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A tool to find podcast metadata over an external api, store them, get their rss feeds and run ETL using Airflow, Kafka, Spark, and Cassandra. The particular Cassandra distribution used is Elassandra, which allows seamless integration with Elasticsearch. Displayed using a Gatsby app, served using Flask

RyanQuey/java-podcast-processor

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java-podcast-processor

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.

image

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See README files in subdirectories for how to setup and use this tool (though some are out of date).

Related Links

Start Everything

  • 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)
  • Open up React Gatsby project (serving searchkit) via flask app at http://localhost:5000/search

Features

Results Displayed Using Searchkit

image

Setup

  • install Docker compose
  • Start everything with: ./scripts/startup/start-every-compose.sh
  • View from Zeppelin using these Zeppelin notebooks.

Development

  • If made changes to java code and want to rebuild what docker is running, run

    ./scripts/startup/start-every-compose.sh rebuild

Debugging

  • 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

Released under MIT License

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:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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A tool to find podcast metadata over an external api, store them, get their rss feeds and run ETL using Airflow, Kafka, Spark, and Cassandra. The particular Cassandra distribution used is Elassandra, which allows seamless integration with Elasticsearch. Displayed using a Gatsby app, served using Flask

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