{"id":113859,"date":"2026-10-07T19:17:40","date_gmt":"2026-10-07T11:17:40","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/113859.html"},"modified":"2026-10-07T19:17:40","modified_gmt":"2026-10-07T11:17:40","slug":"faiss-%e7%b4%a2%e5%bc%95%e6%80%8e%e4%b9%88%e9%80%89%ef%bc%9a10-%e4%b8%87%e6%9d%a1-128-%e7%bb%b4%e5%90%91%e9%87%8f%e4%b8%8a-ivf%e3%80%81pq%e3%80%81hnsw-%e7%9a%84%e5%8f%ac%e5%9b%9e%e4%b8%8e%e5%bb%b6","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/113859.html","title":{"rendered":"Faiss \u7d22\u5f15\u600e\u4e48\u9009\uff1a10 \u4e07\u6761 128 \u7ef4\u5411\u91cf\u4e0a IVF\u3001PQ\u3001HNSW \u7684\u53ec\u56de\u4e0e\u5ef6\u8fdf\u5b9e\u6d4b"},"content":{"rendered":"

\u624b\u91cc\u6709 10 \u4e07\u6761 128 \u7ef4\u5411\u91cf\u3001\u673a\u5668\u53ea\u6709 2 \u6838\u7684\u65f6\u5019，Faiss \u91cc\u6700\u5148\u8be5\u8bd5\u7684\u4e0d\u662f HNSW，\u800c\u662f\u5012\u6392\u8868\u4e0d\u52a0\u538b\u7f29\u7684 IVF：nprobe=16 \u5c31\u80fd\u628a\u53ec\u56de\u505a\u5230\u548c\u66b4\u529b\u68c0\u7d22\u4e00\u6837（1.000），\u5355\u6761\u67e5\u8be2\u4ece 0.452 ms \u6389\u5230 0.195 ms\u3002HNSW \u66f4\u5feb，0.031 ms \u62ff\u5230 0.998 \u7684\u53ec\u56de，\u4ee3\u4ef7\u662f\u7d22\u5f15\u4f53\u79ef\u53d8\u6210\u539f\u59cb\u5411\u91cf\u7684 1.53 \u500d\u3001\u5165\u5e93 2.93 \u79d2（IVF \u53ea\u8981 0.10 \u79d2）\u3002PQ \u538b\u7f29\u80fd\u628a\u7d22\u5f15\u538b\u5230 1\/20，\u4f46\u53ec\u56de\u53ea\u5269 0.337，\u800c\u4e14\u8c03 nprobe \u5b8c\u5168\u6551\u4e0d\u56de\u6765\u2014\u2014\u74f6\u9888\u5728\u538b\u7f29\u7801\u672c，\u4e0d\u5728\u626b\u591a\u5c11\u4e2a\u5012\u6392\u6876\u3002<\/p>\n

\u4e0b\u9762\u8fd9\u7ec4\u6570\u5168\u90e8\u5728\u4e00\u53f0 2 \u6838\u673a\u5668\u4e0a\u8dd1\u51fa\u6765：faiss-cpu 1.15.1\u3001numpy 2.5.3，10 \u4e07\u6761 128 \u7ef4 float32 \u5411\u91cf，1000 \u6761\u67e5\u8be2，top-10\u3002<\/p>\n

\"10<\/p>\n

\u5b9e\u9a8c\u600e\u4e48\u642d\u7684<\/h3>\n

\u6570\u636e\u7528 2000 \u4e2a\u7c07\u5fc3\u52a0\u9ad8\u65af\u566a\u58f0\u5408\u6210，\u6a21\u62df\u771f\u5b9e embedding \u7684\u7c07\u7ed3\u6784：512 \u5b57\u8282\u4e00\u6761\u7684\u5411\u91cf，\u603b\u5171 48.8 MB\u3002\u8bc4\u6d4b\u53e3\u5f84\u662f\u53ec\u56de@10\u2014\u2014\u7528\u66b4\u529b\u68c0\u7d22（IndexFlatL2）\u7684\u7ed3\u679c\u5f53\u6807\u51c6\u7b54\u6848，\u770b\u8fd1\u4f3c\u7d22\u5f15\u7684\u524d 10 \u6761\u91cc\u547d\u4e2d\u4e86\u51e0\u6761\u3002<\/p>\n

