houqp commented on a change in pull request #1141:
URL: https://github.com/apache/arrow-datafusion/pull/1141#discussion_r735280489
##########
File path: datafusion/src/datasource/file_format/mod.rs
##########
@@ -36,25 +36,25 @@ use async_trait::async_trait;
use super::object_store::{ObjectReader, ObjectReaderStream, ObjectStore};
use super::PartitionedFile;
-/// The configurations to be passed when creating a physical plan for
-/// a given file format.
+/// The base configurations to provide when creating a physical plan for
+/// any given file format.
pub struct PhysicalPlanConfig {
/// Store from which the `files` should be fetched
pub object_store: Arc<dyn ObjectStore>,
/// Schema before projection
- pub schema: SchemaRef,
+ pub file_schema: SchemaRef,
/// List of files to be processed, grouped into partitions
- pub files: Vec<Vec<PartitionedFile>>,
+ pub file_groups: Vec<Vec<PartitionedFile>>,
/// Estimated overall statistics of the plan, taking `filters` into account
pub statistics: Statistics,
/// Columns on which to project the data
pub projection: Option<Vec<usize>>,
/// The maximum number of records per arrow column
pub batch_size: usize,
- /// The filters that were pushed down to this execution plan
- pub filters: Vec<Expr>,
/// The minimum number of records required from this source plan
pub limit: Option<usize>,
+ /// The partitioning column names
+ pub table_partition_dims: Vec<String>,
Review comment:
curious why not name it as `table_partition_cols` to better align with
the comment? the type should make it clear that it's storing column names.
##########
File path: datafusion/src/datasource/listing/table.rs
##########
@@ -109,7 +108,8 @@ impl ListingOptions {
/// or file system listing capability to get the list of files.
pub struct ListingTable {
object_store: Arc<dyn ObjectStore>,
- path: String,
+ table_path: String,
Review comment:
I think the table_path should contain contain uri scheme as well? if so,
`table_uri` might be a better name here.
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
+ partitioned_files
+ .chunks(chunk_size)
+ .map(|c| c.to_vec())
+ .collect()
+}
+
+/// Discover the partitions on the given path and prune out files
+/// relative to irrelevant partitions using `filters` expressions
+/// TODO for tables with many files (10k+), it will usually more efficient
+/// to first list the folders relative to the first partition dimension,
+/// prune those, then list only the contain of the remaining folders.
+pub async fn pruned_partition_list(
+ store: &dyn ObjectStore,
+ table_path: &str,
+ filters: &[Expr],
+ file_extension: &str,
+ table_partition_dims: &[String],
+) -> Result<PartitionedFileStream> {
+ if table_partition_dims.is_empty() {
+ Ok(Box::pin(
+ store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .map(|f| {
+ Ok(PartitionedFile {
+ file_meta: f?,
+ partition_values: vec![],
+ })
+ }),
+ ))
+ } else {
+ let applicable_filters = filters
+ .iter()
+ .filter(|f| expr_applicable_for_cols(table_partition_dims, f));
+
+ let table_partition_dims = table_partition_dims.to_vec();
+ let stream_path = table_path.to_owned();
+ // TODO avoid collecting but have a streaming memory table instead
+ let batches: Vec<RecordBatch> = store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .chunks(64)
Review comment:
any particular reason for picking 64 here?
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
+ partitioned_files
+ .chunks(chunk_size)
+ .map(|c| c.to_vec())
+ .collect()
+}
+
+/// Discover the partitions on the given path and prune out files
+/// relative to irrelevant partitions using `filters` expressions
+/// TODO for tables with many files (10k+), it will usually more efficient
+/// to first list the folders relative to the first partition dimension,
+/// prune those, then list only the contain of the remaining folders.
+pub async fn pruned_partition_list(
+ store: &dyn ObjectStore,
+ table_path: &str,
+ filters: &[Expr],
+ file_extension: &str,
+ table_partition_dims: &[String],
+) -> Result<PartitionedFileStream> {
+ if table_partition_dims.is_empty() {
+ Ok(Box::pin(
+ store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .map(|f| {
+ Ok(PartitionedFile {
+ file_meta: f?,
+ partition_values: vec![],
+ })
+ }),
+ ))
+ } else {
+ let applicable_filters = filters
+ .iter()
+ .filter(|f| expr_applicable_for_cols(table_partition_dims, f));
+
+ let table_partition_dims = table_partition_dims.to_vec();
+ let stream_path = table_path.to_owned();
+ // TODO avoid collecting but have a streaming memory table instead
+ let batches: Vec<RecordBatch> = store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .chunks(64)
+ .map(|v| v.into_iter().collect::<Result<Vec<_>>>())
+ .map(move |metas| {
+ paths_to_batch(&table_partition_dims, &stream_path, &metas?)
