liurenjie1024 commented on code in PR #1511:
URL: https://github.com/apache/iceberg-rust/pull/1511#discussion_r2209883442
##########
crates/integrations/datafusion/src/table/mod.rs:
##########
@@ -46,6 +50,8 @@ pub struct IcebergTableProvider {
snapshot_id: Option<i64>,
/// A reference-counted arrow `Schema`.
schema: ArrowSchemaRef,
+ /// The catalog that the table belongs to.
+ catalog: Option<Arc<dyn Catalog>>,
Review Comment:
We don't need to make this optional?
##########
crates/iceberg/src/spec/manifest/mod.rs:
##########
@@ -15,7 +15,9 @@
// specific language governing permissions and limitations
// under the License.
+// todo fix encapsulation
mod _serde;
+pub use _serde::*;
Review Comment:
I don't think we should expose this, a better approach is to expose a pub
function to serializa/deserialize to json
##########
crates/integrations/datafusion/src/physical_plan/write.rs:
##########
@@ -0,0 +1,371 @@
+// 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.
+
+use std::any::Any;
+use std::fmt::{Debug, Formatter};
+use std::sync::Arc;
+
+use datafusion::arrow::array::{ArrayRef, RecordBatch, StringArray,
UInt64Array};
+use datafusion::arrow::datatypes::{
+ DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef,
+};
+use datafusion::common::Result as DFResult;
+use datafusion::error::DataFusionError;
+use datafusion::execution::{SendableRecordBatchStream, TaskContext};
+use datafusion::physical_expr::{EquivalenceProperties, Partitioning};
+use datafusion::physical_plan::execution_plan::{Boundedness, EmissionType};
+use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
+use datafusion::physical_plan::{
+ DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
execute_input_stream,
+};
+use futures::StreamExt;
+use iceberg::arrow::schema_to_arrow_schema;
+use iceberg::spec::{DataFileFormat, DataFileSerde, FormatVersion};
+use iceberg::table::Table;
+use iceberg::writer::CurrentFileStatus;
+use iceberg::writer::file_writer::location_generator::{
+ DefaultFileNameGenerator, DefaultLocationGenerator,
+};
+use iceberg::writer::file_writer::{FileWriter, FileWriterBuilder,
ParquetWriterBuilder};
+use parquet::file::properties::WriterProperties;
+use uuid::Uuid;
+
+use crate::to_datafusion_error;
+
+pub(crate) struct IcebergWriteExec {
+ table: Table,
+ input: Arc<dyn ExecutionPlan>,
+ result_schema: ArrowSchemaRef,
+ plan_properties: PlanProperties,
+}
+
+impl IcebergWriteExec {
+ pub fn new(table: Table, input: Arc<dyn ExecutionPlan>, schema:
ArrowSchemaRef) -> Self {
+ let plan_properties = Self::compute_properties(schema.clone());
+
+ Self {
+ table,
+ input,
+ result_schema: Self::make_result_schema(),
+ plan_properties,
+ }
+ }
+
+ /// todo: Copied from scan.rs
+ fn compute_properties(schema: ArrowSchemaRef) -> PlanProperties {
+ // TODO:
+ // This is more or less a placeholder, to be replaced
+ // once we support output-partitioning
+ PlanProperties::new(
+ EquivalenceProperties::new(schema),
+ Partitioning::UnknownPartitioning(1),
+ EmissionType::Incremental,
+ Boundedness::Bounded,
+ )
+ }
+
+ // Create a record batch with count and serialized data files
+ fn make_result_batch(count: u64, data_files: Vec<String>) ->
DFResult<RecordBatch> {
+ let count_array = Arc::new(UInt64Array::from(vec![count])) as ArrayRef;
+ let files_array = Arc::new(StringArray::from(data_files)) as ArrayRef;
+
+ RecordBatch::try_from_iter_with_nullable(vec![
+ ("count", count_array, false),
+ ("data_files", files_array, false),
+ ])
+ .map_err(|e| {
+ DataFusionError::ArrowError(e, Some("Failed to make result
batch".to_string()))
+ })
+ }
+
+ fn make_result_schema() -> ArrowSchemaRef {
Review Comment:
This could be a lazy static field?
##########
crates/integrations/datafusion/src/physical_plan/write.rs:
##########
@@ -0,0 +1,371 @@
+// 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.
