This component let's the user register terms for analyzing.
- Login to your account to dockerhub:
docker login - From the root of this project, build a new docker image with the respective version:
docker build -t tweetsentimentanalysis/webinterface:0.0.2 -t tweetsentimentanalysis/webinterface:latest . - Run
docker push tweetsentimentanalysis/webinterface:0.0.2to deploy to dockerhub
If you do not want to build the container by your own, you may use the following to get the image from DockerHub:
docker pull tweetsentimentanalysis/webinterface:latest
After you have built the container, you may run it using the following command:
docker run -p 9000:8080 -e REGISTRAR_URL='http://someUrl.toRegistrar.com' -e ELASTICSEARCH_URL='https://some.Url.com' -e AWS_ACCESS_KEY_ID="..." -e AWS_ACCESS_KEY_SECRET="..." tweetsentimentanalysis/webinterface:latest
Use the appropriate URLs as well as AWS credentials with at least the permissions of AmazonSQSReadOnlyAccess, CloudWatchReadOnlyAccesse.
Note, that you also may specify the following environment variables during startup:
AWS_EC2_REGION: The region in which the instances of the autoscaling groups are located, e.g.us-west-2AWS_ANALYZER_AUTO_SCALING_GROUP_NAME: The AWS autoscaling group name of the instances on which tweets get analyzedAWS_PRODUCER_AUTO_SCALING_GROUP_NAME: The AWS autoscaling group name of the instances on which the tweets are pushed to ElasticsearchAWS_FETCHED_TWEETS_SQS_QUEUE_NAME: The AWS SQS Queue name in which the fetched tweets are locatedAWS_ANALYZED_TWEETS_SQS_QUEUE_NAME: The AWS SQS Queue name in which the analyzed tweets are located
In order to clean up, you may want to remove the previously created image and container:
- Run
docker ps -ain order list created containers. - Choose the corresponding container id and invoke
docker stop <ID> && docker rm <ID> - Run
docker imagesto list all created images - Run
docker rmi <ID>with the id of the image to remove it