kosiew commented on code in PR #16589:
URL: https://github.com/apache/datafusion/pull/16589#discussion_r2177077207
##########
datafusion/physical-expr-adapter/README.md:
##########
@@ -0,0 +1,14 @@
+# DataFusion Physical Expression Adapter
+
+This crate provides physical expression schema adaptation utilities for
DataFusion that allow adapting a `PhysicalExpr` to different schema types.
+This handles cases such as `lit(SclarValue::Int32(123)) = int64_column` by
rewriting it to `lit(SclarValue::Int32(123)) = cast(int64_column, 'Int32')`
Review Comment:
```suggestion
This handles cases such as `lit(ScalarValue::Int32(123)) = int64_column` by
rewriting it to `lit(ScalarValue::Int32(123)) = cast(int64_column, 'Int32')`
```
##########
datafusion/physical-expr-adapter/Cargo.toml:
##########
@@ -0,0 +1,30 @@
+[package]
+name = "datafusion-physical-expr-adapter"
+description = "Physical expression schema adaptation utilities for DataFusion"
+keywords = ["datafusion", "query", "sql"]
+readme = "README.md"
+version = { workspace = true }
+edition = { workspace = true }
+homepage = { workspace = true }
+repository = { workspace = true }
+license = { workspace = true }
+authors = { workspace = true }
+rust-version = { workspace = true }
+
+[lib]
+name = "datafusion_physical_expr_adapter"
+path = "src/lib.rs"
+
+[dependencies]
+arrow = { workspace = true }
+datafusion-common = { workspace = true }
+datafusion-expr = { workspace = true }
+datafusion-functions = { workspace = true }
+datafusion-physical-expr = { workspace = true }
+datafusion-physical-expr-common = { workspace = true }
+itertools = { workspace = true }
+
+[dev-dependencies]
+datafusion-expr = { workspace = true }
Review Comment:
Not required as it is already included in dependencies
##########
datafusion/physical-expr-adapter/src/schema_rewriter.rs:
##########
@@ -97,13 +101,111 @@ impl<'a> PhysicalExprSchemaRewriter<'a> {
&self,
expr: Arc<dyn PhysicalExpr>,
) -> Result<Transformed<Arc<dyn PhysicalExpr>>> {
+ if let Some(transformed) =
self.try_rewrite_struct_field_access(&expr)? {
+ return Ok(Transformed::yes(transformed));
+ }
+
if let Some(column) = expr.as_any().downcast_ref::<Column>() {
return self.rewrite_column(Arc::clone(&expr), column);
}
Ok(Transformed::no(expr))
}
+ fn try_rewrite_struct_field_access(
Review Comment:
The new try_rewrite_struct_field_access handles missing struct fields by
returning Null. I tried adding a test case for nested structs (e.g., a.b.c) to
ensure recursive behavior but it failed.
```rust
#[test]
fn test_rewrite_nested_struct_missing_field() {
let physical_schema = Schema::new(vec![Field::new(
"nested",
DataType::Struct(
vec![Field::new(
"a",
DataType::Struct(vec![Field::new("b", DataType::Utf8,
true)].into()),
true,
)]
.into(),
),
true,
)]);
let logical_schema = Schema::new(vec![Field::new(
"nested",
DataType::Struct(
vec![Field::new(
"a",
DataType::Struct(
vec![
Field::new("b", DataType::Utf8, true),
Field::new("c", DataType::Int32, true),
]
.into(),
),
true,
)]
.into(),
),
true,
)]);
let rewriter = PhysicalExprSchemaRewriter::new(&physical_schema,
&logical_schema);
let column_expr = Arc::new(Column::new("nested", 0));
let result = rewriter.rewrite(column_expr).unwrap();
let expected = Arc::new(CastExpr::new(
Arc::new(Column::new("nested", 0)),
DataType::Struct(
vec![Field::new(
"a",
DataType::Struct(
vec![
Field::new("b", DataType::Utf8, true),
Field::new("c", DataType::Int32, true),
]
.into(),
),
true,
)]
.into(),
),
None,
)) as Arc<dyn PhysicalExpr>;
assert_eq!(result.to_string(), expected.to_string());
}
```
```text
called `Result::unwrap()` on an `Err` value: Execution("Cannot cast column
'nested' from 'Struct(a Struct(b Utf8))' (physical data type) to 'Struct(a
Struct(b Utf8, c Int32))' (logical data type)")
```
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