zhengruifeng commented on PR #52637:
URL: https://github.com/apache/spark/pull/52637#issuecomment-3413850999
```py
import decimal
from pyspark.sql.types import *
from pyspark.sql.functions import udf, lit, udtf
df = spark.sql("SELECT DOUBLE(1.234) AS v")
@udf(returnType=DecimalType(38, 18))
def f(v: float):
return decimal.Decimal(v)
df.select("*", f("v")).show()
@udf(returnType=DecimalType(38, 18), useArrow=True)
def f2(v: float):
return decimal.Decimal(v)
df.select("*", f2("v")).show()
@udtf(returnType='a: DOUBLE, b: DECIMAL(38, 18)')
class Float2Decimal:
def eval(self, v: float):
yield v, decimal.Decimal(v)
Float2Decimal(lit(1.234)).show()
@udtf(returnType='a: DOUBLE, b: DECIMAL(38, 18)', useArrow=True)
class Float2Decimal2:
def eval(self, v: float):
yield v, decimal.Decimal(v)
Float2Decimal2(lit(1.234)).show()
```
it turns out that this PR happen to also fix the same issue in
arrow-optimized udf/udtf, the `f2` and `Float2Decimal2` also fail with
```
pyarrow.lib.ArrowInvalid: Rescaling Decimal value would cause data loss
```
before this change.
@ueshin @HyukjinKwon @allisonport-db @asl3
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