+ })
+ .try_collect()
+ .await?;
+
+ let mem_table = MemTable::try_new(batches[0].schema(), vec![batches])?;
+
+ // Filter the partitions using a local datafusion context
+ // TODO having the external context would allow us to resolve
`Volatility::Stable`
+ // scalar functions (`ScalarFunction` & `ScalarUDF`) and
`ScalarVariable`s
+ let mut ctx = ExecutionContext::new();
+ let mut df = ctx.read_table(Arc::new(mem_table))?;
+ for filter in applicable_filters {
+ df = df.filter(filter.clone())?;
+ }
+ let filtered_batches = df.collect().await?;
Review comment:
here we go datafusion in datafusion :D I do think in the future we could
optimize this to only use the physical execution code to directly evaluate the
record batches.
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
Review comment:
minor optimizaton:
```suggestion
let chunk_size = (partitioned_files.len()+n-1) / n;
```
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
+ partitioned_files
+ .chunks(chunk_size)
+ .map(|c| c.to_vec())
+ .collect()
+}
+
+/// Discover the partitions on the given path and prune out files
+/// relative to irrelevant partitions using `filters` expressions
+/// TODO for tables with many files (10k+), it will usually more efficient
+/// to first list the folders relative to the first partition dimension,
+/// prune those, then list only the contain of the remaining folders.
+pub async fn pruned_partition_list(
+ store: &dyn ObjectStore,
+ table_path: &str,
+ filters: &[Expr],
+ file_extension: &str,
+ table_partition_dims: &[String],
+) -> Result<PartitionedFileStream> {
+ if table_partition_dims.is_empty() {
Review comment:
I think we can also avoid the filter when no filter is provided?
```suggestion
if table_partition_dims.is_empty() || filters.empty() {
```
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
+ partitioned_files
+ .chunks(chunk_size)
+ .map(|c| c.to_vec())
+ .collect()
+}
+
+/// Discover the partitions on the given path and prune out files
+/// relative to irrelevant partitions using `filters` expressions
+/// TODO for tables with many files (10k+), it will usually more efficient
+/// to first list the folders relative to the first partition dimension,
+/// prune those, then list only the contain of the remaining folders.
+pub async fn pruned_partition_list(
+ store: &dyn ObjectStore,
+ table_path: &str,
+ filters: &[Expr],
+ file_extension: &str,
+ table_partition_dims: &[String],
+) -> Result<PartitionedFileStream> {
+ if table_partition_dims.is_empty() {
+ Ok(Box::pin(
+ store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .map(|f| {
+ Ok(PartitionedFile {
+ file_meta: f?,
+ partition_values: vec![],
+ })
+ }),
+ ))
+ } else {
+ let applicable_filters = filters
+ .iter()
+ .filter(|f| expr_applicable_for_cols(table_partition_dims, f));
+
+ let table_partition_dims = table_partition_dims.to_vec();
+ let stream_path = table_path.to_owned();
+ // TODO avoid collecting but have a streaming memory table instead
+ let batches: Vec<RecordBatch> = store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .chunks(64)
+ .map(|v| v.into_iter().collect::<Result<Vec<_>>>())
+ .map(move |metas| {
+ paths_to_batch(&table_partition_dims, &stream_path, &metas?)
+ })
+ .try_collect()
+ .await?;
+
+ let mem_table = MemTable::try_new(batches[0].schema(), vec![batches])?;
+
+ // Filter the partitions using a local datafusion context
+ // TODO having the external context would allow us to resolve
`Volatility::Stable`
+ // scalar functions (`ScalarFunction` & `ScalarUDF`) and
`ScalarVariable`s
+ let mut ctx = ExecutionContext::new();
+ let mut df = ctx.read_table(Arc::new(mem_table))?;
+ for filter in applicable_filters {
+ df = df.filter(filter.clone())?;
+ }
+ let filtered_batches = df.collect().await?;
+
+ Ok(Box::pin(stream::iter(
+ batches_to_paths(&filtered_batches).into_iter().map(Ok),
+ )))
+ }
+}
+
+/// convert the paths of the files to a record batch with the following
columns:
+/// - one column for the file size named `_df_part_file_size_`
+/// - one column for with the original path named `_df_part_file_path_`
+/// - one column for with the last modified date named
`_df_part_file_modified_`
+/// - ... one column by partition ...
