Distributed, in-memory computing technologies such as caches, data grids, and databases boost application performance and solve scalability problems by storing and processing large datasets across a cluster of interconnected machines.
This session is for software engineers and architects who build data-intensive applications and want practical experience with in-memory computing. You will be introduced to the fundamental capabilities of distributed, in-memory systems and will learn how to tap into your cluster’s resources and how to negate any negative impact that the network might have on the performance of your applications.
Join Denis Magda as he describes and demonstrates three essential capabilities of in-memory computing—with code samples based on Apache Ignite:
- Data partitioning: to use all of a cluster’s memory and CPU resources.
- Affinity co-location: to avoid data shuffling and use highly performant, distributed SQL queries.
- Co-located processing: to perform compute and data-intensive calculations at high speeds straight on the cluster nodes.
== Denis Magda
Denis Magda is an open-source software enthusiast who started his journey in the technology evangelism group of Sun Microsystems and Java engineering team of Oracle. He now supports the Apache Software Foundation in the roles of Apache Ignite committer and Project Management Committee member. As the Head of Developer Relations for GridGain Systems, he works with software engineers and architects to help them gain expertise in in-memory computing.