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use crate::error::{ExecutionError, Result};
use crate::execution::physical_plan::common::RecordBatchIterator;
use crate::execution::physical_plan::ExecutionPlan;
use crate::execution::physical_plan::Partition;
use arrow::array::ArrayRef;
use arrow::compute::limit;
use arrow::datatypes::SchemaRef;
use arrow::record_batch::{RecordBatch, RecordBatchReader};
use std::sync::{Arc, Mutex};
use std::thread;
use std::thread::JoinHandle;
pub struct LimitExec {
schema: SchemaRef,
partitions: Vec<Arc<dyn Partition>>,
limit: usize,
}
impl LimitExec {
pub fn new(
schema: SchemaRef,
partitions: Vec<Arc<dyn Partition>>,
limit: usize,
) -> Self {
LimitExec {
schema,
partitions,
limit,
}
}
}
impl ExecutionPlan for LimitExec {
fn schema(&self) -> SchemaRef {
self.schema.clone()
}
fn partitions(&self) -> Result<Vec<Arc<dyn Partition>>> {
Ok(vec![Arc::new(LimitPartition {
schema: self.schema.clone(),
partitions: self.partitions.clone(),
limit: self.limit,
})])
}
}
struct LimitPartition {
schema: SchemaRef,
partitions: Vec<Arc<dyn Partition>>,
limit: usize,
}
impl Partition for LimitPartition {
fn execute(&self) -> Result<Arc<Mutex<dyn RecordBatchReader + Send + Sync>>> {
let threads: Vec<JoinHandle<Result<Vec<RecordBatch>>>> = self
.partitions
.iter()
.map(|p| {
let p = p.clone();
let limit = self.limit;
thread::spawn(move || {
let it = p.execute()?;
collect_with_limit(it, limit)
})
})
.collect();
let mut combined_results: Vec<Arc<RecordBatch>> = vec![];
let mut count = 0;
for thread in threads {
let join = thread.join().expect("Failed to join thread");
let result = join?;
for batch in result {
let capacity = self.limit - count;
if batch.num_rows() <= capacity {
count += batch.num_rows();
combined_results.push(Arc::new(batch.clone()))
} else {
let batch = truncate_batch(&batch, capacity)?;
count += batch.num_rows();
combined_results.push(Arc::new(batch.clone()))
}
if count == self.limit {
break;
}
}
}
Ok(Arc::new(Mutex::new(RecordBatchIterator::new(
self.schema.clone(),
combined_results,
))))
}
}
pub fn truncate_batch(batch: &RecordBatch, n: usize) -> Result<RecordBatch> {
let limited_columns: Result<Vec<ArrayRef>> = (0..batch.num_columns())
.map(|i| limit(batch.column(i), n).map_err(|error| ExecutionError::from(error)))
.collect();
Ok(RecordBatch::try_new(
batch.schema().clone(),
limited_columns?,
)?)
}
fn collect_with_limit(
reader: Arc<Mutex<dyn RecordBatchReader + Send + Sync>>,
limit: usize,
) -> Result<Vec<RecordBatch>> {
let mut count = 0;
let mut reader = reader.lock().unwrap();
let mut results: Vec<RecordBatch> = vec![];
loop {
match reader.next_batch() {
Ok(Some(batch)) => {
let capacity = limit - count;
if batch.num_rows() <= capacity {
count += batch.num_rows();
results.push(batch);
} else {
let batch = truncate_batch(&batch, capacity)?;
count += batch.num_rows();
results.push(batch);
}
if count == limit {
return Ok(results);
}
}
Ok(None) => {
return Ok(results);
}
Err(e) => return Err(ExecutionError::from(e)),
}
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::execution::physical_plan::common;
use crate::execution::physical_plan::csv::{CsvExec, CsvReadOptions};
use crate::test;
#[test]
fn limit() -> Result<()> {
let schema = test::aggr_test_schema();
let num_partitions = 4;
let path =
test::create_partitioned_csv("aggregate_test_100.csv", num_partitions)?;
let csv =
CsvExec::try_new(&path, CsvReadOptions::new().schema(&schema), None, 1024)?;
let input = csv.partitions()?;
assert_eq!(input.len(), num_partitions);
let limit = LimitExec::new(schema.clone(), input, 7);
let partitions = limit.partitions()?;
let iter = partitions[0].execute()?;
let batches = common::collect(iter)?;
let row_count: usize = batches.iter().map(|batch| batch.num_rows()).sum();
assert_eq!(row_count, 7);
Ok(())
}
}