A facelift of the Software Engineering project from Findwise, originally conducted in 2016. The tagcloud is a website where the hashtag usage is displayed in a tag cloud, divided by which political parties the account is following:

The project is divided in a bunch of different microservices.

• Index service
• Search service
• Frontend service

The index service is responsible for fetching tweets and inserting them into Elastic. The service is divided into the following tasks:

• FollowerFetcher
• TweetFetcher
• TweetIndexer

The follower fetcher is written in golang and is populating the followers folder inside the config folder. There, files will be found that contains a list with the followers for the account with the same ID as the file name.

The Tweet fetcher is fetching tweets from the accounts specified in the files inside the followers folder, found in the config folder. The data is sent to RabbitMQ

The indexing function is consuming from RabbitMQ and inserting the data into Elastic

The search service is serving the endpoints for the frontend and is delivering data from Elastic

The frontend service is the static files that forms the frontend seen by the users and is communicating with the search service in order to retrieve data

To use RabbitMQ, start the container with

docker run -d --hostname my-rabbit --name some-rabbit -p 15672:15672 -p 5671:5671 -p 5672:5672 rabbitmq:3-management

The ports are used to map ports between the container and your local machine

http://localhost:15672

Default Username/Password

guest/guest

To pull the container

docker pull docker.elastic.co/elasticsearch/elasticsearch:6.3.1

Start the container with

docker run -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:6.3.1