Course Duration in Hours
60
60
Module: Thinking at Scale: Introduction to Hadoop
You know your data is big you found Hadoop. What implications must you consider when working at this scale? This lecture addresses common challenges and general best practices for scaling with your data.
Module: MapReduce and HDFS
These tools provide the core functionality to allow you to store, process, and analyze big data. This lecture "lifts the curtain" and explains how the technology works. You ll understand how these components fit together and build on one another to provide a scalable and powerful system.
Exercise Module: Getting Started with Hadoop
If you d like a more hands-on experience, this is a good time to download the VM and kick the tires a bit. In this activity, using the provided instructions, you ll get a feel for the tools and run some sample jobs.
Module: The Hadoop Ecosystem
An introduction to other projects surrounding Hadoop, which complete the greater ecosystem of available large-data processing tools.
Module: The Hadoop MapReduce API
Learn how to get started writing programs against Hadoop s API.
Module: Introduction to MapReduce Algorithms
Writing programs for MapReduce requires analyzing problems in a new way. This lecture shows how some common functions can be expressed as part of a MapReduce pipeline.
Any Graduates
STAR IT TECHNOLOGIES, Thane,IN