feat: benchmark delta transmission — accuracy, payload size, CPU/memory (#66)

[zzylol]

Summary

• opentelemetry-app/cmd/deltaaccbench/ — self-contained Go benchmark that runs entirely in-process. Simulates N streaming windows per sketch, sends full or sparse-delta payloads, reconstructs at the receiver, and reports compression, accuracy, and resource usage.
• 8 new delta-enabled collector configs for CMS, CS, HLL, and DDSketch (batch + window modes each).
• otel_collector_benchmark/bench_delta.sh — e2e orchestration script measuring bandwidth, collector CPU/memory.
• DDSketch delta optimization in sketchlib-go — replaces the broken protobuf codec with an incremental-sketch approach (gob + Merge) plus a size-based fallback.

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Benchmark results

Parameters: 20 windows × 5000 inserts/window, Zipf(s=1.1, v=1.0, max=5000), delta threshold=1.
CMS/CS accuracy on keys with true frequency >= 10 (heavy-hitter range).

Sketch   Mode    Delta   Full B avg  Delta B avg  Compression  MeanRelErr  MaxRelErr
-------  ------  ------  ----------  -----------  -----------  ----------  ---------
cms      batch   off        246,003            -            -      0.16%     18.75%
cms      batch   on         246,003      170,480       1.44x       0.16%     18.75%
cms      window  off        246,003            -            -      4.70%    150.00%
cms      window  on         246,003      150,014       1.64x       4.70%    150.00%
cs       batch   off        655,554            -            -      0.006%     7.14%
cs       batch   on         655,554      116,987       5.60x       0.006%     7.14%
cs       window  off        655,554            -            -      0.091%    40.00%
cs       window  on         655,554       87,507       7.49x       0.091%    40.00%
hll      batch   off         16,532            -            -      0.45%      1.08%
hll      window  off         16,532            -            -      0.73%      1.34%
hll      window  on          16,532        8,543       1.94x       0.73%      1.34%
dd       batch   off            725            -            -      0.37%      0.95%
dd       window  off            882            -            -      0.29%      0.82%
dd       window  on             882          736       1.20x       0.29%      0.82%
kll      batch   off          2,653        2,653          N/A      0.23%      1.15%
kll      window  off          3,116        3,116          N/A      0.30%      1.03%

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Key findings

CountSketch wins on delta compression

5.6-7.5x compression with zero accuracy impact. Window mode (7.49x) beats batch (5.60x) because the cumulative sketch is dense but each window adds sparse increments.

HLL window+delta halves payload size

1.94x compression, lossless (0.73% accuracy unchanged). Not applicable in batch mode.

CMS: modest compression, accurate in batch

1.4-1.6x compression, zero accuracy impact in batch (0.16%). Window mode error (4.7%) is an inherent CMS property — as accumulated N grows, the eps*N error bound grows — unrelated to delta.

DDSketch delta: window-only, fixed from broken (0.5x) to working (1.20x)

DDSketch batch mode does not use delta. SerializeToBytes stores a dense uint64 array spanning only the occupied bucket range — empty buckets at the edges are never stored. Each batch window produces an independent sketch from scratch, so the full payload is already maximally compact. Delta would only add overhead.

Root cause of the original failure (window mode): DDSketch full serialization uses gob on a dense uint64 array (~1.7 B/entry). The old protobuf delta format cost ~11 B/entry, making every delta larger than the full.

Fix — incremental-sketch approach:

1. ComputeDelta builds a new DDSketch containing only cur[k] - snap[k] for each grown bucket, serialized with SerializeToBytes (same gob codec). Per-window increment counts are small integers → shorter gob varints.
2. ApplyDelta calls target.Merge(incr) — no per-bucket fixups needed.
3. Size-based fallback: transmit full when len(delta) >= len(full).

Results: window mode 1.20x compression, correct_recon=true, accuracy unchanged (0.29%).

Changes to sketchlib-go (optimize-dd-delta branch):

• Rewrote DDSketch/delta.go — incremental-sketch approach, removes protobuf dependency
• Added SubtractFromBucket to DDSketch.go

KLL: no delta support, accurate full-sketch baseline (0.23-0.30%)

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correct_recon summary

Configuration	correct_recon
CMS/CS/HLL/DD window+delta	all windows
CMS/CS batch+delta	all windows (additive cell deltas are exact)
DD batch	N/A — delta skipped; full payload already maximally compact

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E2E bench_delta.sh results

Parameters: 60s per scenario, 1000 series, rates 10k and 50k MPS, modes sdkSketch / colBatch / colWindow.