+
+use std::any::Any;
+use std::fmt::{Debug, Formatter};
+use std::sync::Arc;
+
+use datafusion::arrow::array::{ArrayRef, RecordBatch, StringArray,
UInt64Array};
+use datafusion::arrow::datatypes::{
+ DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef,
+};
+use datafusion::common::Result as DFResult;
+use datafusion::error::DataFusionError;
+use datafusion::execution::{SendableRecordBatchStream, TaskContext};
+use datafusion::physical_expr::{EquivalenceProperties, Partitioning};
+use datafusion::physical_plan::execution_plan::{Boundedness, EmissionType};
+use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
+use datafusion::physical_plan::{
+ DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
execute_input_stream,
+};
+use futures::StreamExt;
+use iceberg::arrow::schema_to_arrow_schema;
+use iceberg::spec::{DataFileFormat, DataFileSerde, FormatVersion};
+use iceberg::table::Table;
+use iceberg::writer::CurrentFileStatus;
+use iceberg::writer::file_writer::location_generator::{
+ DefaultFileNameGenerator, DefaultLocationGenerator,
+};
+use iceberg::writer::file_writer::{FileWriter, FileWriterBuilder,
ParquetWriterBuilder};
+use parquet::file::properties::WriterProperties;
+use uuid::Uuid;
+
+use crate::to_datafusion_error;
+
+pub(crate) struct IcebergWriteExec {
+ table: Table,
+ input: Arc<dyn ExecutionPlan>,
+ result_schema: ArrowSchemaRef,
+ plan_properties: PlanProperties,
+}
+
+impl IcebergWriteExec {
+ pub fn new(table: Table, input: Arc<dyn ExecutionPlan>, schema:
ArrowSchemaRef) -> Self {
+ let plan_properties = Self::compute_properties(schema.clone());
+
+ Self {
+ table,
+ input,
+ result_schema: Self::make_result_schema(),
+ plan_properties,
+ }
+ }
+
+ /// todo: Copied from scan.rs
+ fn compute_properties(schema: ArrowSchemaRef) -> PlanProperties {
+ // TODO:
+ // This is more or less a placeholder, to be replaced
+ // once we support output-partitioning
+ PlanProperties::new(
+ EquivalenceProperties::new(schema),
+ Partitioning::UnknownPartitioning(1),
+ EmissionType::Incremental,
+ Boundedness::Bounded,
+ )
+ }
+
+ // Create a record batch with count and serialized data files
+ fn make_result_batch(count: u64, data_files: Vec<String>) ->
DFResult<RecordBatch> {
+ let count_array = Arc::new(UInt64Array::from(vec![count])) as ArrayRef;
+ let files_array = Arc::new(StringArray::from(data_files)) as ArrayRef;
+
+ RecordBatch::try_from_iter_with_nullable(vec![
+ ("count", count_array, false),
+ ("data_files", files_array, false),
+ ])
+ .map_err(|e| {
+ DataFusionError::ArrowError(e, Some("Failed to make result
batch".to_string()))
+ })
+ }
+
+ fn make_result_schema() -> ArrowSchemaRef {
+ // Define a schema.
+ Arc::new(ArrowSchema::new(vec![
+ Field::new("data_files", DataType::Utf8, false),
+ Field::new("count", DataType::UInt64, false),
+ ]))
+ }
+}
+
+impl Debug for IcebergWriteExec {
+ fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
+ write!(f, "IcebergWriteExec")
+ }
+}
+
+impl DisplayAs for IcebergWriteExec {
+ fn fmt_as(&self, t: DisplayFormatType, f: &mut Formatter) ->
std::fmt::Result {
+ match t {
+ DisplayFormatType::Default => {
+ write!(f, "IcebergWriteExec: table={}",
self.table.identifier())
+ }
+ DisplayFormatType::Verbose => {
+ write!(
+ f,
+ "IcebergWriteExec: table={}, result_schema={:?}",
+ self.table.identifier(),
+ self.result_schema
+ )
+ }
+ DisplayFormatType::TreeRender => {
+ write!(f, "IcebergWriteExec: table={}",
self.table.identifier())
+ }
+ }
+ }
+}
+
+impl ExecutionPlan for IcebergWriteExec {
+ fn name(&self) -> &str {
+ "IcebergWriteExec"
+ }
+
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn properties(&self) -> &PlanProperties {
+ &self.plan_properties
+ }
+
+ fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>> {
+ vec![]
+ }
+
+ fn with_new_children(
+ self: Arc<Self>,
+ _children: Vec<Arc<dyn ExecutionPlan>>,
+ ) -> DFResult<Arc<dyn ExecutionPlan>> {
+ Ok(self)
+ }
+
+ fn execute(
+ &self,
+ partition: usize,
+ context: Arc<TaskContext>,
+ ) -> DFResult<SendableRecordBatchStream> {
+ let parquet_writer_fut = ParquetWriterBuilder::new(
+ WriterProperties::default(),
+ self.table.metadata().current_schema().clone(),
+ self.table.file_io().clone(),
+ DefaultLocationGenerator::new(self.table.metadata().clone())
+ .map_err(to_datafusion_error)?,
+ // todo filename prefix/suffix should be configurable
+ DefaultFileNameGenerator::new(
+ "datafusion".to_string(),
+ Some(Uuid::now_v7().to_string()),
+ DataFileFormat::Parquet,
+ ),
+ )
+ .build();
+
+ let data = execute_input_stream(
+ Arc::clone(&self.input),
+ Arc::new(
+ schema_to_arrow_schema(self.table.metadata().current_schema())
+ .map_err(to_datafusion_error)?,
+ ),
+ partition,
+ Arc::clone(&context),
+ )?;
+
+ // todo non-default partition spec?
