andygrove commented on PR #14283:
URL: https://github.com/apache/datafusion/pull/14283#issuecomment-2614024359
> How do you handle types mismatch issue? Does Comet has another type
handling logic to find the correct types for datafusion physical plan?
We map Spark types to Arrow types. For UDFs, we call DataFusion's
`coerce_types` function. There are some other places where we add casts when
needed.
This is the DataFusion plan that was failing.
```
ProjectionExec: expr=[CASE WHEN Cast [data_type: Int32, timezone:
America/Los_Angeles, child: col_0@0, eval_mode: Legacy] IS NULL THEN NULL ELSE
array_remove(make_array(Cast [data_type: Int32, timezone: America/Los_Angeles,
child: col_0@0, eval_mode: Legacy], Cast [data_type: Int32, timezone:
America/Los_Angeles, child: col_1@1, eval_mode: Legacy], col_2@2), Cast
[data_type: Int32, timezone: America/Los_Angeles, child: col_0@0, eval_mode:
Legacy]) END as col_0]
CometFilterExec: col_0@0 IS NULL
ScanExec: source=[CometScan parquet (unknown)], schema=[col_0: Int8,
col_1: Int16, col_2: Int32]
```
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