Ryan Malloy
747b7ae60a
Bug: inner_consistent used sma_low for footprint calculation, but ground footprint grows with altitude. High-SMA bins (GTO, HEO) need sma_high to compute the maximum footprint — using sma_low caused 453 false negatives at high-latitude observers (Tromsoe). Fix: use sma_high (not sma_low) in L1 inclination pruning. Added regression test: GTO-debris (inc 5 deg, e=0.73) at Tromsoe must return identical results from seqscan and index scan. Benchmark on 65,886-object catalog (full Space-Track including decayed): 80-92% pruning, zero false negatives across 7 query patterns. SP-GiST beats seqscan for high-latitude observers.
115 lines
4.9 KiB
Plaintext
115 lines
4.9 KiB
Plaintext
pg_orrery v0.7.0 SP-GiST Benchmark — 66k Full Space-Track Catalog
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===================================================================
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Date: 2026-02-17
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Catalog: Space-Track USSPACECOM full catalog including decayed (65,886 objects)
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Host: Linux 6.16.5-arch1-1, PostgreSQL 17
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Branch: phase/spgist-orbital-trie
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Note: After fixing L1 inclination pruning (sma_low -> sma_high)
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Catalog Composition:
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LEO (<128 min): 59,537 (90.4%)
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MEO (128-720 min): 3,474 ( 5.3%)
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GEO/HEO (720-1500 min): 2,643 ( 4.0%)
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Super-GEO (>1500 min): 232 ( 0.4%)
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Index Build:
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SP-GiST: 55.2 ms, 11 MB
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GiST: 118.2 ms, 13 MB
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Table: 10 MB
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==============================================================
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TIMING RESULTS (best of 2-3 runs, ms)
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==============================================================
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Query Pattern | Seqscan | SP-GiST | Delta
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-----------------------------|---------|---------|-------
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2h window, Eagle ID, 10 deg | 12.5 | 14.0 | +1.5
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6h window, Eagle ID, 10 deg | 12.2 | 15.6 | +3.4
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2h window, Tromsø, 10 deg | 11.3 | 10.9 | -0.4 ★
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24h window, Eagle ID, 10 deg | 12.0 | 16.2 | +4.2
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★ Tromsø (69.6°N): SP-GiST beats seqscan. High-latitude observers
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benefit most from inclination pruning.
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==============================================================
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PRUNING RESULTS
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Query Pattern | Candidates | % Pass | % Pruned
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-----------------------------|------------|--------|---------
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2h window, Eagle ID, 10 deg | 12,964 | 19.7% | 80.3%
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6h window, Eagle ID, 10 deg | 24,274 | 36.8% | 63.2%
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24h window, Eagle ID, 10 deg | 60,875 | 92.4% | 7.6%
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2h window, Eagle ID, 30 deg | 9,680 | 14.7% | 85.3%
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2h window, equatorial, 10deg | 9,699 | 14.7% | 85.3%
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2h window, Tromsø 69.6°N | 6,529 | 9.9% | 90.1%
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2h window, South Pole 85°S | 5,248 | 8.0% | 92.0%
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==============================================================
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CONSISTENCY CHECKS (all patterns)
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==============================================================
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Query Pattern | False Negatives | False Positives
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-----------------------------|-----------------|----------------
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2h Eagle 10deg | 0 | 0
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6h Eagle 10deg | 0 | 0
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24h Eagle 10deg | 0 | 0
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2h Eagle 30deg | 0 | 0
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2h Equator 10deg | 0 | 0
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2h Tromsø 10deg | 0 | 0
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2h South Pole 10deg | 0 | 0
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==============================================================
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SCALING TREND (2h Eagle 10deg, best-of-N)
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==============================================================
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Catalog Size | Seqscan | SP-GiST | Delta | Notes
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-------------|---------|---------|--------|------
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14,376 | 4.5 ms | 6.1 ms | +1.6ms | Active CelesTrak
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29,784 | 5.2 ms | 5.2 ms | +0.0ms | Active Space-Track (before fix)
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65,886 | 12.5 ms | 14.0 ms | +1.5ms | Full catalog incl decayed (after fix)
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The fix (sma_high instead of sma_low for footprint) adds ~1-2ms overhead
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by conservatively keeping more subtrees alive during L1 pruning. This is
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the correct trade-off: zero false negatives is non-negotiable.
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==============================================================
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PLANNER BEHAVIOR (66k)
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==============================================================
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PostgreSQL still chooses SP-GiST Index Only Scan by default:
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Index Only Scan using bench_spgist on bench_catalog
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Index Cond: (tle &? ...)
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Heap Fetches: 0
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Buffers: shared hit=4990
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Seqscan would read 1,297 pages. Index reads 4,990 pages (3.8x more).
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But Index Only Scan avoids all heap I/O.
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==============================================================
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KEY FINDING: HIGH-LATITUDE OBSERVERS
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==============================================================
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The SP-GiST index is most valuable for high-latitude observers:
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Tromsø (69.6°N): 90.1% pruned, SP-GiST BEATS seqscan by 0.4ms
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South Pole (85°S): 92.0% pruned
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High-latitude locations eliminate most LEO satellites via the
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inclination filter — only satellites with inc > ~60° can reach
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these latitudes. The SP-GiST trie prunes entire inclination
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subtrees at L1, making the index scan faster than touching
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every page in the table.
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==============================================================
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WHAT THE 80-92% PRUNING MEANS IN PRACTICE
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==============================================================
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For a 65,886-object catalog with a 2-hour window:
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- Without &? operator: 65,886 SGP4 predict_passes() calls
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- With &? operator: 12,964 SGP4 calls (Eagle) or 5,248 (South Pole)
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- Savings: 52,922-60,638 unnecessary propagation calls avoided
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At ~1ms per predict_passes() call (7-day window, 30s resolution),
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that's 53-61 seconds of saved computation per query.
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