2026-06-18T07-10-29Z_pgvector-S1-ivfflat-throughput-c8-r6
pgvectorStufe S1 · 5.00 GBbatchStatus: ok
Metriken
Throughput
20.7 QPS
Latenz ⌀
384.62 ms
Latenz p50
378.93 ms
Latenz p95
481.86 ms
Latenz p99
540.26 ms
Recall@1
67.70%
Recall@10
63.70%
Recall@100
55.71%
Precision@10
63.70%
NDCG@10
73.65%
Rohdaten
summary.json ↗Vollständige Run-Metrikenhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-18T07-10-29Z_pgvector-S1-ivfflat-throughput-c8-r6/summary.jsonconfig.json ↗Eingesetzte Konfigurationhttps://raw.githubusercontent.com/unrealshape/bachelor-db-benchmark/main/results/2026-06-18T07-10-29Z_pgvector-S1-ivfflat-throughput-c8-r6/config.jsonDatensatz · 5.00 GB ↗Generator + Bauanleitung im RepoRun-Ordner auf GitHub ↗Beide Rohdateien im Verzeichnis
Konfiguration
- Config-Name
- pgvector-S1-ivfflat-throughput-c8
- 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 8)
Lauf
- Gestartet
- 18.06.2026, 09:10:29
- Beendet
- 18.06.2026, 09:12:11
- Dauer
- 7302s
- Index-Bauzeit
- 162.47s
- Index-Größe
- 10556.3 MB
- CPU ⌀ / Peak
- 0.33 / 0.42 cores
- RAM ⌀ / Peak
- 7448 / 7464 MB
- Disk read (Paging)
- 16827 MB
- Disk write
- 3 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: 2026-06-18T07:01:29Z ingest_config: pgvector-S1-ivfflat insert_time_s: 546.25 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_ids.npy mode: measure-only repeat_group: 2026-06-18T07-01-30Z_pgvector-S1-ivfflat-throughput-c8 repeat_index: 6 repeat_total: 6