+/// Note: For the last modified date, this looses precisions higher than
millisecond.
+fn paths_to_batch(
+ table_partition_dims: &[String],
+ table_path: &str,
+ metas: &[FileMeta],
+) -> Result<RecordBatch> {
+ let mut key_builder = StringBuilder::new(metas.len());
+ let mut length_builder = UInt64Builder::new(metas.len());
+ let mut modified_builder = Date64Builder::new(metas.len());
+ let mut partition_builders = table_partition_dims
+ .iter()
+ .map(|_| StringBuilder::new(metas.len()))
+ .collect::<Vec<_>>();
+ for file_meta in metas {
+ if let Some(partition_values) =
+ parse_partitions_for_path(table_path, file_meta.path(),
table_partition_dims)
+ {
+ key_builder.append_value(file_meta.path())?;
+ length_builder.append_value(file_meta.size())?;
+ match file_meta.last_modified {
+ Some(lm) =>
modified_builder.append_value(lm.timestamp_millis())?,
+ None => modified_builder.append_null()?,
+ }
+ for (i, part_val) in partition_values.iter().enumerate() {
+ partition_builders[i].append_value(part_val)?;
+ }
+ } else {
+ debug!("No partitioning for path {}", file_meta.path());
+ }
+ }
+
+ // finish all builders
+ let mut col_arrays: Vec<ArrayRef> = vec![
+ ArrayBuilder::finish(&mut key_builder),
+ ArrayBuilder::finish(&mut length_builder),
+ ArrayBuilder::finish(&mut modified_builder),
+ ];
+ for mut partition_builder in partition_builders {
+ col_arrays.push(ArrayBuilder::finish(&mut partition_builder));
+ }
+
+ // put the schema together
+ let mut fields = vec![
+ Field::new(FILE_SIZE_COLUMN_NAME, DataType::Utf8, false),
+ Field::new(FILE_PATH_COLUMN_NAME, DataType::UInt64, false),
Review comment:
typo?
```suggestion
Field::new(FILE_SIZE_COLUMN_NAME, DataType::Uint64, false),
Field::new(FILE_PATH_COLUMN_NAME, DataType::Utf8, false),
```
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
+ partitioned_files
+ .chunks(chunk_size)
+ .map(|c| c.to_vec())
+ .collect()
+}
+
+/// Discover the partitions on the given path and prune out files
+/// relative to irrelevant partitions using `filters` expressions
+/// TODO for tables with many files (10k+), it will usually more efficient
+/// to first list the folders relative to the first partition dimension,
+/// prune those, then list only the contain of the remaining folders.
+pub async fn pruned_partition_list(
+ store: &dyn ObjectStore,
+ table_path: &str,
+ filters: &[Expr],
+ file_extension: &str,
+ table_partition_dims: &[String],
+) -> Result<PartitionedFileStream> {
+ if table_partition_dims.is_empty() {
+ Ok(Box::pin(
+ store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .map(|f| {
+ Ok(PartitionedFile {
+ file_meta: f?,
+ partition_values: vec![],
+ })
+ }),
+ ))
+ } else {
+ let applicable_filters = filters
+ .iter()
+ .filter(|f| expr_applicable_for_cols(table_partition_dims, f));
+
+ let table_partition_dims = table_partition_dims.to_vec();
+ let stream_path = table_path.to_owned();
+ // TODO avoid collecting but have a streaming memory table instead
+ let batches: Vec<RecordBatch> = store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .chunks(64)
+ .map(|v| v.into_iter().collect::<Result<Vec<_>>>())
+ .map(move |metas| {
+ paths_to_batch(&table_partition_dims, &stream_path, &metas?)
