Support streaming/incremental fitting
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- Dominant language
- Rust
- Stars
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- Forks
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- Avg merge
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- Merged PRs (30d)
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Description
Memory is limited and using swap is painfully slow to fit massive amounts of data. There is discussion of incremental fitting in https://github.com/rust-ml/linfa/issues/8 years ago but I cannot find incremental_fit in the code. Spark has https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.mllib.regression.StreamingLinearRegressionWithSGD.html which also helps with limited memory with streaming data.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the existing fitting APIs and the earlier incremental fitting discussion in issue #8; the issue does not name implementation files or tests. Compare the desired behavior with Spark's StreamingLinearRegressionWithSGD reference. Done means defining and implementing a clear streaming or incremental fitting approach for massive datasets without requiring all data in memory.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- rust
- Domain
- data-engineering, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100