import<\/span> faiss,<\/span> numpy as<\/span> np,<\/span> time<\/p>\n

np.<\/span>random.<\/span>seed(<\/span>7<\/span>)<\/span>
\nd,<\/span> nb,<\/span> nq,<\/span> k,<\/span> nc =<\/span> 128<\/span>,<\/span> 100_000<\/span>,<\/span> 1000<\/span>,<\/span> 10<\/span>,<\/span> 2000<\/span>
\ncenters =<\/span> np.<\/span>random.<\/span>rand(<\/span>nc,<\/span> d)<\/span>.<\/span>astype(<\/span>"float32"<\/span>)<\/span>
\nxb =<\/span> (<\/span>centers[<\/span>np.<\/span>random.<\/span>randint(<\/span>0<\/span>,<\/span> nc,<\/span> nb)<\/span>]<\/span> +<\/span> 0.08<\/span> *<\/span> np.<\/span>random.<\/span>randn(<\/span>nb,<\/span> d)<\/span>)<\/span>.<\/span>astype(<\/span>"float32"<\/span>)<\/span>
\nxq =<\/span> (<\/span>centers[<\/span>np.<\/span>random.<\/span>randint(<\/span>0<\/span>,<\/span> nc,<\/span> nq)<\/span>]<\/span> +<\/span> 0.08<\/span> *<\/span> np.<\/span>random.<\/span>randn(<\/span>nq,<\/span> d)<\/span>)<\/span>.<\/span>astype(<\/span>"float32"<\/span>)<\/span><\/p>\n

# \u66b4\u529b\u68c0\u7d22\u65e2\u5f53\u57fa\u7ebf，\u4e5f\u5f53\u6807\u51c6\u7b54\u6848<\/span>
\nflat =<\/span> faiss.<\/span>IndexFlatL2(<\/span>d)<\/span>
\nflat.<\/span>add(<\/span>xb)<\/span>
\n_,<\/span> gt =<\/span> flat.<\/span>search(<\/span>xq,<\/span> k)<\/span> # gt: (1000, 10) \u7684\u90bb\u5c45 id<\/span><\/p>\n

def<\/span> recall<\/span>(<\/span>I)<\/span>:<\/span>
\n return<\/span> float<\/span>(<\/span>np.<\/span>mean(<\/span>[<\/span>len<\/span>(<\/span>set<\/span>(<\/span>I[<\/span>i]<\/span>)<\/span> &<\/span> set<\/span>(<\/span>gt[<\/span>i]<\/span>)<\/span>)<\/span> \/<\/span> k for<\/span> i in<\/span> range<\/span>(<\/span>len<\/span>(<\/span>I)<\/span>)<\/span>]<\/span>)<\/span>)<\/span><\/p>\n

