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⚠️ Development for this project has been moved to this repo managed by TU Delft's data managment group

Holistic Schema Matching at Scale

This repository contains the implementation of the holistic schema matching system detailed in my master thesis at TU Delft.

Install

Install using docker-compose

To install docker-compose follow the official instructions. The next step is to build the required containers (client, engine) by running:

docker-compose build

NOTE: For easier setup of Minio create a folder in the projects root named minio-volume and add folders (buckets) with the data you like in there to instantly load them to the system.

Install in minikube

To install minikube follow the official instructions.

NOTE: You will also need to enable the ingress addon by running: minikube addons enable ingress

At first, you have two options, either pull the two required images (client, engine) build by us:

docker pull kpsarakis/schema-matching-engine:latest
docker pull kpsarakis/schema-matching-client:latest

or build them yourself by running

docker build -t kpsarakis/schema-matching-engine:latest ./engine
docker build -t kpsarakis/schema-matching-client:latest --build-arg REACT_APP_SERVER_ADDRESS=/api ./client

Then you need to install Helm by following the official instructions. Once installed run the following commands to deploy a Redis cluster, a Minio cluster and RAbbitMQ (tune their parameters to your liking by going in the helm-config folder in each respective file):

helm repo add bitnami https://charts.bitnami.com/bitnami
helm repo update

helm install -f helm-config/minio-helm-values.yaml minio bitnami/minio
helm install -f helm-config/redis-helm-values.yaml redis bitnami/redis
helm install -f helm-config/rabbitmq-helm-values.yaml rabbitmq bitnami/rabbitmq

The final step is to deploy the client, server, celery worker, flower (celery cluster monitoring), and the ingress service. At first change the configurations of those deployments in the k8s folder (or leave the defaults) and then run the following command to apply them all:

cd k8s/
kubectl apply -f .

Install in a kubernetes cluster

Assuming that you have created a kubernetes cluster somewhere and have the kubectl command configured go in the helm-config and k8s folders to change the deployment configurations to match your use-case then run:

./deploy-charts.sh
cd k8s/
kubectl apply -f .

This will create all the system's components within the cluster and also add a nginx load balancer to handle incoming traffic.

Run

Run with docker-compose

To run the system with docker compose:

docker-compose up

then go to:

  • localhost:3000 to access the UI.
  • localhost:5555 to access the celery cluster monitoring tool Flower.
  • localhost:5000 to access the systems api.
  • localhost:9000 to access Minio.
  • localhost:15672 to access RabbitMQ.

Run with minikube

To access the system deployed with Minikube at first get the IP by running:

minikube ip

then you can access the UI by going to that address, and the api by writing that address with the /api suffix.

If you want to access a specific service run the following command:

minikube service $(SERVICE_NAME)

e.g. for the flower service:

minikube service flower-service

NOTE: The names can be found by running kubectl get svc

NOTE: To access the services deployed by Helm use the instructions given after their deployment.

Run with a kubernetes cluster

The cluster case is similar to Minikube, you have to get the external IP of the nginx load balancer instead of Minikube's and access the UI and api in the same way. For the rest of the services follow either the Helm or your providers port-forwarding instructions.

Repo structure

  • client Module containing the React implementation of the system's UI.

  • engine Module containing the schema matching engine and the backend of the system.

  • env_files Folder containing example env files for the docker-compose.

  • helm-config Folder containing the configuration of the redis, rabbitmq and ingress-nginx charts.

  • k8s Folder containing the kubernetes deployments, apps and services for the client, server, celery worker, flower (celery cluster monitoring), and the ingress service.