liurenjie1024 commented on code in PR #1602: URL: https://github.com/apache/iceberg-rust/pull/1602#discussion_r2375255862
########## crates/integrations/datafusion/src/physical_plan/project.rs: ########## @@ -0,0 +1,511 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +//! Utilities for calculating partition values for Iceberg tables. +//! +//! This module provides functions to calculate partition values from record batches +//! based on Iceberg partition specifications. These utilities are used when writing +//! data to partitioned Iceberg tables. + +use std::sync::Arc; + +use datafusion::arrow::array::{ArrayRef, RecordBatch, StructArray}; +use datafusion::arrow::datatypes::{ + DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef, +}; +use datafusion::common::Result as DFResult; +use datafusion::error::DataFusionError; +use iceberg::spec::{PartitionSpec, Schema}; + +use crate::to_datafusion_error; + +/// Column name for the combined partition values struct +#[allow(dead_code)] +pub(crate) const PARTITION_VALUES_COLUMN: &str = "_iceberg_partition_values"; Review Comment: ```suggestion pub(crate) const PARTITION_VALUES_COLUMN: &str = "_partition"; ``` I would suggest to follow java's conversion to have a meta column module for it: https://github.com/apache/iceberg/blob/bb32b90c4ad63f037f0bda197cc53fb08c886934/core/src/main/java/org/apache/iceberg/MetadataColumns.java#L57 ########## crates/integrations/datafusion/src/physical_plan/project.rs: ########## @@ -0,0 +1,511 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +//! Utilities for calculating partition values for Iceberg tables. +//! +//! This module provides functions to calculate partition values from record batches +//! based on Iceberg partition specifications. These utilities are used when writing +//! data to partitioned Iceberg tables. + +use std::sync::Arc; + +use datafusion::arrow::array::{ArrayRef, RecordBatch, StructArray}; +use datafusion::arrow::datatypes::{ + DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef, +}; +use datafusion::common::Result as DFResult; +use datafusion::error::DataFusionError; +use iceberg::spec::{PartitionSpec, Schema}; + +use crate::to_datafusion_error; + +/// Column name for the combined partition values struct +#[allow(dead_code)] +pub(crate) const PARTITION_VALUES_COLUMN: &str = "_iceberg_partition_values"; + +/// Create an output schema by adding a single partition values struct column to the input schema. +/// Returns the original schema unchanged if the table is unpartitioned. +#[allow(dead_code)] +pub(crate) fn create_schema_with_partition_columns( + input_schema: &ArrowSchema, + partition_spec: &PartitionSpec, + table_schema: &Schema, +) -> DFResult<ArrowSchemaRef> { + if partition_spec.is_unpartitioned() { + return Ok(Arc::new(input_schema.clone())); + } + + let mut fields: Vec<Arc<Field>> = input_schema.fields().to_vec(); + + let partition_struct_type = partition_spec + .partition_type(table_schema) + .map_err(to_datafusion_error)?; + + let arrow_struct_type = + iceberg::arrow::type_to_arrow_type(&iceberg::spec::Type::Struct(partition_struct_type)) + .map_err(to_datafusion_error)?; + + fields.push(Arc::new(Field::new( + PARTITION_VALUES_COLUMN, + arrow_struct_type, + false, // Partition values are generally not null + ))); + + Ok(Arc::new(ArrowSchema::new(fields))) +} + +/// Calculate partition values for a record batch and return as a single struct array. +/// Returns None if the table is unpartitioned. +/// +/// # Arguments +/// * `batch` - The record batch to calculate partition values for +/// * `partition_spec` - The partition specification defining the partition fields +/// * `table_schema` - The Iceberg table schema +/// * `expected_partition_type` - The expected Arrow struct type for the partition values +#[allow(dead_code)] +pub(crate) fn calculate_partition_values( Review Comment: How about replace this part as a `PhysicalExpr`? ########## crates/integrations/datafusion/src/physical_plan/project.rs: ########## @@ -0,0 +1,511 @@ +// Licensed to the Apache Software Foundation (ASF) under one +// or more contributor license agreements. See the NOTICE file +// distributed with this work for additional information +// regarding copyright ownership. The ASF licenses this file +// to you under the Apache License, Version 2.0 (the +// "License"); you may not use this file except in compliance +// with the License. You may obtain a copy of the License at +// +// http://www.apache.org/licenses/LICENSE-2.0 +// +// Unless required by applicable law or agreed to in writing, +// software