High Performance In Memory Computing With Apache Ignite

This book covers a verity of topics, including in-memory data grid, highly available service grid, streaming (event processing for IoT and fast data) and in-memory computing use cases from high-performance computing to get performance gains. The book will be particularly useful for those, who have the following use cases: 1)

This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020. The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions. The papers

Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical

Build efficient, high-performance & scalable systems to process large volumes of data with Apache Ignite Key Features Understand Apache Ignite's in-memory technology Create High-Performance app components with Ignite Build a real-time data streaming and complex event processing system Book Description Apache Ignite is a distributed in-memory platform designed to scale

Use Hadoop to solve business problems by learning from a rich set of real-life case studies About This Book Solve real-world business problems using Hadoop and other Big Data technologies Build efficient data lakes in Hadoop, and develop systems for various business cases like improving marketing campaigns, fraud detection, and

This book demonstrates how to exploit high performance computing with the MOEA Framework, from small personal computers up to large-scale supercomputers. For distributed memory computing on larger systems, we demonstrate how to use Apache Ignite to construct master-slave, island model, and hybrid parallelization architectures. The purchase of this book includes

Every 3rd issue is a quarterly cumulation.