Please note: This course is delivered by accredited Hortonworks instructors. The syllabus includes specific use cases and examples to help illustrate and reinforce the theory and the functionality of the technology being explored. Where possible, the instructor will provide further examples and answer questions relevant to an individual delegates specific application of the technology. However, due to the complexity of the technology and the breadth of application across industries, this may not always be possible in the classroom environment.
This advanced course provides Java programmers a deep-dive into Hadoop application development.
Delegates will learn how to design and develop efficient and effective MapReduce applications for Hadoop using the Hortonworks Data Platform, including how to implement combiners, partitioners, secondary sorts, custom input and output formats, joining large datasets, unit testing, and developing UDFs for Pig and Hive. Labs are run on a 7-node HDP 2.1 cluster running in a virtual machine that students can keep for use after the training.
Experienced Java software engineers who need to develop Java MapReduce applications for Hadoop.