distributed under the License is distributed on an +// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +// KIND, either express or implied. See the License for the +// specific language governing permissions and limitations +// under the License. + +//! Utilities for calculating partition values for Iceberg tables. +//! +//! This module provides functions to calculate partition values from record batches +//! based on Iceberg partition specifications. These utilities are used when writing +//! data to partitioned Iceberg tables. + +use std::sync::Arc; + +use datafusion::arrow::array::{ArrayRef, RecordBatch, StructArray}; +use datafusion::arrow::datatypes::{ + DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef, +}; +use datafusion::common::Result as DFResult; +use datafusion::error::DataFusionError; +use iceberg::spec::{PartitionSpec, Schema}; + +use crate::to_datafusion_error; + +/// Column name for the combined partition values struct +#[allow(dead_code)] +pub(crate) const PARTITION_VALUES_COLUMN: &str = "_iceberg_partition_values"; + +/// Create an output schema by adding a single partition values struct column to the input schema. +/// Returns the original schema unchanged if the table is unpartitioned. +#[allow(dead_code)] +pub(crate) fn create_schema_with_partition_columns( + input_schema: &ArrowSchema, + partition_spec: &PartitionSpec, + table_schema: &Schema, +) -> DFResult<ArrowSchemaRef> { + if partition_spec.is_unpartitioned() { + return Ok(Arc::new(input_schema.clone())); + } + + let mut fields: Vec<Arc<Field>> = input_schema.fields().to_vec(); + + let partition_struct_type = partition_spec + .partition_type(table_schema) + .map_err(to_datafusion_error)?; + + let arrow_struct_type = + iceberg::arrow::type_to_arrow_type(&iceberg::spec::Type::Struct(partition_struct_type)) + .map_err(to_datafusion_error)?; + + fields.push(Arc::new(Field::new( + PARTITION_VALUES_COLUMN, + arrow_struct_type, + false, // Partition values are generally not null + ))); + + Ok(Arc::new(ArrowSchema::new(fields))) +} + +/// Calculate partition values for a record batch and return as a single struct array. +/// Returns None if the table is unpartitioned. +/// +/// # Arguments +/// * `batch` - The record batch to calculate partition values for +/// * `partition_spec` - The partition specification defining the partition fields +/// * `table_schema` - The Iceberg table schema +/// * `expected_partition_type` - The expected Arrow struct type for the partition values +#[allow(dead_code)] +pub(crate) fn calculate_partition_values( + batch: &RecordBatch, + partition_spec: &PartitionSpec, + table_schema: &Schema, + expected_partition_type: &DataType, +) -> DFResult<Option<ArrayRef>> { + if partition_spec.is_unpartitioned() { + return Ok(None); + } + + let batch_schema = batch.schema(); + let mut partition_values = Vec::with_capacity(partition_spec.fields().len()); + + let expected_struct_fields = match expected_partition_type { + DataType::Struct(fields) => fields.clone(), + _ => { + return Err(DataFusionError::Internal( + "Expected partition type must be a struct".to_string(), + )); + } + }; + + for pf in partition_spec.fields() { + let source_field = table_schema.field_by_id(pf.source_id).ok_or_else(|| { + DataFusionError::Internal(format!( + "Source field not found with id {} when calculating partition values", + pf.source_id + )) + })?; + + let field_path = find_field_path(table_schema, source_field.id)?; + let index_path = resolve_arrow_index_path(batch_schema.as_ref(), &field_path)?; + + let source_column = extract_column_by_index_path(batch, &index_path)?; + + let transform_fn = iceberg::transform::create_transform_function(&pf.transform) + .map_err(to_datafusion_error)?; + let partition_value = transform_fn + .transform(source_column) + .map_err(to_datafusion_error)?; + + partition_values.push(partition_value); + } + + let struct_array = StructArray::try_new( + expected_struct_fields, + partition_values, + None, // No null buffer for the struct array itself + ) + .map_err(|e| DataFusionError::ArrowError(e, None))?; + + Ok(Some(Arc::new(struct_array))) +} + +/// Extract a column from a record batch by following an index path. +/// The index path specifies the column indices to traverse for nested structures. +#[allow(dead_code)] +fn extract_column_by_index_path(batch: &RecordBatch, index_path: &[usize]) -> DFResult<ArrayRef> { Review Comment: Could we reuse `RecordBatchProjection`? -- This is an automated message from the Apache Git Service. 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