Get started with the basics of big data and Hadoop clusters and how to use Yarn, MapReduce, and HDFS in Hadoop clusters.

Become a Big Data Professional

This module offers a one-of-a-kind rich and interactive experience to learn the fundamentals and basics of big Data. Throughout this module, we will have plenty of opportunities to get our hands-on experience with functioning Hadoop clusters.

We will start off by learning about the rise of big data as well as the different types of data like structured, unstructured, and semi-structured data. We will then dive into the fundamentals of big data such as YARN (yet another resource manager), MapReduce, and HDFS (Hadoop Distributed File System). By the end of this module, we will have the foundations in place to start working with big data.

Introduction to Big Data and Hadoop

## Summary

The ecosystem of Big Data is still fledgling. New technologies and techniques are introduced frequently. A lot of room for simplification and innovation remains open. This course offered a practical and hands-on exposure to Big Data technologies. It can be hard to wrap your head around Big Data technologies without interacting with the components. HDFS, YARN, and more make up the Big Data stack, which is why you should undertake the exercises. Most Big Data technologies have equivalents in the cloud, but the fundamental technology remains the same.

You are more than welcome and encouraged to share any feedback on this course.

[C. H. Afzal.](https://www.linkedin.com/in/c-h-afzal-bb083a167)

# Summary

The ecosystem of Big Data is still fledgling. New technologies and techniques are introduced frequently. A lot of room for simplification and innovation remains open. This course offered a practical and hands-on exposure to Big Data technologies. It can be hard to wrap your head around Big Data technologies without interacting with the components. HDFS, YARN, and more make up the Big Data stack, which is why you should undertake the exercises. Most Big Data technologies have equivalents in the cloud, but the fundamental technology remains the same.

You are more than welcome and encouraged to share any feedback on this course.

[C. H. Afzal.](https://www.linkedin.com/in/c-h-afzal-bb083a167)

Hadoop

Yarn

Map Reduce

HDFS

Input & Output Formats

Misc

Quiz

Reference: Replication

Reference: Partitioning

Conclusion

Summary

Summary