Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:
- 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
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Audience & Prerequisites
This course is best suited to developers and software engineers. Course examples and exercises are presented in Python and Scala, so knowledge of one of these programming languages is required. Basic knowledge of Linux is assumed. Prior knowledge of Hadoop is not required.
Advance Your Ecosystem Expertise
Apache Spark is the next-generation successor to MapReduce. Spark is a powerful, open-source processing engine for data in the Hadoop cluster, optimized for speed, ease of use, and advanced analytics. The Spark framework supports streaming data processing and complex, iterative algorithms, enabling applications to run up to 100x faster than traditional Hadoop MapReduce programs.
Cloudera University was by far the most well-executed technical training I have attended. I feel confident that I can build my own big data application with an enterprise data hub, and I look forward to using the tools I learned in the classroom.
Advance Your Career
Developers and engineers with Spark experience are among the world's most in-demand and highly-compensated technical roles. Check out some of the job opportunities currently listed that match the professional profile, many of which seek experience building applications for stream processing and real-time analysis of big data.
We also provide private training at your site, at your pace, and tailored to your needs.