From d896bad956493731d11412ea5e862ec317775bbf Mon Sep 17 00:00:00 2001
From: Adrien Guillo <adrien.guillo@datadoghq.com>
Date: Wed, 24 Jun 2026 13:25:00 -0400
Subject: [PATCH] perf(aggregation): parallelize extended_stats variance via
 lane merge
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`extended_stats` collects with Welford's online variance, which recomputes
the running mean from the running sum each step — a strictly serial
recurrence that cannot be vectorized in place.

Add `collect_block`, which accumulates the block into 4 independent
`IntermediateExtendedStats` lanes and combines them with the existing
`merge_fruits` (Chan parallel-variance combination) — the exact operation
already used to merge across segments, so results match multi-segment
aggregation.

Stays within the tight `EPSILON_FOR_TEST = 2e-12` tolerance; even the
rounding-sensitive `test_aggregation_level1` passes.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---
 src/aggregation/metric/extended_stats.rs | 39 +++++++++++++++++++++---
 1 file changed, 35 insertions(+), 4 deletions(-)

diff --git a/src/aggregation/metric/extended_stats.rs b/src/aggregation/metric/extended_stats.rs
index 1e625d5de..efc00d708 100644
--- a/src/aggregation/metric/extended_stats.rs
+++ b/src/aggregation/metric/extended_stats.rs
@@ -315,6 +315,40 @@ impl IntermediateExtendedStats {
         self.sum_of_squares_elastic = t;
         self.update_variance(value);
     }
+
+    /// Collects a contiguous block of raw column values.
+    ///
+    /// The per-value [`Self::collect`] is a strictly serial recurrence (Welford's variance
+    /// recomputes the mean from the running sum each step). To break that dependency chain we
+    /// accumulate into `LANES` independent accumulators and combine them with
+    /// [`Self::merge_fruits`] — the exact Chan parallel-variance combination already used to
+    /// merge across segments, so the result matches multi-segment aggregation (fp summation
+    /// order differs, as it already does there).
+    #[inline]
+    fn collect_block(&mut self, vals: &[u64], field_type: ColumnType) {
+        const LANES: usize = 4;
+        if vals.len() < LANES * 2 {
+            for &val in vals {
+                self.collect(f64_from_fastfield_u64(val, field_type));
+            }
+            return;
+        }
+        let mut lanes: [IntermediateExtendedStats; LANES] = Default::default();
+        let mut chunks = vals.chunks_exact(LANES);
+        for chunk in chunks.by_ref() {
+            for lane in 0..LANES {
+                lanes[lane].collect(f64_from_fastfield_u64(chunk[lane], field_type));
+            }
+        }
+        for &val in chunks.remainder() {
+            lanes[0].collect(f64_from_fastfield_u64(val, field_type));
+        }
+        let mut combined = mem::take(&mut lanes[0]);
+        for lane in 1..LANES {
+            combined.merge_fruits(mem::take(&mut lanes[lane]));
+        }
+        self.merge_fruits(combined);
+    }
 }
 
 #[derive(Clone, Debug)]
@@ -376,10 +410,7 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
         agg_data
             .column_block_accessor
             .fetch_block_with_missing(docs, &self.accessor, self.missing);
-        for val in agg_data.column_block_accessor.iter_vals() {
-            let val1 = f64_from_fastfield_u64(val, self.field_type);
-            extended_stats.collect(val1);
-        }
+        extended_stats.collect_block(agg_data.column_block_accessor.vals(), self.field_type);
 
         // store back
         self.buckets[parent_bucket_id as usize] = extended_stats;