Personal tool to grab podcast data related to several topics I'm interested in, store them, and process using Airflow, Kafka, Spark, and Cassandra. The particular Cassandra distribution used is Elassandra, which allows seamless integration with Elasticsearch.
Workers are built into separate Java jars and consume and produce to Kafka, in order to distribute the workload across the cluster. Everything is built on top of Docker containers and linked together using docker-compose.
Results displayed using a searchkit interface over React (built using Gatsby), served by a Python Flask app.
See README files in subdirectories for how to setup and use this tool (though some are out of date).
For the related Zeppelin notebooks, see here. For Airflow DAGs source code, see here.
- Start everything with:
./scripts/startup/start-every-compose.sh - Open up React Gatsby project (serving searchkit) via flask app at http://www.local.test:5000/
- install Docker compose
- Start everything with:
./scripts/startup/start-every-compose.sh - View from Zeppelin using these Zeppelin notebooks.
-
If made changes to java code and want to rebuild what docker is running, run
./scripts/startup/start-every-compose.sh rebuild
Copyright (c) 2020 Ryan Quey.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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