Distributed Data Processing with Infinispan and Java Streams

Distributed Data Processing with Infinispan and Java Streams

zamareno Distributed Data Processing with Infinispan and Java Streams

Galder Zamarreño is a core R&D engineer at JBoss, a division of Red Hat. He is one of the founding engineers of Infinispan, Red Hat’s distributed, in-memory key-value store and he currently spends most of his time developing Infinispan’s Functional Map API as well as other data grid and caching functionality. He is very keen on functional programming and has been developing in Scala since 2009. Galder has previously worked with JBoss customers helping them build highly distributed and massively scalable Application Server clusters based on technologies such as JGroups and JBoss Cache. Prior to joining Red Hat, Galder worked in the Retail industry where he was a software developer involved in the development of an EFT software switch solution based on JBoss technologies. The love for distributed systems and open source software comes from his days at ESIDE faculty at University of Deusto (Bilbao, Spain) where he studied a master’s degree in Computer Science.

Infinispan is a distributed in-memory key/value data store capable accelerating data processing using Hadoop, Spark and home-grown Map/Reduce APIs. Starting with Infinispan 8, you can now also use the Java 8 Stream API to process, transform and analyse the data stored in the grid, without burdening the architecture with external platforms. Processing can be applied to keys and/or values and it uses Infinispan’s data partitioning logic to distribute operations to nodes where data lives so that they can be executed locally. In this talk you’ll learn about this new extension to Java 8’s Stream class to process data in Infinispan and how it compares with existing APIs.

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