+ let spec_id = self.table.metadata().default_partition_spec_id();
+ let partition_type =
self.table.metadata().default_partition_type().clone();
+ let is_version_1 = self.table.metadata().format_version() ==
FormatVersion::V1;
+
+ let stream = futures::stream::once(async move {
+ let mut writer =
parquet_writer_fut.await.map_err(to_datafusion_error)?;
Review Comment:
We should use `DataFileWriter` rather using `ParquetWriter` directly.
##########
crates/integrations/datafusion/tests/integration_datafusion_test.rs:
##########
@@ -432,3 +433,69 @@ async fn test_metadata_table() -> Result<()> {
Ok(())
}
+
+#[tokio::test]
+async fn test_insert_into() -> Result<()> {
Review Comment:
I'm not a big fan of adding this kind of integration tests. How about adding
sqllogictests?
##########
crates/integrations/datafusion/src/physical_plan/write.rs:
##########
@@ -0,0 +1,371 @@
+// 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.
+
+use std::any::Any;
+use std::fmt::{Debug, Formatter};
+use std::sync::Arc;
+
+use datafusion::arrow::array::{ArrayRef, RecordBatch, StringArray,
UInt64Array};
+use datafusion::arrow::datatypes::{
+ DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef,
+};
+use datafusion::common::Result as DFResult;
+use datafusion::error::DataFusionError;
+use datafusion::execution::{SendableRecordBatchStream, TaskContext};
+use datafusion::physical_expr::{EquivalenceProperties, Partitioning};
+use datafusion::physical_plan::execution_plan::{Boundedness, EmissionType};
+use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
+use datafusion::physical_plan::{
+ DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
execute_input_stream,
+};
+use futures::StreamExt;
+use iceberg::arrow::schema_to_arrow_schema;
+use iceberg::spec::{DataFileFormat, DataFileSerde, FormatVersion};
+use iceberg::table::Table;
+use iceberg::writer::CurrentFileStatus;
+use iceberg::writer::file_writer::location_generator::{
+ DefaultFileNameGenerator, DefaultLocationGenerator,
+};
+use iceberg::writer::file_writer::{FileWriter, FileWriterBuilder,
ParquetWriterBuilder};
+use parquet::file::properties::WriterProperties;
+use uuid::Uuid;
+
+use crate::to_datafusion_error;
+
+pub(crate) struct IcebergWriteExec {
+ table: Table,
+ input: Arc<dyn ExecutionPlan>,
+ result_schema: ArrowSchemaRef,
+ plan_properties: PlanProperties,
+}
+
+impl IcebergWriteExec {
+ pub fn new(table: Table, input: Arc<dyn ExecutionPlan>, schema:
ArrowSchemaRef) -> Self {
+ let plan_properties = Self::compute_properties(schema.clone());
+
+ Self {
+ table,
+ input,
+ result_schema: Self::make_result_schema(),
+ plan_properties,
+ }
+ }
+
+ /// todo: Copied from scan.rs
+ fn compute_properties(schema: ArrowSchemaRef) -> PlanProperties {
+ // TODO:
+ // This is more or less a placeholder, to be replaced
+ // once we support output-partitioning
+ PlanProperties::new(
+ EquivalenceProperties::new(schema),
+ Partitioning::UnknownPartitioning(1),
Review Comment:
The partition number should be same as input
##########
crates/integrations/datafusion/src/physical_plan/write.rs:
##########
@@ -0,0 +1,371 @@
+// 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.