def<\/span> bench<\/span>(<\/span>name,<\/span> index,<\/span> need_train=<\/span>True<\/span>)<\/span>:<\/span>
\n t0 =<\/span> time.<\/span>perf_counter(<\/span>)<\/span>
\n if<\/span> need_train:<\/span>
\n index.<\/span>train(<\/span>xb)<\/span> # IVF\/PQ \u5fc5\u987b\u5148\u8bad\u7ec3<\/span>
\n t_train =<\/span> time.<\/span>perf_counter(<\/span>)<\/span> –<\/span> t0
\n t0 =<\/span> time.<\/span>perf_counter(<\/span>)<\/span>;<\/span> index.<\/span>add(<\/span>xb)<\/span>;<\/span> t_add =<\/span> time.<\/span>perf_counter(<\/span>)<\/span> –<\/span> t0
\n t0 =<\/span> time.<\/span>perf_counter(<\/span>)<\/span>;<\/span> _,<\/span> I =<\/span> index.<\/span>search(<\/span>xq,<\/span> k)<\/span>;<\/span> t_q =<\/span> time.<\/span>perf_counter(<\/span>)<\/span> –<\/span> t0
\n print<\/span>(<\/span>f"<\/span>{<\/span>name}<\/span><\/span>: \u8bad\u7ec3 <\/span>{<\/span>t_train:<\/span>.2f<\/span>}<\/span><\/span>s \u5165\u5e93 <\/span>{<\/span>t_add:<\/span>.2f<\/span>}<\/span><\/span>s "<\/span><\/span>
\n f"\u67e5\u8be2 <\/span>{<\/span>t_q \/<\/span> nq *<\/span> 1000<\/span>:<\/span>.3f<\/span>}<\/span><\/span> ms\/\u6761 \u53ec\u56de@10 <\/span>{<\/span>recall(<\/span>I)<\/span>:<\/span>.3f<\/span>}<\/span><\/span>"<\/span><\/span>)<\/span>
\n return<\/span> I<\/p>\n

ivf =<\/span> faiss.<\/span>IndexIVFFlat(<\/span>faiss.<\/span>IndexFlatL2(<\/span>d)<\/span>,<\/span> d,<\/span> 256<\/span>)<\/span> # 256 \u4e2a\u5012\u6392\u6876<\/span>
\nivf.<\/span>nprobe =<\/span> 16<\/span> # \u6bcf\u6b21\u626b 16 \u4e2a\u6876<\/span>
\nbench(<\/span>"IVF256,Flat nprobe=16"<\/span>,<\/span> ivf)<\/span><\/p>\n

pq =<\/span> faiss.<\/span>IndexIVFPQ(<\/span>faiss.<\/span>IndexFlatL2(<\/span>d)<\/span>,<\/span> d,<\/span> 256<\/span>,<\/span> 16<\/span>,<\/span> 8<\/span>)<\/span> # 16 \u4e2a\u5b50\u91cf\u5316\u5668 x 8 bit<\/span>
\npq.<\/span>nprobe =<\/span> 32<\/span>
\nbench(<\/span>"IVF256,PQ16x8 nprobe=32"<\/span>,<\/span> pq)<\/span><\/p>\n

hnsw =<\/span> faiss.<\/span>IndexHNSWFlat(<\/span>d,<\/span> 32<\/span>)<\/span> # \u56fe\u7d22\u5f15\u4e0d\u9700\u8981\u8bad\u7ec3<\/span>
\nhnsw.<\/span>hnsw.<\/span>efSearch =<\/span> 64<\/span>
\nbench(<\/span>"HNSW32 efSearch=64"<\/span>,<\/span> hnsw,<\/span> need_train=<\/span>False<\/span>)<\/span><\/p>\n

