[Core] Refactoring the pre/post projection logic based on Spark Rule
- Dominant language
- Scala
- Stars
- 1.6k
- Forks
- 657
- Avg merge
- 2d 14h
- Merged PRs (30d)
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Description
### Description
Due to the limitation that only the project operator in the native engine supports evaluating expressions, there is currently a lot of code logic in the transformer to handle inputs with expressions. To address this, we can refactor the code by unifying the handling logic using Spark Rule. We can extract the pre/post projection logic from transformers like agg, sort, etc., and create a separate project transformer. This approach can also be combined with the project collapse optimization #3937 I previously implemented, which allows for merging redundant project operations to improve performance.
Contributor guide
Research direction
Start by reading the existing pre/post projection handling in the agg and sort transformers, then review the project-collapse optimization described in #3937. The work is complete when a separate project transformer unifies this logic through the Spark Rule approach and supports collapsing redundant project operations.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- scala
- Domain
- backend, performance
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100