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2026-06-19T04-26-33Z_pgvector-M-throughput-c8-r6

pgvectorStufe M · 20.00 GBbatchStatus: ok

Metriken

Throughput
2.8 QPS
Latenz ⌀
2860.97 ms
Latenz p50
2869.55 ms
Latenz p95
3495.02 ms
Latenz p99
3742.44 ms
Recall@1
71.70%
Recall@10
68.03%
Recall@100
62.47%
Precision@10
68.03%
NDCG@10
77.12%

Rohdaten

Konfiguration

Config-Name
pgvector-M-throughput-c8
DB-Version
Image
Index-Typ
ivfflat
Index-Params
{"lists":4900,"probes":10}
Dataset
M · 5.250.000 Vektoren · dim 1024 · Variante A · 20.00 GB
Queries
2.000 (Concurrency 8)

Lauf

Gestartet
19.06.2026, 06:26:33
Beendet
19.06.2026, 06:38:45
Dauer
7932s
Index-Bauzeit
500.1s
Index-Größe
41023.4 MB
CPU ⌀ / Peak
0.44 / 0.50 cores
RAM ⌀ / Peak
7458 / 7560 MB
Disk read (Paging)
447769 MB
Disk write
10 MB
Pod-RAM-Limit
Default
Warmup-Queries
1.000
K8s
v1.31.4+k3s1
Nodes
4

Notizen

measured: in-cluster
decoupled: true
ingested_at: 2026-06-19T03:24:44Z
ingest_config: pgvector-M-ivfflat
insert_time_s: 2051.38
n_vectors_actual: 5250000
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: 2026-06-19T03-24-44Z_pgvector-M-throughput-c8
repeat_index: 6
repeat_total: 6