update, and read Cassandra data Discover how to add or remove nodes from the cluster as your application requires Examine a working application that translates from a relational model to Cassandra's data model Use examples for writing clients in Java, Python, and C Use the JMX interface to monitor a cluster's usage, memory patterns, and more Tune memory settings, data storage, and caching for better performance.
Score: 5. Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Hadoop: The Definitive Guide is the most thorough book available on the subject. Using Flume shows operations engineers how to configure, deploy, and monitor a Flume cluster, and teaches developers how to write Flume plugins and custom components for their specific use-cases.
Code examples and exercises are available on GitHub. Comprehensive in scope, the book presents state-of-the-art material on building high performance distributed computing systems, providing practical guidance and best practices as well as describing theoretical software frameworks. Features: describes the fundamentals of building scalable software systems for large-scale data processing in the new paradigm of high performance distributed computing; presents an overview of the Hadoop ecosystem, followed by step-by-step instruction on its installation, programming and execution; Reviews the basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case studies on approaches to clustering, data classification and regression analysis; Explains the process of creating a working recommender system using Scalding and Spark.
Popular Books. Fear No Evil by James Patterson. This book will be your definitive guide to batch and stream data processing with Apache Flink. In the latter half of the book, readers will get to learn the remaining ecosystem of Apache Flink to achieve complex tasks such as event processing, machine learning, and graph processing.
The final part of the book would consist of topics such as scaling Flink solutions, performance optimization and integrating Flink with other tools such as ElasticSearch. Whether you want to dive deeper into Apache Flink, or want to investigate how to get more out of this pow. This book assumes that you have basic knowledge of Hadoop and its ecosystem of tools. You will learn to build six real-life, end-to-end applications using Hadoop in its ecosystem.
Each chapter will cover the steps required to build an application end to end. We start off by discussing various industry use cases and the associated business cases.
We also discuss common architectural patterns. Next, you'll learn how to import and utilize structured and semi-structured data to build a degree view of the customer. We'll also build a classification model based upon historical data using a machine learning library.
We then move on to use an analytics model to predict the likelihood of a certain event. Through these real-world cases, you'll take your Hadoop learning to the next level. You will be able to try out the s. The solutions cover everything from building dynamic websites and working with databases to network communication, cloud computing, and advanced testing strategies. Each recipe includes code that you can use right away, along with a discussion on how and why the solution works, so you can adapt these patterns, approaches, and techniques to situations not specifically covered in this cookbook.
Popular Books. Fear No Evil by James Patterson. Mercy by David Baldacci. From This Moment by Melody Grace. The Dark Hours by Michael Connelly. The Awakening by Nora Roberts. This editions covers the new features such as Hive, Sqoop and Avro.
It also provides you with case studies that can help you solve specific problems. First and foremost, this book is obviously about design patterns, which are templates or general guides to solving problems. However, similarly to the cookbooks, the lessons in this book are short and categorized. Download: MapReduce Design Pattern. If you have been asked to maintain large and complex Hadoop clusters, this book is a must.
Download: Hadoop Operations. Download: Programming Hive. Readers will become more familiar with a wide variety of Hadoop-related tools and best practices for implementation. This book will give readers the examples they need to apply the Hadoop technology to their own problems. Our Placements. Students Testimonials. Our Centers. Join over As more corporations turn to Hadoop to store and process their most valuable data, the risk of a potential breach of those systems increases exponentially.
This practical book not only shows Hadoop administrators and security architects how to protect Hadoop data from unauthorized access, it also shows how to limit the ability of an attacker to corrupt or modify data in the event of a security breach.
Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. Understand the challenges of securing distributed systems, particularly Hadoop Use best practices for preparing Hadoop cluster hardware as securely as possible Get an overview of the Kerberos network authentication protocol Delve into authorization and accounting principles as they apply to Hadoop Learn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at rest Integrate Hadoop data ingest into enterprise-wide security architecture Ensure that security architecture reaches all the way to end-user access.
This practical book not only shows Hadoop administrators and security architects how to protect Hadoop data from unauthorized access, it also shows how to limit. Practical Hadoop Security is an excellent resource for administrators planning a production Hadoop deployment who want to secure their Hadoop clusters. A detailed guide to the security options and configuration within Hadoop itself, author Bhushan Lakhe takes you through a comprehensive study of how to implement defined security within a.
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