Fix: Schema projection order mismatch from table/file schema (#5541)

Looks like I only solved a subset of the issue with #5436

The test I added failed before the fix.

---------

Signed-off-by: Frederic Branczyk <[email protected]>

Author: brancz

vortex-datafusion/src/persistent/opener.rs

@@ -230,6 +230,11 @@ impl FileOpener for VortexOpener {
                 DataFusionError::Execution(format!("Failed to convert file schema to arrow: {e}"))
             })?);
 
+            // Compute the logical file schema by merging physical file types with logical table types.
+            // This schema has the same field names as logical_schema, but with physical types from the file.
+            let logical_file_schema =
+                compute_logical_file_schema(&physical_file_schema, &logical_schema);
+
             if let Some(expr_adapter_factory) = expr_adapter_factory {
                 let partition_values = partition_fields
                     .iter()
@@ -241,13 +246,8 @@ impl FileOpener for VortexOpener {
                 // for schema evolution and divergence between the table's schema and individual files.
                 filter = filter
                     .map(|filter| {
-                        let logical_file_schema = compute_logical_file_schema(
-                            &physical_file_schema.clone(),
-                            &logical_schema,
-                        );
-
                         let expr = expr_adapter_factory
-                            .create(logical_file_schema, physical_file_schema.clone())
+                            .create(logical_file_schema.clone(), physical_file_schema.clone())
                             .with_partition_values(partition_values)
                             .rewrite(filter)?;
 
@@ -257,59 +257,25 @@ impl FileOpener for VortexOpener {
                     })
                     .transpose()?;
 
-                predicate_file_schema = physical_file_schema.clone();
+                predicate_file_schema = physical_file_schema;
             }
 
-            // Create the initial mapping from physical file schema to projected schema.
-            // This gives us the field reordering and tells us which logical schema fields
-            // to select.
-            let (_schema_mapping, adapted_projections) =
-                schema_adapter.map_schema(&physical_file_schema)?;
+            // Use the pre-created schema adapter to map logical_file_schema to projected_schema.
+            // Since logical_file_schema has the same field names as logical_schema (which the adapter
+            // was created with), this works correctly and gives us the projection indices.
+            let (schema_mapping, adapted_projections) =
+                schema_adapter.map_schema(&logical_file_schema)?;
 
-            // Build the Vortex projection expression using the adapted projections.
-            // This will reorder the fields to match the target order.
+            // Build the Vortex projection expression using field names from logical_file_schema
             let fields = adapted_projections
                 .iter()
-                .map(|idx| {
-                    let field = logical_schema.field(*idx);
+                .map(|&idx| {
+                    let field = logical_file_schema.field(idx);
                     FieldName::from(field.name().as_str())
                 })
                 .collect::<Vec<_>>();
             let projection_expr = select(fields, root());
 
-            // After Vortex applies the projection, the batch will have fields in the target
-            // order (matching adapted_projections), but with the physical file types.
-            // We need a second schema mapping for type casting only, not reordering.
-            // Build a schema that represents what Vortex will return: fields in target order
-            // with physical types.
-            let projected_physical_fields: Vec<Field> = adapted_projections
-                .iter()
-                .map(|&idx| {
-                    let logical_field = logical_schema.field(idx);
-                    let field_name = logical_field.name();
-
-                    // Find this field in the physical schema to get its physical type
-                    physical_file_schema
-                        .field_with_name(field_name)
-                        .map(|phys_field| {
-                            Field::new(
-                                field_name,
-                                merge_field_types(phys_field, logical_field),
-                                phys_field.is_nullable(),
-                            )
-                        })
-                        .unwrap_or_else(|_| (*logical_field).clone())
-                })
-                .collect();
-
-            let projected_physical_schema =
-                Arc::new(arrow_schema::Schema::new(projected_physical_fields));
-
-            // Create a second mapping from the projected physical schema (what Vortex returns)
-            // to the final projected schema. This mapping will handle type casting without reordering.
-            let (batch_schema_mapping, _) =
-                schema_adapter.map_schema(&projected_physical_schema)?;
-
             // We share our layout readers with others partitions in the scan, so we can only need to read each layout in each file once.
             let layout_reader = match layout_reader.entry(file_meta.object_meta.location.clone()) {
                 Entry::Occupied(mut occupied_entry) => {
@@ -404,7 +370,7 @@ impl FileOpener for VortexOpener {
                     ))))
                 })
                 .try_flatten()
-                .map(move |batch| batch.and_then(|b| batch_schema_mapping.map_batch(b)))
+                .map(move |batch| batch.and_then(|b| schema_mapping.map_batch(b)))
                 .boxed();
 