+
+use std::any::Any;
+use std::fmt::{Debug, Formatter};
+use std::sync::Arc;
+
+use datafusion::arrow::array::{ArrayRef, RecordBatch, StringArray,
UInt64Array};
+use datafusion::arrow::datatypes::{
+ DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef,
+};
+use datafusion::common::Result as DFResult;
+use datafusion::error::DataFusionError;
+use datafusion::execution::{SendableRecordBatchStream, TaskContext};
+use datafusion::physical_expr::{EquivalenceProperties, Partitioning};
+use datafusion::physical_plan::execution_plan::{Boundedness, EmissionType};
+use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
+use datafusion::physical_plan::{
+ DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
execute_input_stream,
+};
+use futures::StreamExt;
+use iceberg::arrow::schema_to_arrow_schema;
+use iceberg::spec::{DataFileFormat, DataFileSerde, FormatVersion};
+use iceberg::table::Table;
+use iceberg::writer::CurrentFileStatus;
+use iceberg::writer::file_writer::location_generator::{
+ DefaultFileNameGenerator, DefaultLocationGenerator,
+};
+use iceberg::writer::file_writer::{FileWriter, FileWriterBuilder,
ParquetWriterBuilder};
+use parquet::file::properties::WriterProperties;
+use uuid::Uuid;
+
+use crate::to_datafusion_error;
+
+pub(crate) struct IcebergWriteExec {
+ table: Table,
+ input: Arc<dyn ExecutionPlan>,
+ result_schema: ArrowSchemaRef,
+ plan_properties: PlanProperties,
+}
+
+impl IcebergWriteExec {
+ pub fn new(table: Table, input: Arc<dyn ExecutionPlan>, schema:
ArrowSchemaRef) -> Self {
+ let plan_properties = Self::compute_properties(schema.clone());
+
+ Self {
+ table,
+ input,
+ result_schema: Self::make_result_schema(),
+ plan_properties,
+ }
+ }
+
+ /// todo: Copied from scan.rs
+ fn compute_properties(schema: ArrowSchemaRef) -> PlanProperties {
+ // TODO:
+ // This is more or less a placeholder, to be replaced
+ // once we support output-partitioning
+ PlanProperties::new(
+ EquivalenceProperties::new(schema),
+ Partitioning::UnknownPartitioning(1),
+ EmissionType::Incremental,
+ Boundedness::Bounded,
+ )
+ }
+
+ // Create a record batch with count and serialized data files
+ fn make_result_batch(count: u64, data_files: Vec<String>) ->
DFResult<RecordBatch> {
+ let count_array = Arc::new(UInt64Array::from(vec![count])) as ArrayRef;
+ let files_array = Arc::new(StringArray::from(data_files)) as ArrayRef;
+
+ RecordBatch::try_from_iter_with_nullable(vec![
+ ("count", count_array, false),
+ ("data_files", files_array, false),
+ ])
+ .map_err(|e| {
+ DataFusionError::ArrowError(e, Some("Failed to make result
batch".to_string()))
+ })
+ }
+
+ fn make_result_schema() -> ArrowSchemaRef {
+ // Define a schema.
+ Arc::new(ArrowSchema::new(vec![
+ Field::new("data_files", DataType::Utf8, false),
+ Field::new("count", DataType::UInt64, false),
Review Comment:
What's the meaning of `count`?
##########
crates/integrations/datafusion/src/physical_plan/write.rs:
##########
@@ -0,0 +1,371 @@
+// 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.
