I’m trying to add caching functionality in my scalable spark cluster on Docker. I am able to add redis to my Docker container, but that doesn’t add redis-CLI or any other useful tools that I need. And there are some redis-cache projects on PyPi, but they are very old and not compatible with python3.

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    Just add another runstep to your mutlipart docker build that adds and configures path for redis-cli and a copy operation that imports the configuration. Rinse repeat for whatever else you need, then use copy --from to compose your final container.

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    But redis image (https://hub.docker.com/_/redis) totally comes with redis-cli, all you need is exec into the container and type `redis-cli`. What exactly are you trying to achieve?
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    You dont simply add redis to you existing docker image. You use a separate redis container
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    @ebrithil I though storing data in a container is a bad practice. Because you lose the data when the container shuts down.
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    @srpatil who said you store data inside the container? Usually you use either volume or bind mounts for persistent data
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