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The following commit(s) were added to refs/heads/main by this push:
new d4820d1719 fix: log metadata differences when comparing physical and
logical schema (#19070)
d4820d1719 is described below
commit d4820d17194af029657d6d98fc8d609058f9e5ee
Author: Adam Curtis <[email protected]>
AuthorDate: Wed Dec 3 12:13:00 2025 -0500
fix: log metadata differences when comparing physical and logical schema
(#19070)
## Which issue does this PR close?
<!--
We generally require a GitHub issue to be filed for all bug fixes and
enhancements and this helps us generate change logs for our releases.
You can link an issue to this PR using the GitHub syntax. For example
`Closes #123` indicates that this PR will close issue #123.
-->
- Closes #19069
## Rationale for this change
Differences in physical/logical schema metadata can cause aggregate
physical planning to fail, but these differences are not shown in the
error output.
### Previous message
```
Error while planning query: Internal error: Physical input schema should be
the same as the one converted from logical input schema. Differences: .`
```
### Example of updated message
```
Physical input schema should be the same as the one converted from logical
input schema. Differences:
- field metadata at index 0 [usage_idle]: (physical)
{"iox::column::type": "iox::column_type::field::float"} vs (logical) {}
- field metadata at index 1 [usage_system]: (physical)
{"iox::column::type": "iox::column_type::field::float"} vs (logical) {}.
```
<!--
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in the issue then this section is not needed.
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your changes and offer better suggestions for fixes.
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## What changes are included in this PR?
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is sometimes worth providing a summary of the individual changes in this
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## Are these changes tested?
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Yes
## Are there any user-facing changes?
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updated before approving the PR.
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Minor improvements to error messages.
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---
datafusion/core/src/physical_planner.rs | 244 ++++++++++++++++++++++++++++++++
1 file changed, 244 insertions(+)
diff --git a/datafusion/core/src/physical_planner.rs
b/datafusion/core/src/physical_planner.rs
index 9e4c78a3d0..a942b5de41 100644
--- a/datafusion/core/src/physical_planner.rs
+++ b/datafusion/core/src/physical_planner.rs
@@ -687,6 +687,17 @@ impl DefaultPhysicalPlanner {
)
{
let mut differences = Vec::new();
+
+ if physical_input_schema.metadata()
+ != physical_input_schema_from_logical.metadata()
+ {
+ differences.push(format!(
+ "schema metadata differs: (physical) {:?} vs
(logical) {:?}",
+ physical_input_schema.metadata(),
+ physical_input_schema_from_logical.metadata()
+ ));
+ }
+
if physical_input_schema.fields().len()
!= physical_input_schema_from_logical.fields().len()
{
@@ -716,6 +727,15 @@ impl DefaultPhysicalPlanner {
if physical_field.is_nullable() &&
!logical_field.is_nullable() {
differences.push(format!("field nullability at
index {} [{}]: (physical) {} vs (logical) {}", i, physical_field.name(),
physical_field.is_nullable(), logical_field.is_nullable()));
}
+ if physical_field.metadata() !=
logical_field.metadata() {
+ differences.push(format!(
+ "field metadata at index {} [{}]: (physical)
{:?} vs (logical) {:?}",
+ i,
+ physical_field.name(),
+ physical_field.metadata(),
+ logical_field.metadata()
+ ));
+ }
}
return internal_err!("Physical input schema should be the
same as the one converted from logical input schema. Differences: {}",
differences
.iter()
@@ -3921,4 +3941,228 @@ digraph {
Ok(())
}
+
+ // --- Tests for aggregate schema mismatch error messages ---
+
+ use crate::catalog::TableProvider;
+ use datafusion_catalog::Session;
+ use datafusion_expr::TableType;
+
+ /// A TableProvider that returns schemas for logical planning vs physical
planning.
+ /// Used to test schema mismatch error messages.