+
+use std::any::Any;
+use std::fmt::{Debug, Formatter};
+use std::sync::Arc;
+
+use datafusion::arrow::array::{ArrayRef, RecordBatch, StringArray,
UInt64Array};
+use datafusion::arrow::datatypes::{
+ DataType, Field, Schema as ArrowSchema, SchemaRef as ArrowSchemaRef,
+};
+use datafusion::common::Result as DFResult;
+use datafusion::error::DataFusionError;
+use datafusion::execution::{SendableRecordBatchStream, TaskContext};
+use datafusion::physical_expr::{EquivalenceProperties, Partitioning};
+use datafusion::physical_plan::execution_plan::{Boundedness, EmissionType};
+use datafusion::physical_plan::stream::RecordBatchStreamAdapter;
+use datafusion::physical_plan::{
+ DisplayAs, DisplayFormatType, ExecutionPlan, PlanProperties,
execute_input_stream,
+};
+use futures::StreamExt;
+use iceberg::arrow::schema_to_arrow_schema;
+use iceberg::spec::{DataFileFormat, DataFileSerde, FormatVersion};
+use iceberg::table::Table;
+use iceberg::writer::CurrentFileStatus;
+use iceberg::writer::file_writer::location_generator::{
+ DefaultFileNameGenerator, DefaultLocationGenerator,
+};
+use iceberg::writer::file_writer::{FileWriter, FileWriterBuilder,
ParquetWriterBuilder};
+use parquet::file::properties::WriterProperties;
+use uuid::Uuid;
+
+use crate::to_datafusion_error;
+
+pub(crate) struct IcebergWriteExec {
+ table: Table,
+ input: Arc<dyn ExecutionPlan>,
+ result_schema: ArrowSchemaRef,
+ plan_properties: PlanProperties,
+}
+
+impl IcebergWriteExec {
+ pub fn new(table: Table, input: Arc<dyn ExecutionPlan>, schema:
ArrowSchemaRef) -> Self {
+ let plan_properties = Self::compute_properties(schema.clone());
+
+ Self {
+ table,
+ input,
+ result_schema: Self::make_result_schema(),
+ plan_properties,
+ }
+ }
+
+ /// todo: Copied from scan.rs
+ fn compute_properties(schema: ArrowSchemaRef) -> PlanProperties {
+ // TODO:
+ // This is more or less a placeholder, to be replaced
+ // once we support output-partitioning
+ PlanProperties::new(
+ EquivalenceProperties::new(schema),
+ Partitioning::UnknownPartitioning(1),
+ EmissionType::Incremental,
+ Boundedness::Bounded,
+ )
+ }
+
+ // Create a record batch with count and serialized data files
+ fn make_result_batch(count: u64, data_files: Vec<String>) ->
DFResult<RecordBatch> {
+ let count_array = Arc::new(UInt64Array::from(vec![count])) as ArrayRef;
+ let files_array = Arc::new(StringArray::from(data_files)) as ArrayRef;
+
+ RecordBatch::try_from_iter_with_nullable(vec![
+ ("count", count_array, false),
+ ("data_files", files_array, false),
+ ])
+ .map_err(|e| {
+ DataFusionError::ArrowError(e, Some("Failed to make result
batch".to_string()))
+ })
+ }
+
+ fn make_result_schema() -> ArrowSchemaRef {
+ // Define a schema.
+ Arc::new(ArrowSchema::new(vec![
+ Field::new("data_files", DataType::Utf8, false),
+ Field::new("count", DataType::UInt64, false),
+ ]))
+ }
+}
+
+impl Debug for IcebergWriteExec {
+ fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
+ write!(f, "IcebergWriteExec")
+ }
+}
+
+impl DisplayAs for IcebergWriteExec {
+ fn fmt_as(&self, t: DisplayFormatType, f: &mut Formatter) ->
std::fmt::Result {
+ match t {
+ DisplayFormatType::Default => {
+ write!(f, "IcebergWriteExec: table={}",
self.table.identifier())
+ }
+ DisplayFormatType::Verbose => {
+ write!(
+ f,
+ "IcebergWriteExec: table={}, result_schema={:?}",
+ self.table.identifier(),
+ self.result_schema
+ )
+ }
+ DisplayFormatType::TreeRender => {
+ write!(f, "IcebergWriteExec: table={}",
self.table.identifier())
+ }
+ }
+ }
+}
+
+impl ExecutionPlan for IcebergWriteExec {
+ fn name(&self) -> &str {
+ "IcebergWriteExec"
+ }
+
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn properties(&self) -> &PlanProperties {
+ &self.plan_properties
+ }
+
+ fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>> {
+ vec![]
+ }
+
+ fn with_new_children(
+ self: Arc<Self>,
+ _children: Vec<Arc<dyn ExecutionPlan>>,
+ ) -> DFResult<Arc<dyn ExecutionPlan>> {
+ Ok(self)
+ }
+
+ fn execute(
+ &self,
+ partition: usize,
+ context: Arc<TaskContext>,
+ ) -> DFResult<SendableRecordBatchStream> {
+ let parquet_writer_fut = ParquetWriterBuilder::new(
Review Comment:
We should check table property that its data format is parquet, and throw
error if not.
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