MrGranday opened a new pull request, #17314:
URL: https://github.com/apache/datafusion/pull/17314
## Which issue does this PR close?
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- Closes #17297
## Rationale for this change
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Why are you proposing this change? If this is already explained clearly in
the issue then this section is not needed.
Explaining clearly why changes are proposed helps reviewers understand your
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Currently, `DataFrame.cache()` always performs eager caching using an
in-memory `MemTable`.
This works fine in local mode but causes problems in distributed
environments (e.g., Ballista),
where caching should be deferred until distributed execution.
This PR introduces a configuration flag (`local_cache`) to support both
eager and lazy caching.
## What changes are included in this PR?
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There is no need to duplicate the description in the issue here but it is
sometimes worth providing a summary of the individual changes in this PR.
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- Added `LogicalPlan::Cache { id, lineage }` for lazy caching.
- Updated `DataFrame.cache()`:
- If `local_cache = true` → uses current eager caching with `MemTable`.
- If `local_cache = false` → returns a `LogicalPlan::Cache` node for lazy
evaluation.
- Extended physical planner to handle `LogicalPlan::Cache`.
## Are these changes tested?
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- Builds on existing logical/physical plan tests.
- No new dedicated distributed caching tests are included in this PR.
## Are there any user-facing changes?
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updated before approving the PR.
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- Yes, a new configuration option:
- `datafusion.execution.local_cache = true` (default) → eager caching.
- `datafusion.execution.local_cache = false` → lazy caching with
`LogicalPlan::Cache`.
This is a **non-breaking change** because the default behavior remains
unchanged.
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