2026-06-14T15-07-11Z_pgvector-S1-ivfflat-filtered-r2
pgvectorStufe S1 · 5.00 GBfilteredStatus: ok
Metriken
Throughput
20.7 QPS
Latenz ⌀
48.32 ms
Latenz p50
43.28 ms
Latenz p95
93.08 ms
Latenz p99
123.58 ms
Recall@1
62.30%
Recall@10
58.18%
Recall@100
50.70%
Precision@10
58.18%
NDCG@10
69.23%
Rohdaten
summary.json ↗Vollständige Run-Metrikenhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-14T15-07-11Z_pgvector-S1-ivfflat-filtered-r2/summary.jsonconfig.json ↗Eingesetzte Konfigurationhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-14T15-07-11Z_pgvector-S1-ivfflat-filtered-r2/config.jsonDatensatz · 5.00 GB ↗Generator + Bauanleitung im RepoRun-Ordner auf GitHub ↗Beide Rohdateien im Verzeichnis
Konfiguration
- Config-Name
- pgvector-S1-ivfflat-filtered
- 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, 17:07:11
- Beendet
- 14.06.2026, 17:08:53
- Dauer
- 7302s
- Index-Bauzeit
- 157.83s
- Index-Größe
- 10556.3 MB
- CPU ⌀ / Peak
- 0.40 / 0.44 cores
- RAM ⌀ / Peak
- 7470 / 7495 MB
- Disk read (Paging)
- 14617 MB
- Disk write
- 53 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_filter_rating_gte_4_ids.npy mode: measure-only repeat_group: 2026-06-14T15-05-27Z_pgvector-S1-ivfflat-filtered repeat_index: 2 repeat_total: 3