Become an Apache Spark Pro in 2024 - Unleash Your Learning
Confusion and overwhelm - the curse of too much information
Aspiring to become a Pro-Level Apache Spark developer can be a daunting goal. One may easily feel overwhelmed and confused about where to start, what to learn and what comes next. Given the complexity of the framework, the sheer flood of information, too detailed documentation or overly simplistic tutorials, we have a hard time deciding our next move.
I'm convinced that it doesn't have to be this way. Actually, as I know from experience, learning can be easy and seamless, and give us a sense of accomplishment. Imagine dedicating 30 minutes to an hour every day to your learning, always knowing you are on track and what to do next. The question is: How can we get there?
A goal without a plan is simply wishful thinking.
The key to a pleasant and successful learning is to have an easy-to-follow and specific step-by-step guide, which you can follow. Therefore, if you want to improve your skills in Apache Spark, I challenge you to start with making a detailed plan for your learning. Assess where you are standing at the moment, and contemplate carefully what you'll need to learn to reach your goal. Research what there is to study and bring all of this into a detailed map.
Craft your Spark learning roadmap
In order to help you do this, I have created this roadmap for you. This is what I use in my coachings and workshops - and it has helped many people like you to become Pro-Level Spark developers. The roadmap contains all milestones, I suggest you to place on your own learning path as well.
Step 1: Learn to use Spark SQL
Start by learning to use the framework - get your hands dirty. Select your development environment, get some sample data (a single file is fine to begin with), and start coding some use-cases.
Step 2: Study internals
Once you have accomplished this, deep-dive into some of the internals. Study and understand the basic concepts of Spark. There are great resources on YouTube and blogs. Take some notes to make sure you reproduce what you have heard.
Step 3: Real-world Spark
Learn how to deploy applications in a real-world cluster environment. Play around with Spark on Docker and together with a cluster manager. Identify and understand the essential configuration parameters and monitor running applications.
Step 4: Performance
One of the most important chapters. Study common performance issues and how to mitigate them. Try to reproduce them with your data or synthetic data. See what you can do about them. After all, you have the knowledge about the internals, so that this shouldn't be much of a deal.
Step 5: Integrate Spark
There is a vast amount of tools you can use together with Spark. Primarily, we integrate Spark applications in a landscape of various data sources. Play around with a few (at least 2), configure Spark to access them and try to read and write data using them. You may also want to deploy an application in your favourite cloud environment.
Step 6: Become Pro
Well, this may be the hardest part. Here's where your actual experience working with Spark comes into play. Only once you have produced some errors or built something in an non-optimal way, you'll understand why it is better to follow some specific patterns. Ask yourself what the traits of high-quality code are, review code from others and learn to become fast in developing.
Get more information
If you want to learn more about each of these steps, subscribe to the "Learn Spark" mailing sequence. Over the course of 6 weeks, you will receive one email per week, which contains a detailed description of each of the milestones and helpful resources and examples. This will not only provide you with helpful information, but also remind you regularly about your goal.
I offer individual live-coaching and have helped many people like you to master this journey. While you indeed can reach your goal on your own, I'd bet you can be much faster with learning from an expert. If you are interested, visit my Spark-Pro Academy.