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 divided into separate Main classes in a single Java jar 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See README files in subdirectories for how to setup and use this tool (though some are out of date).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.
- I recently presented on Kafka with Cassandra for the Cassandra & DataStax DC Meetup using this project for their Cassandra Lunch. The presentation was featured on Anant Corporation's blog.
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Start everything with:
./scripts/startup/start-every-compose.sh- Starts up all services, connecting them using chained docker-compose files.
- Runs shell script to make sure Cassandra and Kafka are successfully started
- Once C* and Kafka are up, runs initializers (e.g., creating kafka topics and ES indices for Elassandra)
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Open up React Gatsby project (serving searchkit) via flask app at http://localhost:5000/search
- install Docker compose
- Start everything with:
./scripts/startup/start-every-compose.sh - View from Zeppelin using these Zeppelin notebooks.
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If made changes to java code and want to rebuild what docker is running, run
./scripts/startup/start-every-compose.sh rebuild
- Can get logs from containers by using
docker logs:- Get logs for running searches:
docker logs -f java-podcast-processor_run-search-per-term_1 - Get logs for RSS feeds:
docker logs -f java-podcast-processor_extract-episodes-per-podcast_1
- Get logs for running searches:
Copyright (c) 2020 Ryan Quey.
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