TEAStream

Introduction

For more information on this project, you can read this series of articles on the Bleckwen's Medium tech blog:

Twitter sentiment analysis in real time, part 1.html (available)
Twitter sentiment analysis in real time, part 2.html (available)
Twitter sentiment analysis in real time, part 3.html (available)

Time to deploy the project!

0. Useful scripts

If you want to skip ahead the next parts, you can use the .sh files:

build.sh: create the .jar files and build the docker images locally.
start.sh: launch the app.
start-all.sh: both build.sh and start.sh combined.

In this case, jump to part 5.

1. Create the .jar

You will need 2 .jar files created through sbt assembly:

sbt kafkatwitter/assembly
sbt flink/assembly

The files are located respectively in deploy/producer-job and deploy/flink-jobs.

2. Create the Docker images

Go to the deploy directory:

cd deploy/

There are 4 images to build in total:

Busybox

cd busybox/
docker build . -t busybox

Web App

cd web-app/
docker build . -t flask

Flink Job

cd flink-jobs/
docker build . -t flink-job

Producer Job

cd producer-job/
docker build . -t producer-anon-job

3. Add Twitter credentials

Open the .env file with your favorite text editor and write down your credentials: CONSUMER_KEY, CONSUMER_SECRET, ACCESS_TOKEN, ACCESS_TOKEN_SECRET.

4. Launch the project

docker-compose up

If you want to run the process in the background, add the -d option.

5. Use the App

Open localhost:5000 in your web browser. Type the word(s) you want to track and the app will do the rest.
You can look at the results on Kibana at localhost:5601.

run sudo sysctl -w vm.max_map_counts=262144 if elasticsearch returns max virtual memory areas vm.max_map_count [65530] likely too low, increase to at least [262144].

For index pattern, you can use flink-index. The dashboard presented in the articles is available at deploy/export.json and can be imported.

6. Other tools

You can check the flink job with the flink dashboard: localhost:8081.
You can check available topics with the kafka-ui: localhost:8000.
You can check available connectors with the connect-ui: localhost:8003.

7. Stop the app

docker-compose down

The services will be shut down and the containers removed.

Alternatively, you can run stop.sh if you used one of the previous scripts.

License

License: CC BY-NC-SA 4.0

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

All notebooks are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License.

A summary of this license is as follows.

You are free to:

Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material

The licensor cannot revoke these freedoms as long as you follow the license terms.

Under the following terms:

Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

NonCommercial — You may not use the material for commercial purposes.

ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

BleckwenAI/teastream