Notes:

• The full live matrix completed locally against live collector binaries.
• The first HLL delta-enabled runs exposed a stale HLL binary that did not include the new delta_transmission config field. After rebuilding HLL, I reran the full HLL slice and used those rerun rows for the final HLL numbers below.
• The script's bandwidth metric is loopback TX sampled during the run, so the clearest delta wins show up in collector CPU/memory rather than in every bandwidth row.

Selected 50k MPS live results

Sketch	Mode	Delta	BW avg KB/s	SDK CPU%	Col CPU%	Col Mem MB
ddsketch	sdkSketch	off	2037.33	46.72	2.07	218.96
ddsketch	sdkSketch	on	2042.88	48.69	2.07	218.71
ddsketch	colBatch	off	2190.52	98.33	72.97	199.06
ddsketch	colBatch	on	1502.24	74.09	84.95	200.79
ddsketch	colWindow	off	2588.11	109.36	16.94	201.36
ddsketch	colWindow	on	2588.09	109.04	19.08	207.85
kll	sdkSketch	off	1129.59	38.77	18.33	238.88
kll	colBatch	off	1010.01	55.02	160.96	1567.76
kll	colWindow	off	2580.55	109.15	16.31	75.93
hll	sdkSketch	off	15845.78	40.75	8.37	260.95
hll	sdkSketch	on	15840.94	39.85	7.64	332.01
hll	colBatch	off	197.95	23.34	88.61	5588.31
hll	colWindow	off	2584.28	110.44	16.43	303.00
hll	colWindow	on	2584.10	109.64	16.36	209.70
countsketch	sdkSketch	off	10241.01	47.66	3.43	154.79
countsketch	sdkSketch	on	10240.89	45.83	3.55	142.62
countsketch	colBatch	off	2585.11	111.20	19.25	776.76
countsketch	colBatch	on	2585.42	110.12	28.36	46.25
countsketch	colWindow	off	2585.07	109.21	12.74	39.70
countsketch	colWindow	on	2585.10	109.18	12.96	38.44
countminsketch	sdkSketch	off	29236.18	59.77	10.56	474.21
countminsketch	sdkSketch	on	29232.76	59.44	10.13	479.82
countminsketch	colBatch	off	29.75	16.79	99.69	2010.39
countminsketch	colBatch	on	74.76	18.78	91.93	2180.24
countminsketch	colWindow	off	2535.15	109.27	42.16	3342.99
countminsketch	colWindow	on	2535.04	108.87	40.35	2211.78

E2E takeaways

• CountSketch shows the clearest collector-side delta win. In colBatch at 50k MPS, collector memory drops from 776.76 MB to 46.25 MB with delta enabled; at 10k MPS it drops from 181.17 MB to 38.92 MB.
• HLL benefits in colWindow after rebuilding the live binary. At 50k MPS, collector memory falls from 303.00 MB to 209.70 MB; at 10k MPS, from 285.48 MB to 187.98 MB.
• DDSketch shows a bandwidth win in colBatch at 50k. Average loopback bandwidth drops from 2190.52 KB/s to 1502.24 KB/s, while collector memory stays roughly flat around 200 MB.
• CountMinSketch delta helps in colWindow, but the collector remains heavy. At 50k MPS, collector memory drops from 3342.99 MB to 2211.78 MB; colBatch remains >2 GB either way.
• KLL remains the full-sketch baseline. There is no delta path; the heaviest KLL configuration is colBatch at 50k MPS with 1567.76 MB collector memory.

Test plan

• go build ./cmd/deltaaccbench compiles cleanly
• Smoke test: --sketch=all --windows=3 --inserts=300 passes
• Full benchmark: 20 windows × 5000 inserts, results in table above
• DDSketch delta now 1.20x (window) vs previous broken 0.50x
• DDSketch batch delta removed — full is already maximally compact
• Rebuilt HLL and reran --sketch hll --mode all so delta-enabled HLL rows are included in the e2e results
• e2e bench_delta.sh --sketch all --mode all --duration 60s completed locally against live collector binaries

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