+ #[derive(Debug)]
+ struct MockSchemaTableProvider {
+ logical_schema: SchemaRef,
+ physical_schema: SchemaRef,
+ }
+
+ #[async_trait]
+ impl TableProvider for MockSchemaTableProvider {
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn schema(&self) -> SchemaRef {
+ Arc::clone(&self.logical_schema)
+ }
+
+ fn table_type(&self) -> TableType {
+ TableType::Base
+ }
+
+ async fn scan(
+ &self,
+ _state: &dyn Session,
+ _projection: Option<&Vec<usize>>,
+ _filters: &[Expr],
+ _limit: Option<usize>,
+ ) -> Result<Arc<dyn ExecutionPlan>> {
+ Ok(Arc::new(NoOpExecutionPlan::new(Arc::clone(
+ &self.physical_schema,
+ ))))
+ }
+ }
+
+ /// Attempts to plan a query with potentially mismatched schemas.
+ async fn plan_with_schemas(
+ logical_schema: SchemaRef,
+ physical_schema: SchemaRef,
+ query: &str,
+ ) -> Result<Arc<dyn ExecutionPlan>> {
+ let provider = MockSchemaTableProvider {
+ logical_schema,
+ physical_schema,
+ };
+ let ctx = SessionContext::new();
+ ctx.register_table("test", Arc::new(provider)).unwrap();
+
+ ctx.sql(query).await.unwrap().create_physical_plan().await
+ }
+
+ #[tokio::test]
+ // When schemas match, planning proceeds past the schema_satisfied_by
check.
+ // It then panics on unimplemented error in NoOpExecutionPlan.
+ #[should_panic(expected = "NoOpExecutionPlan")]
+ async fn test_aggregate_schema_check_passes() {
+ let schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+
+ plan_with_schemas(
+ Arc::clone(&schema),
+ schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap();
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_metadata() {
+ let logical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+ let physical_schema = Arc::new(
+ Schema::new(vec![Field::new("c1", DataType::Int32, false)])
+ .with_metadata(HashMap::from([("key".into(),
"value".into())])),
+ );
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ assert_contains!(err.to_string(), "schema metadata differs");
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_field_count() {
+ let logical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+ let physical_schema = Arc::new(Schema::new(vec![
+ Field::new("c1", DataType::Int32, false),
+ Field::new("c2", DataType::Int32, false),
+ ]));
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ assert_contains!(err.to_string(), "Different number of fields");
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_field_name() {
+ let logical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+ let physical_schema = Arc::new(Schema::new(vec![Field::new(
+ "different_name",
+ DataType::Int32,
+ false,
+ )]));
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ assert_contains!(err.to_string(), "field name at index");
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_field_type() {
+ let logical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+ let physical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int64,
false)]));
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ assert_contains!(err.to_string(), "field data type at index");
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_field_nullability() {
+ let logical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+ let physical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
true)]));
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ assert_contains!(err.to_string(), "field nullability at index");
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_field_metadata() {
+ let logical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32,
false)]));
+ let physical_schema =
+ Arc::new(Schema::new(vec![Field::new("c1", DataType::Int32, false)
+ .with_metadata(HashMap::from([("key".into(),
"value".into())]))]));
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ assert_contains!(err.to_string(), "field metadata at index");
+ }
+
+ #[tokio::test]
+ async fn test_aggregate_schema_mismatch_multiple() {
+ let logical_schema = Arc::new(Schema::new(vec![
+ Field::new("c1", DataType::Int32, false),
+ Field::new("c2", DataType::Utf8, false),
+ ]));
+ let physical_schema = Arc::new(
+ Schema::new(vec![
+ Field::new("c1", DataType::Int64, true)
+ .with_metadata(HashMap::from([("key".into(),
"value".into())])),
+ Field::new("c2", DataType::Utf8, false),
+ ])
+ .with_metadata(HashMap::from([(
+ "schema_key".into(),
+ "schema_value".into(),
+ )])),
+ );
+
+ let err = plan_with_schemas(
+ logical_schema,
+ physical_schema,
+ "SELECT count(*) FROM test GROUP BY c1",
+ )
+ .await
+ .unwrap_err();
+
+ // Verify all applicable error fragments are present
+ let err_str = err.to_string();
+ assert_contains!(&err_str, "schema metadata differs");
+ assert_contains!(&err_str, "field data type at index");
+ assert_contains!(&err_str, "field nullability at index");
+ assert_contains!(&err_str, "field metadata at index");
+ }
}
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