Better Together: Fast Data with Apache Spark and Apache Ignite - Databricks

Better Together: Fast Data with Apache Spark and Apache Ignite

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Spark and Ignite are two of the most popular open source projects in the area of high-performance Big Data and Fast Data. But did you know that one of the best ways to boost performance for your next generation real-time applications is to use them together? In this session, Nikita Ivanov, Apache Ignite Project Committee member and Founder and CTO at GridGain, will explain in detail how IgniteRDD – an implementation of native Spark RDD and DataFrame APIs – shares the state of the RDD across other Spark jobs, applications and workers. Nikita will also demonstrate how IgniteRDD, with its advanced in-memory indexing capabilities, allows execution of SQL queries many times faster than native Spark RDDs or Data Frames. Don’t miss this opportunity to learn from one of the experts how to use Spark and Ignite better together in your projects.

About Christos Erotocritou

Christos Erotocritou comes from a software engineering background currently working as solutions architect at GridGain Systems with over 10 years experience in technology. Driven by a passion and dedication for solving complex problems and finding new ways to use technology, he has worked for a number of software companies specialising in high-performance in-memory computing and has hands-on experience with a broad spectrum of technologies. His key areas of expertise include In-memory computing, data grids, distributed systems, NoSQL, cloud applications & orchestration, DevOps, IoT, Raspberry Pi, Arduino and other micro-controllers. He has a master's degree in Intelligent Systems (AI) from university of Sussex and a bachelors in Software Engineering.