Guess whose first Pluralsight course was released today?
It’s been an incredible journey shooting my first Pluralsight course. I’ve certainly learned a great deal throughout the process.
For the last month I’ve been recording away and trying to get my first course ready (“Pig Latin: Getting Started“), learning all the tips and tricks of Camtasia, setting up my own microphone, etc. I’ve had no background in setting up quality sound equipment, but I have an awesome Pluralsight editor who helped me through the process.
Finally, all the hard work has paid off and my course is live.
My first course is “Pig Latin: Getting Started.” This course is a beginner course on Pig Latin and tries to help users who are familiar with SQL translate those skills into Apache Hadoop’s Pig application. Typically anywhere you have a Hadoop Distributed File System (HDFS) installed, you will have Pig running as well.
Why Big Data?
Data is consuming the world as we speak, and Big Data developers are in high demand. The median salary for Big Data developers is around $103,000/year. Which makes this a great time to begin a career in Big Data or transition to a Big Data position.
One problem is knowing where to start. When I first started out, I didn’t have a direction or a roadmap for what to learn about the Hadoop Stack.
Do I learn Hive or Pig?
What is Oozie and Zookeeper?
What is this an animal farm?
This is the reason I decided to become a Pluralsight author. I wanted to help others who are just starting out in the Hadoop stack, whether it be job-related, in my case, or simply because you’re ready for a new challenge. Pluralsight gives me that opportunity to reach a huge audience. Together we can make a roadmap to help you navigate through the Hadoop stack.
Why Start with Pig Latin
Why did I start with Pig Latin? There are other applications I could have started with, but Pig Latin is a great first step. I feel Pig offers the right mix of ease-of-use and ability to create more powerful queries to give a better picture of what exactly MapReduce is. In fact, for my first MapReduce job, I used Pig Latin not Java. Before developing with Pig I did have some experience in Java, but it’s not necessary. To learn Pig Latin, all you really need is a basic understanding of SQL, and you can begin to write powerful MapReduce jobs in 10 minutes. Check out this example Pig Script.
If you ready for the challenge to conquer the Hadoop stack, then let’s get started with Pig Latin. Pig Latin: Getting Started will take you through the steps
- Setting up a Hadoop development environment
- Comparing Java MapReduce to Pig Latin
- Loading and Storing Data
- Examples on where to find Data
- Using Pig from the Grunt Shell
- Writing User Defined Function
Checkout the course to find out more about my journey into MapReduce and the Pig Grunt shell.