Webinar: How to Easily Share State Across Multiple Spark Jobs using Apache Ignite™
About
Learn how to easily share state in memory across multiple Spark jobs, either within the same application or between different Spark applications using an implementation of Spark RDD abstraction provided in the latest release of Apache Ignite™ in an upcoming webinar on February 3, 2016 at 11:00 AM PDT / 2:00 PM EDT.
In this one-hour webinar, Apache Ignite Podling Project Management Committee Member and GridGain co-founder Dmitriy Setrakyan, will explain the details behind IgniteRDD, a newly introduced implementation of native Spark RDD and DataFrame APIs which, in addition to all the standard RDD functionality, also has the ability to share the state of the RDD across other Spark jobs, applications and workers. Dmitriy will also demonstrate how IgniteRDD, with its advanced in-memory indexing capabilities, allows to execute SQL queries many times faster than native Spark RDDs or Data Frames.
Don't miss this opportunity to learn how these two leading-edge Apache projects can be used together to provide more power and flexibility to developers and software architects who are building the next generation of Big Data/Fast Data applications.
In this one-hour webinar, Apache Ignite Podling Project Management Committee Member and GridGain co-founder Dmitriy Setrakyan, will explain the details behind IgniteRDD, a newly introduced implementation of native Spark RDD and DataFrame APIs which, in addition to all the standard RDD functionality, also has the ability to share the state of the RDD across other Spark jobs, applications and workers. Dmitriy will also demonstrate how IgniteRDD, with its advanced in-memory indexing capabilities, allows to execute SQL queries many times faster than native Spark RDDs or Data Frames.
Don't miss this opportunity to learn how these two leading-edge Apache projects can be used together to provide more power and flexibility to developers and software architects who are building the next generation of Big Data/Fast Data applications.
Speakers