zhuqi-lucas commented on code in PR #14823:
URL: https://github.com/apache/datafusion/pull/14823#discussion_r1966714007
##########
datafusion/physical-plan/src/sorts/sort.rs:
##########
@@ -414,6 +419,66 @@ impl ExternalSorter {
Ok(used)
}
+ /// Reconstruct `self.in_mem_batches` to organize the payload buffers of
each
+ /// `StringViewArray` in sequential order by calling `gc()` on them.
+ ///
+ /// # Rationale
+ /// After (merge-based) sorting, all batches will be sorted into a single
run,
+ /// but physically this sorted run is chunked into many small batches. For
+ /// `StringViewArray`s inside each sorted run, their inner buffers are not
+ /// re-constructed by default, leading to non-sequential payload locations
+ /// (permutated by `interleave()` Arrow kernel). A single payload buffer
might
+ /// be shared by multiple `RecordBatch`es.
+ /// When writing each batch to disk, the writer has to write all
referenced buffers,
+ /// because they have to be read back one by one to reduce memory usage.
This
+ /// causes extra disk reads and writes, and potentially execution failure.
+ ///
+ /// # Example
+ /// Before sorting:
+ /// batch1 -> buffer1
+ /// batch2 -> buffer2
+ ///
+ /// sorted_batch1 -> buffer1
+ /// -> buffer2
+ /// sorted_batch2 -> buffer1
+ /// -> buffer2
+ ///
+ /// Then when spilling each batch, the writer has to write all referenced
buffers
+ /// repeatedly.
+ fn organize_stringview_arrays(&mut self) -> Result<()> {
+ let mut organized_batches =
Vec::with_capacity(self.in_mem_batches.len());
+
+ for batch in self.in_mem_batches.drain(..) {
+ let mut new_columns: Vec<Arc<dyn Array>> =
+ Vec::with_capacity(batch.num_columns());
+
+ let mut arr_mutated = false;
+ for array in batch.columns() {
+ if let Some(string_view_array) =
+ array.as_any().downcast_ref::<StringViewArray>()
+ {
+ let new_array = string_view_array.gc();
Review Comment:
Will string_view_array.gc() affect the performance when it call many times?
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