Real World Vagrant - Build an Apache Spark Development Env!
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- Simply run a single command on your desktop, go for a coffee, and come back with a running distributed environment for cluster deployment
- Ability to automate the installation of software across multiple Virtual Machines
For testing or playing around with Apache Spark. Don't contaminate your computer! Keep your PC or Mac clean by simply building and running a custom spark development environment within a Virtual Machine.
Suggested Spark Udemy curriculum courses to follow ...
Here I show you have to simply modify your Vagrant file to switch to a graphical Centos (RHEL) Linux Virtual Machine. We will navigate briefly within this Virtual Machine. This is the image we will be configuring. Amazing that you have a Graphical O/S in under 1.2GB!
Hard to believe... This new environment will now boot up in under 2.5 minutes (On my machine anyway!) We also execute the Spark example within the ScalaIDE. Ensuring everything works. You can now give this final box and vagrant file to your colleague and they can have a Spark Environment up and running in under 2.5 minutes.
- Basic programming or scripting experience is required.
- You will need a desktop PC and an Internet connection. The course is created with Windows in mind.
- The software needed for this course is freely available
- This Course is based on top of my previous course - "Real World Vagrant For Distributed Computing"
- You will require a computer with a Virtualization chipset support - VT-x. Most computers purchased over the last five years should be good enough
- Optional : Some exposure to Linux and/or Bash shell environment
- 64-bit Windows operating system required (Would recommend Windows 7 or above)
- This course is not recommened if you have no desire to work with/in distributed computing
Note : This course is built on top of the "Real World Vagrant For Distributed Computing - Toyin Akin" course
This course enables you to package a complete Spark Development environment into your own custom 2.3GB vagrant box.
Once built you no longer need to manipulate your Windows machine in order to get a fully fledged Spark environment to work. With the final solution, you can boot up a complete Apache Spark environment in under 3 minutes!!
Install any version of Spark you prefer. We have codified for 1.6.2 or 2.0.1. but it's pretty easy to extend this for a new version.
Why Apache Spark ...
Apache Spark run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk.
Apache Spark has an advanced DAG execution engine that supports cyclic data flow and in-memory computing.
Apache Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells.
Apache Spark can combine SQL, streaming, and complex analytics.
Apache Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application.
- Software engineers who want to expand their skills into the world of distributed computing
- Developers who want to write/test their code against Scala / Spark