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// 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.
//! DataFusion data sources: [`TableProvider`] and [`ListingTable`]
//!
//! [`ListingTable`]: crate::datasource::listing::ListingTable
pub mod avro_to_arrow;
pub mod default_table_source;
pub mod empty;
pub mod file_format;
pub mod listing;
pub mod listing_table_factory;
pub mod memory;
pub mod physical_plan;
pub mod provider;
pub mod streaming;
pub mod view;
// backwards compatibility
pub use datafusion_execution::object_store;
use futures::Stream;
pub use self::default_table_source::{
provider_as_source, source_as_provider, DefaultTableSource,
};
use self::listing::PartitionedFile;
pub use self::memory::MemTable;
pub use self::provider::TableProvider;
pub use self::view::ViewTable;
use crate::arrow::datatypes::{Schema, SchemaRef};
use crate::error::Result;
pub use crate::logical_expr::TableType;
use crate::physical_plan::expressions::{MaxAccumulator, MinAccumulator};
use crate::physical_plan::{Accumulator, ColumnStatistics, Statistics};
use futures::StreamExt;
/// Get all files as well as the file level summary statistics (no statistic for partition columns).
/// If the optional `limit` is provided, includes only sufficient files.
/// Needed to read up to `limit` number of rows.
pub async fn get_statistics_with_limit(
all_files: impl Stream<Item = Result<(PartitionedFile, Statistics)>>,
file_schema: SchemaRef,
limit: Option<usize>,
) -> Result<(Vec<PartitionedFile>, Statistics)> {
let mut result_files = vec![];
let mut null_counts = vec![0; file_schema.fields().len()];
let mut has_statistics = false;
let (mut max_values, mut min_values) = create_max_min_accs(&file_schema);
let mut is_exact = true;
// The number of rows and the total byte size can be calculated as long as
// at least one file has them. If none of the files provide them, then they
// will be omitted from the statistics. The missing values will be counted
// as zero.
let mut num_rows = None;
let mut total_byte_size = None;
// fusing the stream allows us to call next safely even once it is finished
let mut all_files = Box::pin(all_files.fuse());
while let Some(res) = all_files.next().await {
let (file, file_stats) = res?;
result_files.push(file);
is_exact &= file_stats.is_exact;
num_rows = if let Some(num_rows) = num_rows {
Some(num_rows + file_stats.num_rows.unwrap_or(0))
} else {
file_stats.num_rows
};
total_byte_size = if let Some(total_byte_size) = total_byte_size {
Some(total_byte_size + file_stats.total_byte_size.unwrap_or(0))
} else {
file_stats.total_byte_size
};
if let Some(vec) = &file_stats.column_statistics {
has_statistics = true;
for (i, cs) in vec.iter().enumerate() {
null_counts[i] += cs.null_count.unwrap_or(0);
if let Some(max_value) = &mut max_values[i] {
if let Some(file_max) = cs.max_value.clone() {
match max_value.update_batch(&[file_max.to_array()]) {
Ok(_) => {}
Err(_) => {
max_values[i] = None;
}
}
} else {
max_values[i] = None;
}
}
if let Some(min_value) = &mut min_values[i] {
if let Some(file_min) = cs.min_value.clone() {
match min_value.update_batch(&[file_min.to_array()]) {
Ok(_) => {}
Err(_) => {
min_values[i] = None;
}
}
} else {
min_values[i] = None;
}
}
}
}
// If the number of rows exceeds the limit, we can stop processing
// files. This only applies when we know the number of rows. It also
// currently ignores tables that have no statistics regarding the
// number of rows.
if num_rows.unwrap_or(usize::MIN) > limit.unwrap_or(usize::MAX) {
break;
}
}
// if we still have files in the stream, it means that the limit kicked
// in and that the statistic could have been different if we processed
// the files in a different order.
if all_files.next().await.is_some() {
is_exact = false;
}
let column_stats = if has_statistics {
Some(get_col_stats(
&file_schema,
null_counts,
&mut max_values,
&mut min_values,
))
} else {
None
};
let statistics = Statistics {
num_rows,
total_byte_size,
column_statistics: column_stats,
is_exact,
};
Ok((result_files, statistics))
}
fn create_max_min_accs(
schema: &Schema,
) -> (Vec<Option<MaxAccumulator>>, Vec<Option<MinAccumulator>>) {
let max_values: Vec<Option<MaxAccumulator>> = schema
.fields()
.iter()
.map(|field| MaxAccumulator::try_new(field.data_type()).ok())
.collect::<Vec<_>>();
let min_values: Vec<Option<MinAccumulator>> = schema
.fields()
.iter()
.map(|field| MinAccumulator::try_new(field.data_type()).ok())
.collect::<Vec<_>>();
(max_values, min_values)
}
fn get_col_stats(
schema: &Schema,
null_counts: Vec<usize>,
max_values: &mut [Option<MaxAccumulator>],
min_values: &mut [Option<MinAccumulator>],
) -> Vec<ColumnStatistics> {
(0..schema.fields().len())
.map(|i| {
let max_value = match &max_values[i] {
Some(max_value) => max_value.evaluate().ok(),
None => None,
};
let min_value = match &min_values[i] {
Some(min_value) => min_value.evaluate().ok(),
None => None,
};
ColumnStatistics {
null_count: Some(null_counts[i]),
max_value,
min_value,
distinct_count: None,
}
})
.collect()
}