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This advanced course provides Java programmers a deep-dive into Hadoop application development. Students 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.
Students must have experience developing Java applications and using a Java IDE. Labs are completed using the Eclipse IDE and Gradle. No prior Hadoop knowledge is required.
Experienced Java software engineers who need to develop Java MapReduce applications for Hadoop.
At the completion of the course students will be able to:
Students will work through the following lab exercises using Eclipse, Maven, and the Hortonworks Data Platform 2.X:
Hortonworks offers a comprehensive certification program that identifies you as an expert in Apache Hadoop. Visit Certification for more information.
Hortonworks University is your expert source for Apache Hadooptraining and certification. Public and private on-site courses areavailable for developers, administrators, data analysts and otherIT professionals involved in implementing big data solutions.Classes combine presentation material with industry-leading hands-on labs that fully prepare students for real-world Hadoop scenarios.
Please contact us for any questions on Apache Hadoop training courses or if you would like to discuss on-site training.