zilliztech / zilliztech/VectorDBBench

Duplicate vectors in LAION 100M dataset

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Description

The LAION 100M dataset used for benchmarking has a large number of duplicate vectors, which is impacting the recall results of several test queries and making it impossible to achieve 0.99 recall. Whenever a query has multiple results with same distance, the results are not in a order. algorithm does not have a way to order it as all the ids are with the same distance. accuracy calculation expects the ids to be in the same order.

Is this to be expected in this dataset ?

For example, in the first datafile the vector below appears 947 times.

Vector id 2783
[0.012306213,0.057373047,-0.019821167,-0.026184082,0.0066490173,0.04647827,0.042755127,-0.023773193,-0.0077285767,-0.047546387,-0.050048828,-0.023651123,-0.0038471222,-0.004505157
5,0.010421753,0.007423401,0.0045814514,0.031707764,0.013145447,0.011917114,-0.0022068024,0.01878357,-0.02078247,0.04095459,-0.049743652,-0.0317688,0.03488159,-0.061065674,-0.004287
7197,-0.018661499,0.016220093,0.008796692,-0.014205933,-0.012191772,0.030303955,0.027328491,-0.0068511963,-0.027511597,0.0037670135,-0.045440674,0.020370483,0.033050537,-0.03341674
8,0.0018873215,-0.0009403229,-0.017028809,-0.006641388,0.00044631958,-0.01838684,0.0158844,-0.008522034,-0.026016235,0.029800415,0.0013132095,-0.005104065,0.009666443,0.021850586,0
.003774643,0.02368164,0.0077285767,-0.026123047,0.049987793,-0.052703857,0.003917694,0.0013389587,0.034698486,0.007293701,-0.02368164,-0.015586853,0.0009965897,0.016204834,-0.00793
457,-0.016479492,-0.007396698,0.021011353,0.00579834,-0.014205933,-0.0049552917,0.0132751465,-0.006816864,0.0014657974,-0.005645752,-0.002840042,-0.01576233,0.028747559,-0.01071167
,-0.020584106,0.016525269,0.037322998,0.010879517,0.051452637,-0.0039634705,0.027038574,0.035980225,-0.019592285,0.0049591064,0.038482666,-0.014770508,0.013191223,-0.0012178421,0.0
16052246,0.012680054,-0.0064888,-0.03427124,0.011932373,-0.009994507,0.021087646,0.009132385,-0.010070801,0.030593872,0.040618896,-0.0041618347,0.02003479,-0.044952393,0.012886047,
0.015731812,-0.0519104,0.023239136,-0.034820557,-0.01838684,-0.00044584274,-0.018249512,-0.016998291,0.005016327,0.001036644,-0.04425049,-0.03793335,0.013191223,-0.011169434,-0.022
842407,0.0011997223,-0.018005371,-0.008682251,-0.01940918,-0.018051147,-0.022109985,-0.014701843,-0.01084137,0.019638062,-0.018096924,-0.01902771,0.004096985,-0.006832123,0.0361938
48,0.0073242188,-0.01953125,-0.026473999,0.0077323914,-0.0057525635,-0.038024902,-0.036010742,0.0005121231,0.023391724,0.04425049,-0.017196655,-0.02758789,-0.018249512,-0.02130127,
-0.009155273,8.940697e-07,0.0015888214,-0.008743286,0.025421143,0.011817932,0.03555298,-0.02029419,-0.03579712,0.016708374,0.017837524,0.003698349,0.01576233,0.014282227,-0.0218353
27,0.0020523071,0.0006170273,0.0018396378,8.6426735e-06,-0.027038574,-0.0050239563,-8.606911e-05,0.009429932,0.0017881393,-0.031311035,0.005607605,0.0014467239,-0.010643005,-0.0098
95325,0.002248764,-0.0029525757,0.0077323914,-0.005836487,0.0071258545,0.002538681,0.03186035,0.01121521,0.08294678,0.011924744,0.0003569126,0.007949829,-0.011756897,0.025878906,0.
035705566,0.007785797,0.051971436,-0.017990112,0.0036888123,0.00011360645,-0.032470703,0.0015163422,-0.0060768127,-0.011482239,-0.04638672,0.01134491,0.030914307,0.014732361,0.0097
42737,-0.015403748,0.050964355,-0.004535675,0.03479004,-0.019943237,0.011856079,-0.021728516,-0.00674057,-0.011444092,0.009803772,-0.01889038,0.007827759,0.019836426,-0.03253174,0.
008934021,-0.0087890625,-0.0109939575,0.006587982,0.017196655,0.003332138,-0.035003662,0.0077209473,-0.0037212372,0.012779236,-0.02104187,-0.019134521,-0.033447266,-0.0062294006,-0
