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refactor(7181): move streaming_merge() into separate mod from the mer…
…ge mod. (#7799) Merge mod has the SortPreservingMergeStream, containing the loser tree. This SortPreservingMergeStream struct will be used repeatedly as part of the cascading merge; in turn, the cascading merge will be implemented for the streaming_merge() method.
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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. | ||
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//! Merge that deals with an arbitrary size of streaming inputs. | ||
//! This is an order-preserving merge. | ||
use crate::metrics::BaselineMetrics; | ||
use crate::sorts::{ | ||
merge::SortPreservingMergeStream, | ||
stream::{FieldCursorStream, RowCursorStream}, | ||
}; | ||
use crate::{PhysicalSortExpr, SendableRecordBatchStream}; | ||
use arrow::datatypes::{DataType, SchemaRef}; | ||
use arrow_array::*; | ||
use datafusion_common::Result; | ||
use datafusion_execution::memory_pool::MemoryReservation; | ||
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macro_rules! primitive_merge_helper { | ||
($t:ty, $($v:ident),+) => { | ||
merge_helper!(PrimitiveArray<$t>, $($v),+) | ||
}; | ||
} | ||
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macro_rules! merge_helper { | ||
($t:ty, $sort:ident, $streams:ident, $schema:ident, $tracking_metrics:ident, $batch_size:ident, $fetch:ident, $reservation:ident) => {{ | ||
let streams = FieldCursorStream::<$t>::new($sort, $streams); | ||
return Ok(Box::pin(SortPreservingMergeStream::new( | ||
Box::new(streams), | ||
$schema, | ||
$tracking_metrics, | ||
$batch_size, | ||
$fetch, | ||
$reservation, | ||
))); | ||
}}; | ||
} | ||
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/// Perform a streaming merge of [`SendableRecordBatchStream`] based on provided sort expressions | ||
/// while preserving order. | ||
pub fn streaming_merge( | ||
streams: Vec<SendableRecordBatchStream>, | ||
schema: SchemaRef, | ||
expressions: &[PhysicalSortExpr], | ||
metrics: BaselineMetrics, | ||
batch_size: usize, | ||
fetch: Option<usize>, | ||
reservation: MemoryReservation, | ||
) -> Result<SendableRecordBatchStream> { | ||
// Special case single column comparisons with optimized cursor implementations | ||
if expressions.len() == 1 { | ||
let sort = expressions[0].clone(); | ||
let data_type = sort.expr.data_type(schema.as_ref())?; | ||
downcast_primitive! { | ||
data_type => (primitive_merge_helper, sort, streams, schema, metrics, batch_size, fetch, reservation), | ||
DataType::Utf8 => merge_helper!(StringArray, sort, streams, schema, metrics, batch_size, fetch, reservation) | ||
DataType::LargeUtf8 => merge_helper!(LargeStringArray, sort, streams, schema, metrics, batch_size, fetch, reservation) | ||
DataType::Binary => merge_helper!(BinaryArray, sort, streams, schema, metrics, batch_size, fetch, reservation) | ||
DataType::LargeBinary => merge_helper!(LargeBinaryArray, sort, streams, schema, metrics, batch_size, fetch, reservation) | ||
_ => {} | ||
} | ||
} | ||
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let streams = RowCursorStream::try_new( | ||
schema.as_ref(), | ||
expressions, | ||
streams, | ||
reservation.new_empty(), | ||
)?; | ||
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Ok(Box::pin(SortPreservingMergeStream::new( | ||
Box::new(streams), | ||
schema, | ||
metrics, | ||
batch_size, | ||
fetch, | ||
reservation, | ||
))) | ||
} |