gratus00 commented on code in PR #21600:
URL: https://github.com/apache/datafusion/pull/21600#discussion_r3090106065
##########
datafusion/physical-plan/src/sorts/sort.rs:
##########
@@ -323,56 +312,185 @@ impl ExternalSorter {
self.reserve_memory_for_batch_and_maybe_spill(&input)
.await?;
- self.in_mem_batches.push(input);
+ let coalescer = self
+ .coalescer
+ .as_mut()
+ .expect("coalescer must exist during insert phase");
+ coalescer
+ .push_batch(input)
+ .map_err(|e| DataFusionError::ArrowError(Box::new(e), None))?;
+
+ self.drain_completed_batches()?;
+
+ Ok(())
+ }
+
+ /// Drains completed (full) batches from the coalescer, sorts each,
+ /// and appends the sorted chunks to `sorted_runs`.
+ fn drain_completed_batches(&mut self) -> Result<()> {
+ // Collect completed batches first to avoid borrow conflict
+ let mut completed = vec![];
+ if let Some(coalescer) = self.coalescer.as_mut() {
+ while let Some(batch) = coalescer.next_completed_batch() {
+ completed.push(batch);
+ }
+ }
+ for batch in &completed {
+ self.sort_and_store_run(batch)?;
+ }
+ Ok(())
+ }
+
+ /// Sorts a single coalesced batch and stores the result as a new run.
+ ///
+ /// Uses radix sort when the batch is large enough to amortize encoding
+ /// overhead (more than `batch_size` rows). Otherwise falls back to
lexsort.
+ fn sort_and_store_run(&mut self, batch: &RecordBatch) -> Result<()> {
+ let use_radix_for_this_batch =
+ self.use_radix && batch.num_rows() > self.batch_size;
+
Review Comment:
Thanks for the timely answer, I'll be sure to check both out. I'm a newcomer
to the project, so trying to review my way through for now. If you have any
suggestions I'm all for them but so far this seems like a good place to start
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