res-life opened a new issue, #17027:
URL: https://github.com/apache/iceberg/issues/17027
### Apache Iceberg version
1.9.0
### Query engine
Spark
### Please describe the bug 🐞
This is a follow-up to #12915, which was automatically closed as stale
without a resolution.
The decimal truncate transform can increase the precision of a negative
boundary value beyond the precision of the source decimal type. For example,
truncating a valid `decimal(7,3)` value with width 10 maps:
```
-9999.999 -> -10000.000
```
The input has precision 7, while the transformed value requires precision 8.
A valid source value can therefore produce a partition value that cannot be
represented by the transform's declared decimal type.
A minimal Spark SQL reproduction is:
```sql
CREATE TABLE sample (a decimal(7,3))
USING iceberg
PARTITIONED BY (truncate(10, a));
INSERT INTO sample VALUES (-9999.999);
```
The write fails when Iceberg serializes the transformed partition value:
```
Caused by: java.lang.IllegalArgumentException:
Cannot write value as decimal(7,3), too large: -10000.000
at
org.apache.iceberg.util.DecimalUtil.toReusedFixLengthBytes(DecimalUtil.java:39)
at
org.apache.iceberg.avro.ValueWriters$DecimalWriter.write(ValueWriters.java:345)
```
The same behavior occurs for other precisions and scales when a negative
value near the minimum boundary is rounded down by the truncate transform, such
as the `decimal(5,4)` example in #12915.
Iceberg should handle this boundary case without allowing an unrepresentable
transformed value to reach the metadata writer. This may require defining how
decimal truncate behaves when the mathematical result exceeds the source
precision.
### Willingness to contribute
- [ ] I can contribute a fix for this bug independently
- [ ] I would be willing to contribute a fix for this bug with guidance from
the Iceberg community
- [ ] I cannot contribute a fix for this bug at this time
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