2026-06-14T15-20-30Z_pgvector-S1-ivfflat-hybrid-r3
pgvectorStufe S1 · 5.00 GBhybridStatus: ok
Metriken
Throughput
7.2 QPS
Latenz ⌀
139.74 ms
Latenz p50
122.17 ms
Latenz p95
221.20 ms
Latenz p99
328.64 ms
Recall@1
10.20%
Recall@10
25.53%
Recall@100
30.80%
Precision@10
25.53%
NDCG@10
35.45%
Rohdaten
summary.json ↗Vollständige Run-Metrikenhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-14T15-20-30Z_pgvector-S1-ivfflat-hybrid-r3/summary.jsonconfig.json ↗Eingesetzte Konfigurationhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-14T15-20-30Z_pgvector-S1-ivfflat-hybrid-r3/config.jsonDatensatz · 5.00 GB ↗Generator + Bauanleitung im RepoRun-Ordner auf GitHub ↗Beide Rohdateien im Verzeichnis
Konfiguration
- Config-Name
- pgvector-S1-ivfflat-hybrid
- DB-Version
- —
- Image
- —
- Index-Typ
- ivfflat
- Index-Params
- {"lists":1200,"probes":10}
- Dataset
- S1 · 1.350.000 Vektoren · dim 1024 · Variante A · 5.00 GB
- Queries
- 2.000 (Concurrency 1)
Lauf
- Gestartet
- 14.06.2026, 17:20:30
- Beendet
- 14.06.2026, 17:25:15
- Dauer
- 7485s
- Index-Bauzeit
- 157.83s
- Index-Größe
- 10556.3 MB
- CPU ⌀ / Peak
- 0.44 / 1.15 cores
- RAM ⌀ / Peak
- 7447 / 7479 MB
- Disk read (Paging)
- 33038 MB
- Disk write
- 122 MB
- Pod-RAM-Limit
- 8 GiB
- Warmup-Queries
- 1.000
- K8s
- v1.31.4+k3s1
- Nodes
- 4
Notizen
measured: in-cluster decoupled: true ingested_at: 2026-06-14T15:00:37Z ingest_config: pgvector-S1-ivfflat insert_time_s: 522.73 n_vectors_actual: 1350000 has_metadata: true mem_limit_gb: 8 pre_run_reset: skipped (decoupled, warmup-discard) n_queries_executed: 1000 n_warmup: 1000 gt_file: ground_truth_hybrid_alpha_50_ids.npy mode: measure-only repeat_group: 2026-06-14T15-10-44Z_pgvector-S1-ivfflat-hybrid repeat_index: 3 repeat_total: 3