KillrChat

A hand's on exercise for Cassandra 2.1

Introduction

This hands-on will make you, step by step with TDD, create a working chat application using

• Apache Cassandra™
• Achilles
• Spring Boot
• AngularJS + UI Bootstrap

The hands-on will focus on the data modelling part, you need to

1. understand the data model (tables)
2. implement the services to make the tests pass using Achilles

All the front-end, as well as the REST resource and all Spring configuration config and other glue code is provided as a convenience so that participants can focus solely on the data modelling and service layer

For object mapping, we use Achilles which provides many tools to make development more effective and easier. We'll use the JUnit rule support from Achilles to start an embedded Cassandra in memory for unit testing.

Once all the exercises are done, we can have some fun using the real chat !

Running the application

Warning! You'll need a recent and decent browser (no IE8) to make the chat front-end work: IE10, Chrome, FireFox ...

Development mode

To run the application in the development mode:

killrchat> mvn clean test
killrchat> mvn spring-boot:run -Pdev

When running the application in dev mode, Achilles will start an embedded Cassandra server and create the following data folders:

1. /tmp/killrchat_cassandra/data
2. /tmp/killrchat_cassandra/commitlog
3. /tmp/killrchat_cassandra/saved_caches

You can change those default values in the src/main/resources/config/application.yml file

Then connect to the chat by opening your browser at http://localhost:8080/killrchat/index.html

Production mode

To run the application in the production mode:

killrchat> mvn clean test
killrchat> mvn spring-boot:run -Pprod

When running the application in dev mode, Achilles will connect to an existing Cassandra server. You can configure the server host and port in the the src/main/resources/config/application.yml file. By default Achilles will execute the src/main/resources/cassandra/schema_creation.cql script to create the killrchat keyspace and appropriate tables

Then connect to the chat by opening your browser at http://localhost:8080/killrchat/index.html

To deploy the application in multiple back-end servers, you will need to reconfigure the messaging system in the ChatRoomResource and MessageResource. For the hand's on, we use an in-memory messaging system but for production you'd probably want to plugin a distributed messaging broker like RabbitMQ.

Packaging the application

To package KillrChat and build a stand-alone Java jar archive, type mvn package. It will generate a killrchat-1.0.jar file in the target folder

Exercises

• Exercise 1: manage accounts
• Exercise 2: manage chat rooms
• Exercise 3: manage participants joining and leaving rooms
• Exercise 4: manage chat messages

Remarks

The data model for chat room message is still not perfect because it is a wide row. Typically the partition will grow over time and performance will suffer.

The solution is to use bucketing techniques but it is an advanced data modelling topic, far beyond the goal of this hands-on

Alternatively, we can use the DateTieredCompactionStrategy to make reading recent messages faster.