High Performance in-memory computing with Apache Ignite-Leanpub(2017).pdf

My first acquaintance with High load systems was at the beginning of 2007, and I started working on a real-world project since 2009. From that moment, I spent most of my office time with Cassandra, Hadoop, and numerous CEP tools. Our first Hadoop project (the year 2011-2012) with a cluster of 54 nodes often disappointed me with its long startup time. I have never been satisfied with the performance of our applications and was always looking for something new to boost the performance of our information systems. During this time, I have tried HazelCast, Ehcache, Oracle Coherence as in-memory caches to gain the performance of the applications. I was usually disappointed from the complexity of using these libraries or from their functional limitations. When I first encountered Apache Ignite, I was amazed! It was the platform that I’d been waiting on for a long time: a simple spring based framework with a lot of awesome features such as DataBase caching, Big data acceleration, Streaming and compute/service grids. In 2015, I had participated in Russian HighLoad++ conference1 with my presentation and started blogging in Dzone/JavaCodeGeeks and in my personal blog2 about developing High-load systems. They became popular shortly, and I received a lot of feedback from the readers. Through them, I clarified the idea behind the book. The goal of the book was to provide a guide for those who really need to implement an in-memory platform in their projects. At the same time, the idea behind the book is not writing a manual. Although the Apache Ignite platform is very big and growing day by day, we concentrate only on the features of the platform (from our point of view) that can really help to improve the performance of the applications. We hope that High-performance in-memory computing with Apache Ignite will be the go-to guide for architects and developers: both new and at an intermediate level, to get up and to develop with as little friction as possible.