\u56db\u79cd\u7d22\u5f15\u7684\u5b9e\u6d4b\u7ed3\u679c<\/h3>\n\n\u7d22\u5f15\u8bad\u7ec3\u8017\u65f6\u5165\u5e93\u8017\u65f6\u67e5\u8be2 ms\/\u6761\u53ec\u56de@10\u7d22\u5f15\u6587\u4ef6\u4f53\u79ef\u500d\u7387<\/tr>\n\n\n\n\n\n\n
Flat（\u66b4\u529b，\u57fa\u7ebf）<\/td>\n\u4e0d\u9700\u8981<\/td>\n0.02 s<\/td>\n0.452<\/td>\n1.000<\/td>\n48.8 MB<\/td>\n1.00<\/td>\n<\/tr>\n
IVF256,Flat nprobe=16<\/td>\n0.70 s<\/td>\n0.10 s<\/td>\n0.195<\/td>\n1.000<\/td>\n49.7 MB<\/td>\n1.02<\/td>\n<\/tr>\n
HNSW32 efSearch=64<\/td>\n\u4e0d\u9700\u8981<\/td>\n2.93 s<\/td>\n0.031<\/td>\n0.998<\/td>\n74.8 MB<\/td>\n1.53<\/td>\n<\/tr>\n
IVF1024,PQ32x8 nprobe=32<\/td>\n5.37 s<\/td>\n0.51 s<\/td>\n0.063<\/td>\n0.573<\/td>\n4.4 MB<\/td>\n0.09<\/td>\n<\/tr>\n
IVF256,PQ16x8 nprobe=32<\/td>\n1.99 s<\/td>\n0.24 s<\/td>\n0.072<\/td>\n0.337<\/td>\n2.5 MB<\/td>\n0.05<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u53e3\u5f84\u8bf4\u660e：\u53ec\u56de@10 \u4ee5\u66b4\u529b\u68c0\u7d22\u7ed3\u679c\u4e3a\u6807\u51c6\u7b54\u6848；\u4f53\u79ef\u500d\u7387 = \u7d22\u5f15\u6587\u4ef6 \u00f7 \u539f\u59cb\u5411\u91cf 48.8 MB；\u67e5\u8be2\u8017\u65f6\u4e3a 1000 \u6761\u67e5\u8be2\u8fde\u7eed\u6267\u884c\u540e\u7684\u5e73\u5747\u503c，\u672a\u505a\u9884\u70ed\u5254\u9664\u3002<\/p>\n

Flat（\u57fa\u7ebf）: \u5165\u5e93 0.02s \u67e5\u8be2 0.452 ms\/\u6761 \u53ec\u56de 1.000
\nIVF256,Flat nprobe=16: \u8bad\u7ec3 0.70s \u5165\u5e93 0.10s \u67e5\u8be2 0.195 ms\/\u6761 \u53ec\u56de 1.000
\nIVF256,PQ16x8 nprobe=32: \u8bad\u7ec3 1.99s \u5165\u5e93 0.24s \u67e5\u8be2 0.072 ms\/\u6761 \u53ec\u56de 0.337
\nIVF1024,PQ32x8 nprobe=32: \u8bad\u7ec3 5.37s \u5165\u5e93 0.51s \u67e5\u8be2 0.063 ms\/\u6761 \u53ec\u56de 0.573
\nHNSW32 efSearch=64: \u5165\u5e93 2.93s \u67e5\u8be2 0.031 ms\/\u6761 \u53ec\u56de 0.998<\/p>\n

\u8fd9\u7ec4\u6570\u636e\u91cc\u6700\u80fd\u8bf4\u660e\u95ee\u9898\u7684\u662f IVF \u548c HNSW \u7684\u5dee\u522b：\u4e24\u8005\u53ec\u56de\u90fd\u5728 0.998 \u4ee5\u4e0a，\u4f46 HNSW \u7684\u67e5\u8be2\u5feb 6 \u500d，\u5165\u5e93\u6162 29 \u500d，\u7d22\u5f15\u5927 50%\u3002\u67e5\u8be2\u91cf\u5927\u7684\u5728\u7ebf\u670d\u52a1，\u8fd9\u70b9\u5dee\u5f02\u503c\u5f97；\u79bb\u7ebf\u6279\u5904\u7406\u6bcf\u5929\u8dd1\u4e00\u6b21\u7684\u573a\u666f，\u5c31\u6ca1\u5fc5\u8981\u4e3a HNSW \u4ed8\u8fd9\u4efd\u5165\u5e93\u4ee3\u4ef7\u3002<\/p>\n

\"\u56db\u79cd\u7d22\u5f15\u7684\u53ec\u56de\u3001\u5ef6\u8fdf\u4e0e\u4f53\u79ef\u7ed3\u8bba\"<\/p>\n