+ })
+ .try_collect()
+ .await?;
+
+ let mem_table = MemTable::try_new(batches[0].schema(), vec![batches])?;
+
+ // Filter the partitions using a local datafusion context
+ // TODO having the external context would allow us to resolve
`Volatility::Stable`
+ // scalar functions (`ScalarFunction` & `ScalarUDF`) and
`ScalarVariable`s
+ let mut ctx = ExecutionContext::new();
+ let mut df = ctx.read_table(Arc::new(mem_table))?;
+ for filter in applicable_filters {
+ df = df.filter(filter.clone())?;
+ }
+ let filtered_batches = df.collect().await?;
+
+ Ok(Box::pin(stream::iter(
+ batches_to_paths(&filtered_batches).into_iter().map(Ok),
+ )))
+ }
+}
+
+/// convert the paths of the files to a record batch with the following
columns:
+/// - one column for the file size named `_df_part_file_size_`
+/// - one column for with the original path named `_df_part_file_path_`
+/// - one column for with the last modified date named
`_df_part_file_modified_`
+/// - ... one column by partition ...
+/// Note: For the last modified date, this looses precisions higher than
millisecond.
+fn paths_to_batch(
+ table_partition_dims: &[String],
+ table_path: &str,
+ metas: &[FileMeta],
+) -> Result<RecordBatch> {
+ let mut key_builder = StringBuilder::new(metas.len());
+ let mut length_builder = UInt64Builder::new(metas.len());
+ let mut modified_builder = Date64Builder::new(metas.len());
+ let mut partition_builders = table_partition_dims
+ .iter()
+ .map(|_| StringBuilder::new(metas.len()))
+ .collect::<Vec<_>>();
+ for file_meta in metas {
+ if let Some(partition_values) =
+ parse_partitions_for_path(table_path, file_meta.path(),
table_partition_dims)
+ {
+ key_builder.append_value(file_meta.path())?;
+ length_builder.append_value(file_meta.size())?;
+ match file_meta.last_modified {
+ Some(lm) =>
modified_builder.append_value(lm.timestamp_millis())?,
+ None => modified_builder.append_null()?,
+ }
+ for (i, part_val) in partition_values.iter().enumerate() {
+ partition_builders[i].append_value(part_val)?;
+ }
+ } else {
+ debug!("No partitioning for path {}", file_meta.path());
+ }
+ }
+
+ // finish all builders
+ let mut col_arrays: Vec<ArrayRef> = vec![
+ ArrayBuilder::finish(&mut key_builder),
+ ArrayBuilder::finish(&mut length_builder),
+ ArrayBuilder::finish(&mut modified_builder),
+ ];
+ for mut partition_builder in partition_builders {
+ col_arrays.push(ArrayBuilder::finish(&mut partition_builder));
+ }
+
+ // put the schema together
+ let mut fields = vec![
+ Field::new(FILE_SIZE_COLUMN_NAME, DataType::Utf8, false),
+ Field::new(FILE_PATH_COLUMN_NAME, DataType::UInt64, false),
+ Field::new(FILE_MODIFIED_COLUMN_NAME, DataType::Date64, false),
+ ];
+ for pn in table_partition_dims {
+ fields.push(Field::new(pn, DataType::Utf8, false));
+ }
+
+ let batch = RecordBatch::try_new(Arc::new(Schema::new(fields)),
col_arrays)?;
+ Ok(batch)
+}
+
+/// convert a set of record batches created by `paths_to_batch()` back to
partitioned files.
