Prevent memory overflows (and spills) on sorts with a fixed limit (#3593

)

datafusion/core/src/physical_plan/metrics/value.rs

@@ -122,6 +122,13 @@ impl Gauge {
         self.value.fetch_add(n, Ordering::Relaxed);
     }
 
+    /// Sub `n` from the metric's value
+    pub fn sub(&self, n: usize) {
+        // relaxed ordering for operations on `value` poses no issues
+        // we're purely using atomic ops with no associated memory ops
+        self.value.fetch_sub(n, Ordering::Relaxed);
+    }
+
     /// Set the metric's value to `n` and return the previous value
     pub fn set(&self, n: usize) -> usize {
         // relaxed ordering for operations on `value` poses no issues

datafusion/core/src/physical_plan/sorts/sort.rs

@@ -124,6 +124,21 @@ impl ExternalSorter {
             // calls to `timer.done()` below.
             let _timer = tracking_metrics.elapsed_compute().timer();
             let partial = sort_batch(input, self.schema.clone(), &self.expr, self.fetch)?;
+            // The resulting batch might be smaller than the input batch if there
+            // is an propagated limit.
+
+            if self.fetch.is_some() {
+                let new_size = batch_byte_size(&partial.sorted_batch);
+                let size_delta = size.checked_sub(new_size).ok_or_else(|| {
+                    DataFusionError::Internal(format!(
+                        "The size of the sorted batch is larger than the size of the input batch: {} > {}",
+                        size,
+                        new_size
+                    ))
+                })?;
+                self.shrink(size_delta);
+                self.metrics.mem_used().sub(size_delta);
+            }
             in_mem_batches.push(partial);
         }
         Ok(())
@@ -1062,6 +1077,65 @@ mod tests {
         Ok(())
     }
 
+    #[tokio::test]
+    async fn test_sort_fetch_memory_calculation() -> Result<()> {
+        // This test mirrors down the size from the example above.
+        let avg_batch_size = 5336;
+        let partitions = 4;
+
+        // A tuple of (fetch, expect_spillage)
+        let test_options = vec![
+            // Since we don't have a limit (and the memory is less than the total size of
+            // all the batches we are processing, we expect it to spill.
+            (None, true),
+            // When we have a limit however, the buffered size of batches should fit in memory
+            // since it is much lover than the total size of the input batch.
+            (Some(1), false),
+        ];
+
+        for (fetch, expect_spillage) in test_options {
+            let config = RuntimeConfig::new()
+                .with_memory_limit(avg_batch_size * (partitions - 1), 1.0);
+            let runtime = Arc::new(RuntimeEnv::new(config)?);
+            let session_ctx =
+                SessionContext::with_config_rt(SessionConfig::new(), runtime);
+
+            let csv = test::scan_partitioned_csv(partitions)?;
+            let schema = csv.schema();
+
+            let sort_exec = Arc::new(SortExec::try_new(
+                vec![
+                    // c1 string column
+                    PhysicalSortExpr {
+                        expr: col("c1", &schema)?,
+                        options: SortOptions::default(),
+                    },
+                    // c2 uin32 column
+                    PhysicalSortExpr {
+                        expr: col("c2", &schema)?,
+                        options: SortOptions::default(),
+                    },
+                    // c7 uin8 column
+                    PhysicalSortExpr {
+                        expr: col("c7", &schema)?,
+                        options: SortOptions::default(),
+                    },
+                ],
+                Arc::new(CoalescePartitionsExec::new(csv)),
+                fetch,
+            )?);
+
+            let task_ctx = session_ctx.task_ctx();
+            let result = collect(sort_exec.clone(), task_ctx).await?;
+            assert_eq!(result.len(), 1);
+
+            let metrics = sort_exec.metrics().unwrap();
+            let did_it_spill = metrics.spill_count().unwrap() > 0;
+            assert_eq!(did_it_spill, expect_spillage, "with fetch: {:?}", fetch);
+        }
+        Ok(())
+    }
+
     #[tokio::test]
     async fn test_sort_metadata() -> Result<()> {
         let session_ctx = SessionContext::new();