Hadoop MapReduce - System's view

Here are videos that I created to explain Hadoop's MapReduce framework from system's perspective. As a disclaimer, this video is at an abstraction that I liked, which means it might not be suitable for general Computer Science audience. If however, you have some experience with Hadoop, you should be fine. I have skipped over lot of Hadoop's features for simplicity and succinctness, like HDFS, Hadoop I/O, setting up/administering Hadoop cluster and writing Hadoop programs (and various high-level languages/tools that use Hadoop).

1. Job Submission at the client side


2. Job submission at the JobTracker side

3. Task Scheduling

4. Task Creation

5. Map execution

6. Reduce execution

Slides: PDF, Keynote

Video tutorial on reinforcement learning

This video tutorial is based on a talk I gave at my Comp 650 class and hence assumes that the audience knows a little about Markov Decision Processes and Partially Observable Markov Decision Processes. If you are unfamiliar with them, I recommend that you at least read through their wikipedia pages before going through this tutorial. Also, I suggest that you view this video on youtube, because the embedded video given below is cropped.


If you have any suggestions, comments or questions, please feel free to email me :)

PDF slides