\u8c03 nprobe \u6551\u4e0d\u56de PQ<\/h3>\n

PQ \u7248\u672c\u7684\u53ec\u56de 0.337 \u770b\u7740\u96be\u53d7，\u7b2c\u4e00\u53cd\u5e94\u662f\u52a0\u5927 nprobe\u3002\u7ed3\u679c\u662f\u767d\u8d39\u529f\u592b：<\/p>\n

nprobe= 1 \u67e5\u8be2 0.005 ms\/\u6761 \u53ec\u56de@10 0.336
\nnprobe= 4 \u67e5\u8be2 0.012 ms\/\u6761 \u53ec\u56de@10 0.337
\nnprobe= 8 \u67e5\u8be2 0.021 ms\/\u6761 \u53ec\u56de@10 0.337
\nnprobe= 16 \u67e5\u8be2 0.040 ms\/\u6761 \u53ec\u56de@10 0.337
\nnprobe= 32 \u67e5\u8be2 0.076 ms\/\u6761 \u53ec\u56de@10 0.337
\nnprobe= 64 \u67e5\u8be2 0.132 ms\/\u6761 \u53ec\u56de@10 0.337
\nnprobe=128 \u67e5\u8be2 0.229 ms\/\u6761 \u53ec\u56de@10 0.337<\/p>\n

nprobe \u4ece 1 \u6da8\u5230 128，\u626b\u63cf\u7684\u6876\u6570\u91cf\u7ffb\u4e86 128 \u500d，\u67e5\u8be2\u8017\u65f6\u6da8\u4e86 46 \u500d，\u53ec\u56de\u4e00\u4f4d\u5c0f\u6570\u90fd\u6ca1\u52a8\u3002\u539f\u56e0\u4e0d\u96be\u7406\u89e3：\u6b63\u786e\u7684\u90a3\u6761\u90bb\u5c45\u65e9\u5c31\u88ab\u5012\u6392\u6876\u5708\u8fdb\u6765\u4e86，\u95ee\u9898\u51fa\u5728\u8ddd\u79bb\u662f\u7528 16 \u5b57\u8282\u7684\u538b\u7f29\u7801\u7b97\u7684，\u7b97\u51fa\u6765\u7684\u6392\u5e8f\u548c\u771f\u5b9e\u8ddd\u79bb\u4e0d\u4e00\u81f4，\u524d 10 \u540d\u88ab\u6324\u51fa\u53bb\u4e86\u3002\u626b\u66f4\u591a\u6876\u53ea\u4f1a\u5e26\u8fdb\u66f4\u591a\u540c\u6837\u88ab\u538b\u7f29\u7801\u626d\u66f2\u7684\u5019\u9009\u3002<\/p>\n

\u771f\u6b63\u7ba1\u7528\u7684\u65cb\u94ae\u662f\u6bcf\u4e2a\u5411\u91cf\u7684\u5b57\u8282\u6570\u3002\u628a\u5b50\u91cf\u5316\u5668\u6570\u91cf\u4ece 16 \u52a0\u5230 64，\u53ec\u56de\u4ece 0.337 \u5347\u5230 0.803，\u7d22\u5f15\u4e5f\u4ece 2.5 MB \u6da8\u5230 7.1 MB：<\/p>\n

\"PQ<\/p>\n\n\u5b50\u91cf\u5316\u5668 mnbits\u5b57\u8282\/\u5411\u91cf\u8bad\u7ec3\u8017\u65f6\u67e5\u8be2 ms\/\u6761\u53ec\u56de@10\u7d22\u5f15\u6587\u4ef6<\/tr>\n\n\n\n\n\n\n
8<\/td>\n8<\/td>\n8<\/td>\n1.63 s<\/td>\n0.048<\/td>\n0.244<\/td>\n1.8 MB<\/td>\n<\/tr>\n
16<\/td>\n8<\/td>\n16<\/td>\n1.94 s<\/td>\n0.075<\/td>\n0.337<\/td>\n2.5 MB<\/td>\n<\/tr>\n
32<\/td>\n8<\/td>\n32<\/td>\n2.86 s<\/td>\n0.110<\/td>\n0.509<\/td>\n4.1 MB<\/td>\n<\/tr>\n
64<\/td>\n8<\/td>\n64<\/td>\n4.97 s<\/td>\n0.229<\/td>\n0.803<\/td>\n7.1 MB<\/td>\n<\/tr>\n
32<\/td>\n6<\/td>\n24<\/td>\n1.62 s<\/td>\n0.643<\/td>\n0.425<\/td>\n3.2 MB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u53e3\u5f84\u8bf4\u660e：\u5168\u90e8\u4e3a IVF256 + nprobe=32，\u540c\u6837\u7684 10 \u4e07\u6761\u6570\u636e\u548c 1000 \u6761\u67e5\u8be2；\u5b57\u8282\/\u5411\u91cf = m \u00d7 nbits \u00f7 8，\u4e0e\u7d22\u5f15\u6587\u4ef6\u5927\u5c0f\u4e92\u76f8\u5370\u8bc1（16 \u5b57\u8282 \u00d7 10 \u4e07\u6761 = 1.6 MB，\u52a0\u7801\u672c\u548c\u5012\u6392\u8868\u540e\u662f 2.5 MB）\u3002<\/p>\n

