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1 change: 0 additions & 1 deletion .gitignore
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Expand Up @@ -10,5 +10,4 @@ build/
venv/
.venv/
.idea/
results/
logs/
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{
"run_id": "2b7731aedcf24574a76987efc93e01d5",
"task_label": "2025112810",
"results": [
{
"metrics": {
"max_load_count": 0,
"insert_duration": 0,
"optimize_duration": 0,
"load_duration": 0,
"qps": 328.772,
"serial_latency_p99": 0.0184,
"serial_latency_p95": 0.0169,
"recall": 0.9983,
"ndcg": 0.9984,
"conc_num_list": [
1,
5,
10,
20,
30,
40,
60,
80
],
"conc_qps_list": [
74.0598,
247.3597,
323.0974,
326.6714,
325.9711,
326.109,
327.0808,
328.772
],
"conc_latency_p99_list": [
0.017595845824107528,
0.028741827234625816,
0.04373327549546957,
0.08262120254337789,
0.11297819921746849,
0.14499322351068258,
0.22070514821447432,
0.323815074507147
],
"conc_latency_p95_list": [
0.01655156835913658,
0.026233703596517444,
0.04003582429140806,
0.07535540163516997,
0.10579421008005738,
0.13709212997928263,
0.21008139979094267,
0.3113258379977196
],
"conc_latency_avg_list": [
0.013500699638887824,
0.020207179967241768,
0.030934518305094215,
0.06117603413692736,
0.0919196840900463,
0.12243950031881758,
0.1829535317926977,
0.24257953358352213
],
"st_ideal_insert_duration": 0,
"st_search_stage_list": [],
"st_search_time_list": [],
"st_max_qps_list_list": [],
"st_recall_list": [],
"st_ndcg_list": [],
"st_serial_latency_p99_list": [],
"st_serial_latency_p95_list": [],
"st_conc_failed_rate_list": []
},
"task_config": {
"db": "TencentElasticsearch",
"db_config": {
"db_label": "sa5-1node",
"version": "",
"note": "",
"scheme": "http",
"host": "10.0.228.48",
"port": 9200,
"user": "elastic",
"password": "**********"
},
"db_case_config": {
"element_type": "float",
"index": "vsearch",
"number_of_shards": 1,
"number_of_replicas": 0,
"refresh_interval": "-1",
"merge_max_thread_count": 8,
"use_rescore": false,
"oversample_ratio": 2,
"use_routing": false,
"use_force_merge": true,
"metric_type": "COSINE",
"efConstruction": 200,
"M": 16,
"num_candidates": 4000
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Thank you for sharing your test results on Tencent-ES with us. However, the num_candidates parameter appears to be set higher than typical. For tasks targeting top-100 retrieval, it is common to set this value around 100, which can achieve recall=0.9. Here, setting it to 4000 achieves a recall above 0.99, but it also significantly increases computational overhead. Please confirm whether this meets your expectations.

},
"case_config": {
"case_id": 11,
"custom_case": null,
"k": 100,
"concurrency_search_config": {
"num_concurrency": [
1,
5,
10,
20,
30,
40,
60,
80
],
"concurrency_duration": 30,
"concurrency_timeout": 3600
}
},
"stages": [
"drop_old",
"load",
"search_serial",
"search_concurrent"
]
},
"label": ":)"
}
],
"file_fmt": "result_{}_{}_{}.json",
"timestamp": 1764259200
}
3 changes: 3 additions & 0 deletions vectordb_bench/results/dbPrices.json
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"OpenSearch": {
"16c128g": 1.418,
"16c128g-force_merge": 1.418
},
"TencentElasticsearch": {
"sa5-1node": 0.95
}
}
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