Cloudera Developer Training for Apache Spark (CDTAS)
- Data 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.
By the end of this course, you will learn:
- Using the Spark shell for interactive data analysis
- The features of Spark’s Resilient Distributed Datasets
- How Spark runs on a cluster
- How Spark parallelizes task execution
- Writing Spark applications
- Processing streaming data with Spark
This three-day course for Apache Spark enables you to build complete, unified big data applications combining batch, streaming, and interactive analytics on all their data. With Spark, developers can write sophisticated parallel applications to execute faster decisions, better decisions, and real-time actions, applied to a wide variety of use cases, architectures and industries.
Advance Your Ecosystem Expertise
Apache Spark is the next-generation successor to MapReduce. Spark is a powerful, opensource processing engine for data in the Hadoop cluster, optimized for speed, ease of use, and sophisticated 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.