\u8868\u91cc\u6700\u540e\u4e00\u884c\u662f\u4e2a\u610f\u5916\u7684\u5751：nbits=6 \u6bcf\u5411\u91cf\u53ea\u8981 24 \u5b57\u8282，\u6bd4 m=32\/nbits=8 \u7701 8 \u5b57\u8282，\u4f46\u67e5\u8be2\u4ece 0.110 ms \u53d8\u6210 0.643 ms，\u6162\u4e86\u8fd1 6 \u500d\u3002faiss \u7684 PQ \u8ddd\u79bb\u8ba1\u7b97\u53ea\u5bf9 nbits=8 \u548c 4 \u6709 SIMD \u5feb\u8def\u5f84，6 bit \u8d70\u901a\u7528\u8def\u5f84，\u7701\u4e0b\u7684\u90a3\u70b9\u4f53\u79ef\u5168\u88ab\u7b97\u529b\u5403\u56de\u53bb\u4e86\u3002<\/p>\n

\u6211\u8e29\u5230\u7684\u4e24\u4e2a\u5751<\/h3>\n

\u7b2c\u4e00\u4e2a\u8ddf\u6570\u636e\u6709\u5173\u3002\u540c\u4e00\u5957\u4ee3\u7801，\u6211\u628a\u5411\u91cf\u6362\u6210\u5747\u5300\u968f\u673a\u6570（\u6ca1\u6709\u7c07\u7ed3\u6784）\u518d\u8dd1\u4e00\u904d，IVF256 nprobe=8 \u7684\u53ec\u56de\u53ea\u6709 0.175，PQ \u662f 0.165\u3002128 \u7ef4\u7a7a\u95f4\u91cc\u5747\u5300\u968f\u673a\u7684\u70b9\u5f7c\u6b64\u8ddd\u79bb\u90fd\u5dee\u4e0d\u591a，\u5012\u6392\u6876\u5206\u4e0d\u51fa\u8c01\u8be5\u8fdb\u54ea\u4e2a\u6876，\u538b\u7f29\u7801\u4e5f\u5206\u4e0d\u51fa\u5dee\u8ddd\u3002\u6240\u4ee5\u5728\u81ea\u5df1\u7684\u8bed\u6599\u4e0a\u505a\u9009\u578b\u524d，\u5148\u786e\u8ba4\u6570\u636e\u662f\u4e0d\u662f\u771f\u7684\u6709\u7c07\u7ed3\u6784\u2014\u2014\u7528\u771f\u5b9e embedding \u8dd1，\u522b\u7167\u642c\u522b\u4eba\u7684\u53ec\u56de\u6570\u5b57\u3002<\/p>\n

\u7b2c\u4e8c\u4e2a\u662f\u6d41\u7a0b\u4e0a\u7684\u3002IVF \u548c PQ \u5fc5\u987b\u5148\u8bad\u7ec3\u518d\u5165\u5e93，\u987a\u5e8f\u53cd\u4e86\u4f1a\u76f4\u63a5\u62a5\u9519：<\/p>\n