+fn batches_to_paths(batches: &[RecordBatch]) -> Vec<PartitionedFile> {
+ batches
+ .iter()
+ .flat_map(|batch| {
+ let key_array = batch
+ .column(0)
+ .as_any()
+ .downcast_ref::<StringArray>()
+ .unwrap();
+ let length_array = batch
+ .column(1)
+ .as_any()
+ .downcast_ref::<UInt64Array>()
+ .unwrap();
+ let modified_array = batch
+ .column(2)
+ .as_any()
+ .downcast_ref::<Date64Array>()
+ .unwrap();
+
+ (0..batch.num_rows()).map(move |row| PartitionedFile {
+ file_meta: FileMeta {
+ last_modified: match modified_array.is_null(row) {
+ false =>
Some(Utc.timestamp_millis(modified_array.value(row))),
+ true => None,
+ },
+ sized_file: SizedFile {
+ path: key_array.value(row).to_owned(),
+ size: length_array.value(row),
+ },
+ },
+ partition_values: (3..batch.columns().len())
+ .map(|col| {
+ ScalarValue::try_from_array(batch.column(col),
row).unwrap()
+ })
+ .collect(),
+ })
+ })
+ .collect()
+}
+
+/// Extract the partition values for the given `file_path` (in the given
`table_path`)
+/// associated to the partitions defined by `table_partition_dims`
+fn parse_partitions_for_path<'a>(
+ table_path: &str,
+ file_path: &'a str,
+ table_partition_dims: &[String],
+) -> Option<Vec<&'a str>> {
+ let subpath = file_path.strip_prefix(table_path)?;
+
+ // ignore whether table_path ended with "/" or not
+ let subpath = match subpath.strip_prefix('/') {
+ Some(subpath) => subpath,
+ None => subpath,
+ };
+
+ let mut part_values = vec![];
+ for (path, pn) in subpath.split('/').zip(table_partition_dims) {
+ if let Some(val) = path.strip_prefix(&format!("{}=", pn)) {
Review comment:
I think we could avoid the `format!` string creation here by applying
https://doc.rust-lang.org/stable/std/primitive.str.html#method.split_once with
`=` on path and compare `pn` with the first component.
##########
File path: datafusion/src/datasource/listing/helpers.rs
##########
@@ -0,0 +1,682 @@
+// 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.
+
+//! Helper functions for the table implementation
+
+use std::sync::Arc;
+
+use arrow::{
+ array::{
+ Array, ArrayBuilder, ArrayRef, Date64Array, Date64Builder, StringArray,
+ StringBuilder, UInt64Array, UInt64Builder,
+ },
+ datatypes::{DataType, Field, Schema},
+ record_batch::RecordBatch,
+};
+use chrono::{TimeZone, Utc};
+use futures::{
+ stream::{self},
+ StreamExt, TryStreamExt,
+};
+use log::debug;
+
+use crate::{
+ error::Result,
+ execution::context::ExecutionContext,
+ logical_plan::{self, Expr},
+ physical_plan::functions::Volatility,
+ scalar::ScalarValue,
+};
+
+use crate::datasource::{
+ object_store::{FileMeta, ObjectStore, SizedFile},
+ MemTable, PartitionedFile, PartitionedFileStream,
+};
+
+const FILE_SIZE_COLUMN_NAME: &str = "_df_part_file_size_";
+const FILE_PATH_COLUMN_NAME: &str = "_df_part_file_path_";
+const FILE_MODIFIED_COLUMN_NAME: &str = "_df_part_file_modified_";
+
+/// Partition the list of files into `n` groups
+pub fn split_files(
+ partitioned_files: Vec<PartitionedFile>,
+ n: usize,
+) -> Vec<Vec<PartitionedFile>> {
+ if partitioned_files.is_empty() {
+ return vec![];
+ }
+ let mut chunk_size = partitioned_files.len() / n;
+ if partitioned_files.len() % n > 0 {
+ chunk_size += 1;
+ }
+ partitioned_files
+ .chunks(chunk_size)
+ .map(|c| c.to_vec())
+ .collect()
+}
+
+/// Discover the partitions on the given path and prune out files
+/// relative to irrelevant partitions using `filters` expressions
+/// TODO for tables with many files (10k+), it will usually more efficient
+/// to first list the folders relative to the first partition dimension,
+/// prune those, then list only the contain of the remaining folders.
+pub async fn pruned_partition_list(
+ store: &dyn ObjectStore,
+ table_path: &str,
+ filters: &[Expr],
+ file_extension: &str,
+ table_partition_dims: &[String],
+) -> Result<PartitionedFileStream> {
+ if table_partition_dims.is_empty() {
+ Ok(Box::pin(
+ store
+ .list_file_with_suffix(table_path, file_extension)
+ .await?
+ .map(|f| {
+ Ok(PartitionedFile {
+ file_meta: f?,
+ partition_values: vec![],
+ })
+ }),
+ ))
+ } else {
+ let applicable_filters = filters
+ .iter()
+ .filter(|f| expr_applicable_for_cols(table_partition_dims, f));
Review comment:
to avoid the complexity of `expr_applicable_for_cols`, perhaps we could
just throw a runtime error to the user if invalid filters are provided? this
also makes sure that if there is a typo in the filter, we won't silent the
error.
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