Fokko opened a new pull request, #5926:
URL: https://github.com/apache/iceberg/pull/5926
While writing tests for Python, I noticed some unreachable code. This also
allows us to simplify the logic here by inlining the `allValuesAreNull`
function.
The `allValuesAreNull` check is redundant for the `isNan` check.
Because we first check if there are NaN values:
```java
@Override
public <T> Boolean isNaN(BoundReference<T> ref) {
int pos = Accessors.toPosition(ref.accessor());
if (stats.get(pos).containsNaN() != null && !stats.get(pos).containsNaN())
{
return ROWS_CANNOT_MATCH;
}
if (allValuesAreNull(stats.get(pos), ref.type().typeId())) {
return ROWS_CANNOT_MATCH; // Unreachable code
}
return ROWS_MIGHT_MATCH;
}
```
And then we do the same in the `allValuesAreNull`:
```java
private boolean allValuesAreNull(PartitionFieldSummary summary, Type.TypeID
typeId) {
// containsNull encodes whether at least one partition value is null,
// lowerBound is null if all partition values are null
boolean allNull = summary.containsNull() && summary.lowerBound() == null;
if (allNull && (Type.TypeID.DOUBLE.equals(typeId) ||
Type.TypeID.FLOAT.equals(typeId))) {
// floating point types may include NaN values, which we check
separately.
// In case bounds don't include NaN value, containsNaN needs to be
checked against.
allNull = summary.containsNaN() != null && !summary.containsNaN();
}
return allNull;
}
```
Since the `isNan` can only be applied to Floats and Doubles, we always take
the branch. And then we come to the same conclusion.
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