Controlling Hadoop Jobs Using Oozie
This Apache Oozie course teaches you how to control Hadoop jobs on your Big Data projects. Even better, the materials and software provided are all free.
About this Course
This course gives an overview of Oozie and how it is able to control Hadoop jobs. It begins with looking at the components required to code a workflow as well as optional components such as case statements, forks, and joins. That is followed by using the Oozie coordinator in order to schedule a workflow.
One of the things that the student will quickly notice is that workflows are coded using XML which tends to get verbose. The last lesson of this course shows a graphical workflow editor tool designed to simplify the work in generating a workflow.
After completing this course, you should be able to:
- Describe the MapReduce model v1
- List the limitations of Hadoop 1 and MapReduce 1
- Review the Java code required to handle the Mapper class, the Reducer class, and the program driver needed to access MapReduce
- Describe the YARN model
- Compare YARN / Hadoop 2 / MR2 vs Hadoop 1 / MR1
- If you did not pass the course, you can take it again at any time.(Note: You have a maximum of 3 attempts.)
Have taken the Hadoop Fundamentals course on Big Data University.
Recommended skills prior to taking this course
- Basic understanding of Apache Hadoop and Big Data.
- Basic Linux Operating System knowledge.
- Basic understanding of the Scala, Python, or Java programming languages.