2026-06-19T06-48-56Z_pgvector-S1-tune-hybrid-a30-r2
pgvectorStufe S1 · 5.00 GBhybridStatus: ok
Metriken
Throughput
8.3 QPS
Latenz ⌀
119.99 ms
Latenz p50
103.93 ms
Latenz p95
187.55 ms
Latenz p99
297.02 ms
Recall@1
4.60%
Recall@10
5.22%
Recall@100
7.64%
Precision@10
5.22%
NDCG@10
6.12%
Rohdaten
summary.json ↗Vollständige Run-Metrikenhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-19T06-48-56Z_pgvector-S1-tune-hybrid-a30-r2/summary.jsonconfig.json ↗Eingesetzte Konfigurationhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-19T06-48-56Z_pgvector-S1-tune-hybrid-a30-r2/config.jsonDatensatz · 5.00 GB ↗Generator + Bauanleitung im RepoRun-Ordner auf GitHub ↗Beide Rohdateien im Verzeichnis
Konfiguration
- Config-Name
- pgvector-S1-tune-hybrid-a30
- 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
- 1.000 (Concurrency 1)
Lauf
- Gestartet
- 19.06.2026, 08:48:56
- Beendet
- 19.06.2026, 08:52:59
- Dauer
- 7443s
- Index-Bauzeit
- 160.1s
- Index-Größe
- 10556.3 MB
- CPU ⌀ / Peak
- 0.48 / 1.07 cores
- RAM ⌀ / Peak
- 7446 / 7480 MB
- Disk read (Paging)
- 33110 MB
- Disk write
- 9 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: 2026-06-19T06:19:44Z ingest_config: pgvector-S1-ivfflat insert_time_s: 541.61 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_30_ids.npy mode: measure-only repeat_group: 2026-06-19T06-44-44Z_pgvector-S1-tune-hybrid-a30 repeat_index: 2 repeat_total: 6