sam-1112 commented on code in PR #5215:
URL: https://github.com/apache/datafusion-comet/pull/5215#discussion_r3964426068
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native/spark-expr/src/predicate_funcs/rlike.rs:
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@@ -225,4 +245,122 @@ mod tests {
let result =
expr.evaluate(&RecordBatch::new_empty(Arc::new(Schema::empty())));
assert!(result.is_err());
}
+
+ #[test]
+ fn test_rlike_string_array_layouts() {
+ let pattern = "R[a-z]+";
+ let cases: Vec<(DataType, ArrayRef)> = vec![
+ (
+ DataType::Utf8,
+ Arc::new(StringArray::from(vec![Some("Rose"), None,
Some("Daisy")])),
+ ),
+ (
+ DataType::LargeUtf8,
+ Arc::new(LargeStringArray::from(vec![
+ Some("Rose"),
+ None,
+ Some("Daisy"),
+ ])),
+ ),
+ (
+ DataType::Utf8View,
+ Arc::new(StringViewArray::from(vec![
+ Some("Rose"),
+ None,
+ Some("Daisy"),
+ ])),
+ ),
+ ];
+
+ for (data_type, array) in cases {
+ let schema = Arc::new(Schema::new(vec![Field::new("s", data_type,
true)]));
+ let batch = RecordBatch::try_new(Arc::clone(&schema),
vec![array]).unwrap();
+ let expr = RLike::try_new(Arc::new(Column::new("s", 0)),
pattern).unwrap();
+ assert_bool_results(
+ expr.evaluate(&batch).unwrap(),
+ &[Some(true), None, Some(false)],
+ );
+ }
+ }
+
+ #[test]
+ fn test_rlike_string_array_no_nulls() {
+ let schema = Arc::new(Schema::new(vec![Field::new("s", DataType::Utf8,
false)]));
+ let batch = RecordBatch::try_new(
+ Arc::clone(&schema),
+ vec![Arc::new(StringArray::from(vec!["Rose", "Daisy"]))],
+ )
+ .unwrap();
+
+ let expr = RLike::try_new(Arc::new(Column::new("s", 0)),
"R[a-z]+").unwrap();
+ let ColumnarValue::Array(arr) = expr.evaluate(&batch).unwrap() else {
+ panic!("expected array result");
+ };
+ // All-valid input must not allocate a null buffer (filter fast path).
Review Comment:
Agreed. I reworded the comment to describe preserving the null-buffer-free
output shape and avoiding the unnecessary validity allocation, without
referring to the filter fast path.
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