.0037117004,0.04168701,0.006126404,0.017593384,0.009254456,-0.04284668,0.035461426,0.006046295,-0.012191772,-0.0362854,0.0068855286,-0.012832642,0.02279663,0.0035209656,0.000308752
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0929565,0.09100342,-0.015640259,-0.010482788,-0.026565552,0.008346558,-0.047424316,-0.019836426,-0.004760742,-0.0061950684,0.0018606186,0.020523071,-0.016586304,-0.020874023,-0.012
939453,-0.023910522,-0.005607605,-0.035949707,-0.030670166,-0.017578125,0.013870239,0.005302429,-0.008956909,0.057556152,-0.0034542084,-0.006969452,-0.018005371,-0.0047721863,4.202
1275e-05,-0.07434082,-0.030670166,-0.011924744,-0.002483368,0.0234375,-0.02557373,0.03250122,-0.0047721863,0.0071411133,0.010894775,-0.029754639,-0.01512146,0.03930664,-0.027954102
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07259369,0.014450073,-0.03857422,-0.032318115,0.0011663437,-0.03152466,0.0073394775,0.02116394,0.018692017,-0.0362854,0.015335083,0.03375244,0.005809784,-0.0066070557,0.025650024,0
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77,-0.003566742,-0.005241394,-0.011703491,-0.005897522,-0.013023376,0.021072388,-0.04067993,0.008407593,0.039367676,0.013198853,0.00045251846,-0.028961182,0.0060653687,-0.0178833,0
.011566162,0.0045318604,0.025650024,-0.034698486,0.064208984,-0.01499176,-0.008773804,-0.0022735596,-0.049865723,0.00096178055,-0.005344391,-0.019729614,-0.019332886,0.025360107,0.
011024475,-0.021820068,-0.1763916,0.011001587,0.012046814,-0.012481689,-0.024795532,-0.007411957,-0.014190674,0.016235352,-0.026901245,-0.4633789,0.0075149536,0.010391235,0.0056991
577,0.009162903,-0.010063171,-0.0126953125,-0.007575989,0.012054443,-0.009864807,-0.0070343018,-0.016464233,0.02268982,0.022277832,-0.030700684,0.006214142,0.021118164,0.0048942566
,0.003452301,-0.0052833557,-0.01977539,-0.03817749,0.07336426,0.014083862,-0.024276733,-0.032043457,-0.0066070557,0.07055664,-0.013427734,0.041870117,0.015686035,0.0018825531,0.001
666069,0.052581787,0.0014324188,0.00856781,0.0058898926,-0.0014448166,-0.027557373,-0.00166893,0.019592285,0.010444641,-0.015426636,0.00036096573,-0.0020751953,-0.05368042,-0.02940
3687,0.020339966,-0.0020713806,-0.046661377,-0.018157959,-0.06341553,0.010925293,0.01663208,0.040893555,0.011711121,-0.03463745,0.0059127808,0.014533997,0.01625061,0.019714355,-0.0
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4,0.004497528,-0.005596161,0.00047302246,-0.000726223,0.00881958,-0.013473511,0.0030403137,-0.040252686,0.018203735,-0.02281189,-0.018600464,-0.02406311,-0.013916016,0.007648468,0.
00037908554,0.018844604,0.009429932,0.038604736,0.023788452,0.038360596,0.03213501,0.011116028,-0.015609741,-0.016174316,-0.001159668,-0.030380249,0.040618896,0.048980713,0.0034942
627,0.013458252,0.050079346,0.011390686,-0.021072388,0.022720337,0.006252289,-0.023376465,0.021835327,-0.0041275024,0.007411957,0.03994751,0.031402588,0.014862061,0.016433716,-0.00
4009247,0.0053749084,0.014587402,0.024612427,-0.0015525818,-0.008758545,-0.004470825,0.0004892349,0.0129776,-0.008026123,0.018463135,0.008125305,0.0065460205,0.025344849,0.02943420
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019088745,0.022659302,0.0011548996,0.0211792,0.007774353,-0.014884949]

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No source file, test, or entry point is identified. Start by reproducing the recall queries against the first LAION 100M datafile and verify the reported duplicate vector and tied-distance results; done requires determining whether the dataset or benchmark's tie handling is responsible for the failed recall target.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data, testing-qa
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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