RuntimeError: Error in virtual void faiss::IndexIVFFlat::add_core(…)
\nat \/project\/faiss\/IndexIVFFlat.cpp:66: Error: 'is_trained' failed<\/p>\n

\u53e6\u5916 faiss \u5bf9\u8bad\u7ec3\u6837\u672c\u91cf\u6709\u81ea\u5df1\u7684\u5224\u65ad，\u8bad\u7ec3\u96c6\u7ed9 2000 \u6761\u65f6\u4f1a\u6253\u5370 please provide at least 9984 training points，\u8fd9\u4e2a 9984 \u7ea6\u7b49\u4e8e 39 \u00d7 nlist\u3002\u6211\u8bd5\u4e86 2000 \/ 13000 \/ 26000 \/ 100000 \u56db\u79cd\u8bad\u7ec3\u89c4\u6a21，\u53ec\u56de\u5206\u522b\u662f 0.346 \/ 0.337 \/ 0.333 \/ 0.337，\u5728\u8fd9\u4e2a\u6570\u636e\u96c6\u4e0a\u6ca1\u6709\u533a\u522b，\u4f46\u8bad\u7ec3\u6837\u672c\u5c11\u4e8e\u5efa\u8bae\u503c\u65f6\u8be5\u7ed9\u7684\u8b66\u544a\u8fd8\u662f\u4f1a\u7ed9\u3002<\/p>\n

\u6211\u600e\u4e48\u7528\u5b83<\/h3>\n

\"\u9009\u578b\u8981\u8dd1\u7684\u56db\u4e2a\u52a8\u4f5c\"<\/p>\n

\u5341\u4e07\u6761\u8fd9\u4e2a\u91cf\u7ea7，\u6211\u7684\u9ed8\u8ba4\u9009\u62e9\u662f IVF256 \u52a0 Flat \u5012\u6392\u8868\u3001nprobe=16：\u53ec\u56de\u548c\u66b4\u529b\u68c0\u7d22\u4e00\u6837，\u67e5\u8be2\u5feb 2.3 \u500d，\u7d22\u5f15\u53ea\u5927 1.8%，\u8bad\u7ec3 0.7 \u79d2\u3002\u4e0a\u7ebf\u524d\u53ea\u5728\u771f\u5b9e\u8bed\u6599\u4e0a\u8dd1\u4e00\u904d\u53ec\u56de，\u5bf9\u5f97\u4e0a\u5c31\u6536\u5de5\u3002<\/p>\n

HNSW \u6211\u4f1a\u7559\u7ed9\u4e24\u79cd\u60c5\u51b5：\u67e5\u8be2\u5ef6\u8fdf\u6709\u786c\u6307\u6807（\u6bd4\u5982\u8981\u538b\u5230 0.05 ms \u4ee5\u5185），\u6216\u8005\u6570\u636e\u662f\u6d41\u5f0f\u589e\u91cf\u3001\u6ca1\u6cd5\u505c\u673a\u91cd\u8bad\u3002\u5b83\u7684\u4ee3\u4ef7\u662f\u5165\u5e93 2.93 \u79d2\u548c 74.8 MB \u7d22\u5f15，\u589e\u91cf\u63d2\u5165\u8fd8\u4f1a\u8ba9\u56fe\u7ed3\u6784\u6162\u6162\u53d8\u5dee，\u9700\u8981\u5b9a\u671f\u91cd\u5efa\u3002<\/p>\n

