Comments (4)
henryharbeck
commented on August 27, 2024
The expressions are all evaluated in parallel to increase performance. This means each expression must be valid on its own.
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stinodego
commented on August 27, 2024
This is intended. We do more work than needed, but we can do it in parallel.
You're seeing an error due to this change:
#16841
Add null_on_oob=True to your get calls and you won't see an error anymore.
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barak1412
commented on August 27, 2024
Thanks!
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ritchie46
commented on August 27, 2024
If we count cpu cycles we don't do more work than needed. This allows us to vectorize the expressions. If we would execute them concurrently this would be super branchy and not very optimizable.
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Related Issues (20)
- Unexpected results occur when using the head(1) expression in the select method.
- Add cumulative n_unique HOT 1
- Series constructor with NumPy datetime64 scalar returns incorrect results
- Request for new method argmax_horizontal HOT 4
- `pl.struct` inside `list.eval` produces different dtype if fields are named
- Add `Expr.scatter` HOT 3
- Example code for `group_by` iteration is wrong HOT 1
- `unpivot()` on an empty DataFrame creates two empty `variable` columns
- SQL expression panics on invalid query HOT 2
- Make series raw display output to not use single quotes to be consistent with the DataFrame raw display outputs. HOT 9
- ParquetWriter<CloudWriter> hangs when uploading to S3
- When using `.implode().list` in `GroupBy.agg`, the return type is list, not the original type of the value. HOT 2
- `Series.search_sorted` gives wrong answer when using expression arguments HOT 4
- Panic occurring when using streaming and limit with Parquet
- `Expr.replace` and `Expr.replace_strict` set "NO_DEFAULT" as a value HOT 1
- Parquet files cannot be read from pre-signed S3 URLs due to S3 forbidding HTTP HEAD HOT 8
- Wrong result when filtering categorical using `.is_in` in `scan_parquet` HOT 2
- `.over()` fails with `.get`. HOT 6
- Don't disable coalesce when joining on expressions HOT 3
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