SparkML Determine if action is needed for Utility transformers
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Enhancement
RumbleML
- Dominant language
- Java
- Stars
- 246
- Forks
- 85
- Avg merge
- 6d 1h
- Merged PRs (30d)
- 22
Description
org.apache.spark.ml.feature.ColumnPruner and org.apache.spark.ml.feature.VectorAttributeRewriter are defined as utility methods of SparkML. Conclusively determine whether these need to be exposed to the end-user. If so, implement tests for them. If not, hide them from the user
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 reading the linked Apache Spark API documentation for ColumnPruner and VectorAttributeRewriter, then trace how these utility transformers are exposed or used in RumbleDB. Done means reaching a supported decision: add tests if they should be user-facing, or hide them if they should remain internal.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- java, spark
- Domain
- machine-learning
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100