Separate parallel backend from frontend
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python
- Domain
- backend, stream-processing
Research direction
No files or tests are named. Start by tracing how scatter, connect, DaskStream, and node clients interact, then inspect the client API points around submit and loop; done would mean pipeline definitions can be reused across backends with client choice and downstream execution handled consistently.
Written by the indexing model from the issue text.
Description
Recently I've been trying to split my pipelines up into chunks so the chunks can be re-used as much as possible. One issue I foresee running into is that scatter may not work as intended. scatter will send the data to the cluser for processing, but since the downstream nodes are already defined (I'm linking them via connect) they won't properly operate on the data (since they aren't DaskStream nodes).
It seems that it may be beneficial to separate the front end pipeline definition from the decision about which backend is being used, at least at the class level. This would make pipelines more modular since we don't need to re-write the same pipeline for each backend. Additionally this would allow the user executing a pipeline to decide what backend they want/are able to use.
One approach to handle this could be to specify a client for the entire pipeline, where a client mimics some of the dask client API (mostly submit and loop I think). If the client associated with any node is changed/updated then the entire pipeline shifts to use that client. This would also require nodes to know if they are downstream of a scatter but haven't been gathered yet, since then they would know to use the pipeline's client rather than standard local execution (which most likely should be a dummy client). Maybe this can be inspected when the client is set, since it could change during the pipeline build process?
- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 149
- Avg merge
- 17h 39m
- Merged PRs (30d)
- 1
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