PQ \u6211\u6682\u65f6\u4e0d\u7528\u5728\u8fd9\u4e2a\u91cf\u7ea7\u3002\u5341\u4e07\u6761\u538b\u7f29\u5230 2.5 MB \u7701\u4e0b\u6765\u7684\u5185\u5b58，\u6362 0.337 \u7684\u53ec\u56de\u4e0d\u5212\u7b97\u3002PQ \u771f\u6b63\u7684\u7528\u6b66\u4e4b\u5730\u662f\u5343\u4e07\u7ea7\u4ee5\u4e0a\u3001\u5185\u5b58\u88c5\u4e0d\u4e0b\u539f\u59cb\u5411\u91cf\u7684\u573a\u666f，\u90a3\u65f6\u5019\u8fde Flat \u5012\u6392\u8868\u90fd\u653e\u4e0d\u4e0b，\u538b\u7f29\u662f\u552f\u4e00\u9009\u9879，\u4ee3\u4ef7\u5c31\u662f\u53ec\u56de\u3002\u771f\u8981\u4e0a，\u6211\u4f1a\u5148\u628a m \u8c03\u5230 32 \u6216 64，\u800c\u4e0d\u662f\u53bb\u52a8 nprobe\u3002<\/p>\n

\u4e09\u6761\u53ef\u4ee5\u9a6c\u4e0a\u505a\u7684：<\/p>\n

  • \u7528\u771f\u5b9e\u8bed\u6599\u62bd 10 \u4e07\u6761\u5411\u91cf，\u6309\u4e0a\u9762\u7684\u5199\u6cd5\u8dd1\u4e00\u904d Flat \u548c IVF256（nprobe \u53d6 8\u300116\u300132 \u4e09\u4e2a\u503c），\u770b\u53ec\u56de\u548c\u5ef6\u8fdf\u5bf9\u4e0d\u5bf9\u5f97\u4e0a\u9700\u6c42\u3002<\/li>\n
  • \u51b3\u5b9a\u662f\u5426\u4e0a HNSW \u4e4b\u524d，\u5148\u91cf\u4e00\u4e0b\u5165\u5e93\u8017\u65f6\u548c\u7d22\u5f15\u6587\u4ef6\u5927\u5c0f，\u628a\u8fd9\u4e24\u9879\u548c\u67e5\u8be2\u5ef6\u8fdf\u653e\u4e00\u8d77\u770b\u3002<\/li>\n
  • \u5982\u679c\u6700\u7ec8\u8981\u8d70 PQ，\u5148\u628a\u5b50\u91cf\u5316\u5668\u6570\u91cf\u626b\u4e00\u904d（8 \/ 16 \/ 32 \/ 64），\u522b\u628a\u8c03\u53c2\u65f6\u95f4\u82b1\u5728 nprobe \u4e0a\u3002<\/li>\n","protected":false},"excerpt":{"rendered":"

    \u624b\u91cc\u6709 10 \u4e07\u6761 128 \u7ef4\u5411\u91cf\u3001\u673a\u5668\u53ea\u6709 2 \u6838\u7684\u65f6\u5019，Faiss \u91cc\u6700\u5148\u8be5\u8bd5\u7684\u4e0d\u662f HNSW，\u800c\u662f\u5012\u6392\u8868\u4e0d\u52a0\u538b\u7f29\u7684 IVF：nprobe16 \u5c31\u80fd\u628a\u53ec\u56de\u505a\u5230\u548c\u66b4\u529b\u68c0\u7d22\u4e00\u6837（1.000），\u5355\u6761\u67e5\u8be2\u4ece 0.452 ms \u6389\u5230 0.195 ms\u3002HNSW \u66f4\u5feb，0.031 ms \u62ff\u5230 0.998 \u7684\u53ec\u56de，\u4ee3\u4ef7\u662f\u7d22\u5f15\u4f53\u79ef\u53d8\u6210\u539f\u59cb\u5411\u91cf\u7684 1.53 \u500d\u3001\u5165\u5e93 2.93 \u79d2<\/p>\n","protected":false},"author":2,"featured_media":113855,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[10839,10237,6238,132],"topic":[],"class_list":["post-113859","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-faiss","tag-10237","tag-6238","tag-132"],"yoast_head":"\nFaiss \u7d22\u5f15\u600e\u4e48\u9009\uff1a10 \u4e07\u6761 128 \u7ef4\u5411\u91cf\u4e0a IVF\u3001PQ\u3001HNSW \u7684\u53ec\u56de\u4e0e\u5ef6\u8fdf\u5b9e\u6d4b - 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