feat(datafusion): implement the project node to add the partition columns

crates/iceberg/src/arrow/mod.rs

@@ -28,7 +28,8 @@ pub mod delete_file_loader;
 pub(crate) mod delete_filter;
 
 mod reader;
-pub(crate) mod record_batch_projector;
+/// RecordBatch projection utilities
+pub mod record_batch_projector;
 pub(crate) mod record_batch_transformer;
 mod value;
 

crates/iceberg/src/arrow/record_batch_projector.rs

@@ -20,13 +20,16 @@ use std::sync::Arc;
 use arrow_array::{ArrayRef, RecordBatch, StructArray, make_array};
 use arrow_buffer::NullBuffer;
 use arrow_schema::{DataType, Field, FieldRef, Fields, Schema, SchemaRef};
+use parquet::arrow::PARQUET_FIELD_ID_META_KEY;
 
+use crate::arrow::schema::schema_to_arrow_schema;
 use crate::error::Result;
+use crate::spec::Schema as IcebergSchema;
 use crate::{Error, ErrorKind};
 
 /// Help to project specific field from `RecordBatch`` according to the fields id.
-#[derive(Clone, Debug)]
-pub(crate) struct RecordBatchProjector {
+#[derive(Clone, Debug, PartialEq, Eq)]
+pub struct RecordBatchProjector {
     // A vector of vectors, where each inner vector represents the index path to access a specific field in a nested structure.
     // E.g. [[0], [1, 2]] means the first field is accessed directly from the first column,
     // while the second field is accessed from the second column and then from its third subcolumn (second column must be a struct column).
@@ -77,6 +80,46 @@ impl RecordBatchProjector {
         })
     }
 
+    /// Create RecordBatchProjector using Iceberg schema.
+    ///
+    /// This constructor converts the Iceberg schema to Arrow schema with field ID metadata,
+    /// then uses the standard field ID lookup for projection.
+    ///
+    /// # Arguments
+    /// * `iceberg_schema` - The Iceberg schema for field ID mapping  
+    /// * `target_field_ids` - The field IDs to project
+    pub fn from_iceberg_schema(
+        iceberg_schema: Arc<IcebergSchema>,
+        target_field_ids: &[i32],
+    ) -> Result<Self> {
+        let arrow_schema_with_ids = Arc::new(schema_to_arrow_schema(&iceberg_schema)?);
+
+        let field_id_fetch_func = |field: &Field| -> Result<Option<i64>> {
+            if let Some(value) = field.metadata().get(PARQUET_FIELD_ID_META_KEY) {
+                let field_id = value.parse::<i32>().map_err(|e| {
+                    Error::new(
+                        ErrorKind::DataInvalid,
+                        "Failed to parse field id".to_string(),
+                    )
+                    .with_context("value", value)
+                    .with_source(e)
+                })?;
+                Ok(Some(field_id as i64))
+            } else {
+                Ok(None)
+            }
+        };
+
+        let searchable_field_func = |_field: &Field| -> bool { true };
+
+        Self::new(
+            arrow_schema_with_ids,
+            target_field_ids,
+            field_id_fetch_func,
+            searchable_field_func,
+        )
+    }
+
     fn fetch_field_index<F1, F2>(
         fields: &Fields,
         index_vec: &mut Vec<usize>,
@@ -129,7 +172,7 @@ impl RecordBatchProjector {
     }
 
     /// Do projection with columns
-    pub(crate) fn project_column(&self, batch: &[ArrayRef]) -> Result<Vec<ArrayRef>> {
+    pub fn project_column(&self, batch: &[ArrayRef]) -> Result<Vec<ArrayRef>> {
         self.field_indices
             .iter()
             .map(|index_vec| Self::get_column_by_field_index(batch, index_vec))
@@ -166,6 +209,7 @@ mod test {
     use arrow_schema::{DataType, Field, Fields, Schema};
 
     use crate::arrow::record_batch_projector::RecordBatchProjector;
+    use crate::spec::{NestedField, PrimitiveType, Schema as IcebergSchema, Type};
     use crate::{Error, ErrorKind};
 
     #[test]
@@ -293,4 +337,25 @@ mod test {
             RecordBatchProjector::new(schema.clone(), &[3], field_id_fetch_func, |_| true);
         assert!(projector.is_ok());
     }
+
+    #[test]
+    fn test_from_iceberg_schema() {
+        let iceberg_schema = IcebergSchema::builder()
+            .with_schema_id(0)
+            .with_fields(vec![
+                NestedField::required(1, "id", Type::Primitive(PrimitiveType::Int)).into(),
+                NestedField::required(2, "name", Type::Primitive(PrimitiveType::String)).into(),
+                NestedField::optional(3, "age", Type::Primitive(PrimitiveType::Int)).into(),
+            ])
+            .build()
+            .unwrap();
+
+        let projector =
+            RecordBatchProjector::from_iceberg_schema(Arc::new(iceberg_schema), &[1, 3]).unwrap();
+
+        assert_eq!(projector.field_indices.len(), 2);
+        assert_eq!(projector.projected_schema_ref().fields().len(), 2);
+        assert_eq!(projector.projected_schema_ref().field(0).name(), "id");
+        assert_eq!(projector.projected_schema_ref().field(1).name(), "age");
+    }
 }

crates/iceberg/src/transform/mod.rs

@@ -29,7 +29,7 @@ mod truncate;
 mod void;
 
 /// TransformFunction is a trait that defines the interface for all transform functions.
-pub trait TransformFunction: Send + Sync {
+pub trait TransformFunction: Send + Sync + std::fmt::Debug {
     /// transform will take an input array and transform it into a new array.
     /// The implementation of this function will need to check and downcast the input to specific
     /// type.

crates/integrations/datafusion/src/physical_plan/mod.rs

@@ -18,9 +18,11 @@
 pub(crate) mod commit;
 pub(crate) mod expr_to_predicate;
 pub(crate) mod metadata_scan;
+pub(crate) mod project;
 pub(crate) mod scan;
 pub(crate) mod write;
 
 pub(crate) const DATA_FILES_COL_NAME: &str = "data_files";
 
+pub use project::project_with_partition;
 pub use scan::IcebergTableScan;