2026-06-18T07-49-27Z_pgvector-S-ivfflat-throughput-c8-r4
pgvectorStufe S · 10.00 GBbatchStatus: ok
Metriken
Throughput
7.0 QPS
Latenz ⌀
1135.38 ms
Latenz p50
1134.33 ms
Latenz p95
1459.75 ms
Latenz p99
1580.23 ms
Recall@1
71.70%
Recall@10
66.94%
Recall@100
60.34%
Precision@10
66.94%
NDCG@10
76.29%
Rohdaten
summary.json ↗Vollständige Run-Metrikenhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-18T07-49-27Z_pgvector-S-ivfflat-throughput-c8-r4/summary.jsonconfig.json ↗Eingesetzte Konfigurationhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-18T07-49-27Z_pgvector-S-ivfflat-throughput-c8-r4/config.jsonDatensatz · 10.00 GB ↗Generator + Bauanleitung im RepoRun-Ordner auf GitHub ↗Beide Rohdateien im Verzeichnis
Konfiguration
- Config-Name
- pgvector-S-ivfflat-throughput-c8
- DB-Version
- —
- Image
- —
- Index-Typ
- ivfflat
- Index-Params
- {"lists":1000,"probes":10}
- Dataset
- S · 2.650.000 Vektoren · dim 1024 · Variante A · 10.00 GB
- Queries
- 10.000 (Concurrency 8)
Lauf
- Gestartet
- 18.06.2026, 09:49:27
- Beendet
- 18.06.2026, 09:54:17
- Dauer
- 7490s
- Index-Bauzeit
- 264.3s
- Index-Größe
- 20710.9 MB
- CPU ⌀ / Peak
- 0.44 / 0.47 cores
- RAM ⌀ / Peak
- 7449 / 7477 MB
- Disk read (Paging)
- 133962 MB
- Disk write
- 19 MB
- Pod-RAM-Limit
- Default
- Warmup-Queries
- 1.000
- K8s
- v1.31.4+k3s1
- Nodes
- 4
Notizen
measured: in-cluster decoupled: true ingested_at: 2026-06-18T07:34:21Z ingest_config: pgvector-S-ivfflat insert_time_s: 1043.52 n_vectors_actual: 2650000 has_metadata: true mem_limit_gb: null pre_run_reset: skipped (decoupled, warmup-discard) n_queries_executed: 1000 n_warmup: 1000 gt_file: ground_truth_ids.npy mode: measure-only repeat_group: 2026-06-18T07-34-21Z_pgvector-S-ivfflat-throughput-c8 repeat_index: 4 repeat_total: 6