andygrove commented on PR #65:
URL: https://github.com/apache/datafusion-spark/pull/65#issuecomment-6823887733
Thanks, the fix looks right to me: hoisting `with_data_type` so it covers
the non-ANSI `unary` branch too is exactly what was missing. Two small
non-blocking nits on the tests.
1. The new tests check values but never assert the output type. A result
with the wrong precision or scale could still print the same values. The
`DOUBLE` cast catches that for scale 2, but not for the zero and negative scale
cases. An `arrow_typeof` check would pin the type directly, for example:
```
query TTTT
SELECT arrow_typeof(negative(d32)), arrow_typeof(negative(d64)),
arrow_typeof(negative(d128)), arrow_typeof(negative(d256))
FROM decimal_negative_scales LIMIT 1;
----
Decimal32(7, -2) Decimal64(10, 0) Decimal128(10, -2) Decimal256(42, 0)
```
2. `decimal_negative` and `decimal_negative_scales` are only dropped in the
ANSI section, so they stay around for the rest of the non-ANSI tests. It's
harmless, but dropping them right after their last use in each section would
keep the file tidier.
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