AmoghAtreya commented on code in PR #42609:
URL: https://github.com/apache/superset/pull/42609#discussion_r3688670842
##########
superset/utils/pandas_postprocessing/resample.py:
##########
@@ -46,6 +171,20 @@ def resample(
_("Resample method should be in ") + ", ".join(RESAMPLE_METHOD) +
"."
)
+ tz = df.index.tz
+ df = _pad_to_time_range(
+ df,
+ _coerce_bound(time_range_start, tz),
+ _coerce_bound(time_range_end, tz),
+ )
+ # An empty frame with no time-range anchors has nothing to bin. Returning
+ # early keeps the DatetimeIndex intact; ``resample`` on a zero-length index
+ # would otherwise degrade it to an object Index.
+ if df.empty:
+ return df
+
+ _validate_bucket_count(df.index.min(), df.index.max(), rule)
Review Comment:
Just fixed that!
Here is how I was able to resolve it:
* **Scoped Bucket Validation:** Scoped `_validate_bucket_count` so it
strictly executes on the padded path (when `time_range_start` or
`time_range_end` is supplied). Plain `resample()` operations on un-bounded
historical data are left untouched.
* **Raised & Configurable Cap:** Raised `MAX_RESAMPLE_BUCKETS` to `50_000`
in `superset/config.py` and made it configurable via `current_app.config`
(following the existing fallback pattern used for Prophet).
* **Documentation:** Added an entry to `UPDATING.md` documenting the new
`MAX_RESAMPLE_BUCKETS` configuration option.
* **Test Coverage:** Added and updated unit tests verifying that:
- Bounded queries exceeding the 50k limit raise
`InvalidPostProcessingError`.
- Unbounded queries over large historical ranges (e.g. daily points from
1990 to 2020 spanning >10,000 buckets) execute successfully without raising
errors.
All 22 resample unit tests are passing as intended.
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