             Ok(stream)
@@ -870,4 +836,81 @@ mod tests {
 
         Ok(())
     }
+
+    #[tokio::test]
+    // Minimal reproducing test for the schema projection bug.
+    // Before the fix, this would fail with a cast error when the file schema
+    // and table schema have different field orders and we project a subset of columns.
+    async fn test_projection_bug_minimal_repro() -> anyhow::Result<()> {
+        let object_store = Arc::new(InMemory::new()) as Arc<dyn ObjectStore>;
+        let file_path = "/path/file.vortex";
+
+        // File has columns in order: a, b, c with simple types
+        let batch = record_batch!(
+            ("a", Int32, vec![Some(1)]),
+            ("b", Utf8, vec![Some("test")]),
+            ("c", Int32, vec![Some(2)])
+        )
+        .unwrap();
+        let data_size = write_arrow_to_vortex(object_store.clone(), file_path, batch).await?;
+
+        // Table schema has columns in DIFFERENT order: c, a, b
+        // and different types that require casting (Utf8 -> Dictionary)
+        let table_schema = Arc::new(Schema::new(vec![
+            Field::new("c", DataType::Int32, true),
+            Field::new("a", DataType::Int32, true),
+            Field::new(
+                "b",
+                DataType::Dictionary(Box::new(DataType::UInt32), Box::new(DataType::Utf8)),
+                true,
+            ),
+        ]));
+
+        // Project columns [0, 2] from table schema, which should give us: c, b
+        // Before the fix, the schema adapter would get confused about which fields
+        // to select from the file, causing incorrect type mappings.
+        let projection = vec![0, 2];
+
+        let opener = VortexOpener {
+            session: SESSION.clone(),
+            object_store: object_store.clone(),
+            projection: Some(projection.into()),
+            filter: None,
+            file_pruning_predicate: None,
+            expr_adapter_factory: Some(Arc::new(DefaultPhysicalExprAdapterFactory) as _),
+            schema_adapter_factory: Arc::new(DefaultSchemaAdapterFactory),
+            partition_fields: vec![],
+            file_cache: VortexFileCache::new(1, 1, SESSION.clone()),
+            logical_schema: table_schema.clone(),
+            batch_size: 100,
+            limit: None,
+            metrics: Default::default(),
+            layout_readers: Default::default(),
+            has_output_ordering: false,
+        };
+
+        // This should succeed and return the correctly projected and cast data
+        let data = opener
+            .open(
+                make_meta(file_path, data_size),
+                PartitionedFile::new(file_path.to_string(), data_size),
+            )?
+            .await?
+            .try_collect::<Vec<_>>()
+            .await?;
+
+        // Verify the columns are in the right order and have the right values
+        use datafusion::arrow::util::pretty::pretty_format_batches_with_options;
+        let format_opts = FormatOptions::new().with_types_info(true);
+        assert_snapshot!(pretty_format_batches_with_options(&data, &format_opts)?.to_string(), @r"
+        +-------+--------------------------+
+        | c     | b                        |
+        | Int32 | Dictionary(UInt32, Utf8) |
+        +-------+--------------------------+
+        | 2     | test                     |
+        +-------+--------------------------+
+        ");
+
+        Ok(())
+    }
 }