Coding with Java Collections
Being able to code productively with Java Collections is an essential skill needed to create robust, bug-free, and performant applications.
This lab is designed to deepen your Java Collections knowledge. You will be required to complete the following Java coding exercise:
- Exercise 1 - Comparators: Complete the Comparator code required to implement a custom sorting algorithm used to order a deck of cards
- Exercise 2 - SimpleGame: Complete the Collection code required to implement a simple interactive console-based card game
- Exercise 3 - UsingCollections: Complete the collection based code required to read in a Movie dataset stored on the filesystem and implement various querying capabilities exposed as a service
Note: Each exercise is supplied with a fully completed solution code for reference when required.
Upon completion of this lab, you will be able to:
- Be able to work confidently with Java Collections
- Implement custom sorting algorithms using Comparators
- Understand the benefits of working with Java Collections and associated Interfaces
- Run and debug the Java code and examine the results that are printed to the console
- Be comfortable with using a browser-based IDE
This lab will start with the following AWS resources provisioned automatically for you:
- A single EC2 instance, named ide.java.platform.instance, which will have a public IP address attached. This instance will host a web-based Java IDE (based on the Visual Code editor).
To achieve the lab end state, you will be walked through the process of:
- Using your local browser, access the web-based Java IDE served from the ide.java.platform.instance
- Completing the following lab exercises:
- Exercise 1 - Comparators
- Exercise 2 - SimpleGame
- Exercise 3 - UsingCollections
June 16th, 2018 - Optimized creation of lab resources to reduce the time it takes to access the browser IDE by 60%.
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).