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Cloudera Announces New Apache Spark Training Course for Big Data Developers

Hands-On Course Prepares Developers to Write Sophisticated Parallel Applications for Faster Time-to-Insight and Stream Processing, Applied to a Wide Variety of Use Cases, Architectures, and Industries

PALO ALTO, CA -- (Marketwired) -- 07/16/14 -- Cloudera, the leader in enterprise analytic data management powered by Apache Hadoop™, today announced the first hands-on Apache Spark training course that will enrich developers' experience with this groundbreaking new processing engine. The three-day course, called Cloudera Developer Training for Apache Spark, will prepare developers and software engineers to build complete, unified applications that combine batch, streaming, and interactive analytics on all of their data. With Cloudera Developer Training for Apache Spark, data professionals can take advantage of this next-generation framework's advantages for speed, ease of use, and advanced analytics to enable faster business decisions and better user outcomes.

Spark is an open source data analytics framework originally developed in the AMPLab at the University of California, Berkeley that complements Hadoop as part of an enterprise data hub. Broadly embraced by the open source community, Big Data vendors, and data-intensive enterprises for its stream processing capabilities and its support for complex, iterative algorithms, Spark offers performance gains that enable applications to run on the data in a Hadoop cluster at speeds up to 100 times faster than traditional MapReduce programs. Cloudera was also the first company to offer commercial support for Spark as part of a Cloudera Enterprise subscription and recently announced a collaboration with Databricks, IBM, Intel, and MapR to broaden support for Spark as the standard data processing engine for the Hadoop ecosystem.

Through instructor-led discussions and interactive, hands-on exercises, participants will dive deep into the technical applications of Spark to understand how it relates to the rest of the Hadoop ecosystem and write sophisticated parallel applications. Developers will learn real-world best practices drawn from Cloudera's work with Spark on some of the largest clusters in development and production:

  • Using the Spark shell for interactive data analysis
  • The features of Spark's Resilient Distributed Datasets
  • How Spark runs on a cluster
  • Parallel programming with Spark
  • Writing Spark applications
  • Processing streaming data with Spark

"Spark offers clear benefits for realizing sophisticated analytics and is quickly becoming the future of data processing on Hadoop," said Sarah Sproehnle, vice president, Education Services, Cloudera. "With Spark, customers can realize immediate business advantages. For example, Spark Streaming enables businesses to process live data as it arrives in the enterprise data hub, rather than having to wait to batch-process it later. The fact that the same codebase can be used for streaming data and data-at-rest significantly reduces development time for Big Data applications, speeding up time-to-insight by several orders of magnitude and decreasing the need for expensive specialized systems. This is just one case where the benefits of Spark have a direct impact on a company's bottom line."

Cloudera offers a wide variety of courses to prepare developers to work with all aspects of Big Data. Cloudera Developer Training for Apache Spark offers developers a chance to experience the dramatic data processing improvements Spark delivers and build their expertise with one of the most relevant tools in an enterprise data hub. To learn more about this new course offering:

What developers are saying about Cloudera Developer Training for Apache Spark:
"The presentation format of all Cloudera training courses is always very clear and progressive. By building on previous concepts with each new course, Cloudera University makes Spark Developer Training an important step in a developer's learning path. The labs were extremely relevant to everyday Big Data challenges and went beyond the typical introductory exercises I have seen elsewhere. The classroom discussion led by the Cloudera instructor was invaluable, as each student came with different use cases and levels of knowledge. The course effectively reinforces the importance of learning Spark Streaming and the Lambda Architecture for combining batch and streaming workloads within a single environment. After seeing how other participants responded to the presentation format of Cloudera's Spark Developer Training course, I've actually changed the way I'm going to present the fundamental concepts in my book, Spark In Action."
-- Chris Fregly, author of Spark in Action

About Cloudera
Cloudera is revolutionizing enterprise data management by offering the first unified Platform for Big Data, an enterprise data hub built on Apache Hadoop™. Cloudera offers enterprises one place to store, process and analyze all their data, empowering them to extend the value of existing investments while enabling fundamental new ways to derive value from their data. Only Cloudera offers everything needed on a journey to an enterprise data hub, including software for business critical data challenges such as storage, access, management, analysis, security and search. As the leading educator of Hadoop professionals, Cloudera has trained over 22,000 individuals worldwide. Over 1,000 partners and a seasoned professional services team help deliver greater time to value. Finally, only Cloudera provides proactive and predictive support to run an enterprise data hub with confidence. Leading organizations in every industry plus top public sector organizations globally run Cloudera in production.

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Cloudera, Cloudera's Platform for Big Data, Cloudera Enterprise Data Hub Edition, Cloudera Enterprise Flex Edition, Cloudera Enterprise Basic Edition and CDH are trademarks or registered trademarks of Cloudera Inc. in the United States, and in jurisdictions throughout the world. All other company and product names may be trade names or trademarks of their respective owners.

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