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Typesafe Announces Full Lifecycle Support For Apache Spark

By - Source: Typesafe

Typesafe, makers of the Typesafe Reactive Platform, announced a commercial support program for the Apache Spark in-memory data processing engine. Typesafe co-founder Martin Odersky is the creator of the Scala programming language. Apache Spark is written in Scala, making it the language of choice for many Spark developers. Under the new program, Typesafe offers support for Spark developers using Scala, along with support for Apache Mesos, Apache Kafka, Hadoop and more.

"Being successful in any Spark project, whether it's architecture, code reviews, best practices, or production support, calls for the best expertise in the world," said Jamie Allen, Senior Director of Global Services at Typesafe. "Typesafe can help you build a truly Reactive big data solution so you have confidence you are designing, building and deploying things the right way and taking advantage of the full capabilities of Spark and related technologies."

Big Data processing architectures have evolved away from MapReduce batch-oriented processing using Hadoop clusters and Java, to in-memory tools such as Apache Spark aimed at processing "Fast" data streams in real time. The new support options from Typesafe aim to help customers quickly develop reactive big data processing solutions.

Typesafe offers full lifecycle support for customers' Apache Spark projects, starting from two-day hands on Spark workshops to assist developers in getting up to speed quickly, where developers learn how to implement and maintain Fast Data pipelines, to architecture and design reviews and  technical support available 24/7. Official support is offered for Spark Core, Spark SQL, Spark Streaming modules, and the Scala and Java APIs.

Typesafe is a contributor to the Apache Spark project, having added backpressure support to Spark 1.5 that allows streaming programs to dynamically adjust to system instability, such as a large burst in input, or a temporary delay in writing output.