andygrove commented on code in PR #1073:
URL: https://github.com/apache/datafusion-comet/pull/1073#discussion_r1853910995
##########
native/spark-expr/src/list.rs:
##########
@@ -413,14 +426,297 @@ impl PartialEq<dyn Any> for GetArrayStructFields {
}
}
+#[derive(Debug, Hash)]
+pub struct ArrayInsert {
+ src_array_expr: Arc<dyn PhysicalExpr>,
+ pos_expr: Arc<dyn PhysicalExpr>,
+ item_expr: Arc<dyn PhysicalExpr>,
+ legacy_negative_index: bool,
+}
+
+impl ArrayInsert {
+ pub fn new(
+ src_array_expr: Arc<dyn PhysicalExpr>,
+ pos_expr: Arc<dyn PhysicalExpr>,
+ item_expr: Arc<dyn PhysicalExpr>,
+ legacy_negative_index: bool,
+ ) -> Self {
+ Self {
+ src_array_expr,
+ pos_expr,
+ item_expr,
+ legacy_negative_index,
+ }
+ }
+}
+
+impl PhysicalExpr for ArrayInsert {
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn data_type(&self, input_schema: &Schema) -> DataFusionResult<DataType> {
+ match self.src_array_expr.data_type(input_schema)? {
+ DataType::List(field) => Ok(DataType::List(field)),
+ DataType::LargeList(field) => Ok(DataType::LargeList(field)),
+ data_type => Err(DataFusionError::Internal(format!(
+ "Unexpected data type in ArrayInsert: {:?}",
+ data_type
+ ))),
+ }
+ }
+
+ fn nullable(&self, input_schema: &Schema) -> DataFusionResult<bool> {
+ self.src_array_expr.nullable(input_schema)
+ }
+
+ fn evaluate(&self, batch: &RecordBatch) -> DataFusionResult<ColumnarValue>
{
+ let pos_value = self
+ .pos_expr
+ .evaluate(batch)?
+ .into_array(batch.num_rows())?;
+
+ // Spark supports only IntegerType (Int32):
+ //
https://github.com/apache/spark/blob/branch-3.5/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala#L4737
+ if !matches!(pos_value.data_type(), DataType::Int32) {
+ return Err(DataFusionError::Internal(format!(
+ "Unexpected index data type in ArrayInsert: {:?}, expected
type is Int32",
+ pos_value.data_type()
+ )));
+ }
+
+ // Check that src array is actually an array and get it's value type
+ let src_value = self
+ .src_array_expr
+ .evaluate(batch)?
+ .into_array(batch.num_rows())?;
+ let src_element_type = match src_value.data_type() {
+ DataType::List(field) => field.data_type(),
+ DataType::LargeList(field) => field.data_type(),
+ data_type => {
+ return Err(DataFusionError::Internal(format!(
+ "Unexpected src array type in ArrayInsert: {:?}",
+ data_type
+ )))
+ }
Review Comment:
That's a good question. I wonder if the existing code for LargeList is
actually being tested. It would be interesting to try removing it and see if
there are any regressions. It makes sense to only handle List if Spark only
supports i32 indexes.
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