This project implements an end-to-end tech stack for a data platform

follow Data Lake-House architecture, there are main interfaces of this platform:

• Distributed query/execution engine: Spark Thrift Server
• Stream processing: Kafka
• Storage: HDFS
• Data mart: ClickHouse
• Orchestration: Airflow
• Main file format: Parquet with Snappy compression
• Warehouse table format: Hive and Iceberg

How-to-run will be uploaded later

First run:

1. Change the variable IS_RESUME in ./services/metastore/docker-compose.yml to False

2. Create docker network docker network create default_net

3. Docker up bash start_all_service.sh

After finishing all the above steps, change IS_RESUME back to True then rerun start all service