向量索引

节点向量索引在 Neo4j 5.11 中发布了公共 Beta 版，在 Neo4j 5.13 中达到了通用可用性。

向量索引通过将节点或属性表示为多维空间中的向量，从而实现相似性搜索和复杂的分析查询。

以下资源提供了在 Neo4j 中使用 LLM 和向量索引的实践教程

Neo4j 向量索引由 Apache Lucene 索引和搜索库提供支持。[1]

示例图

本页面上的示例使用了 Neo4j 电影推荐数据集，重点关注 Movie 节点的 plot 和 embedding 属性。embedding 属性由 plot 和 title 属性组合而成的 1536 维向量嵌入组成。

vector index graph

该图包含 28863 个节点和 332522 个关系。

要重新创建该图，请下载并导入此 dump 文件到一个空的 Neo4j 数据库（运行 5.13 或更高版本）。dump 文件可以导入到 Aura 和 本地部署实例。

用于加载数据集的 dump 文件包含由 OpenAI 使用模型 text-embedding-ada-002 生成的嵌入。

Neo4j 中的向量和嵌入

向量索引允许您从大型数据集中查询向量嵌入。嵌入是数据对象（如文本、图像或文档）的数值表示。文本中的每个单词或标记通常表示为高维向量，其中每个维度表示该单词含义的某个特定方面。

特定数据对象的嵌入可以通过专有（如 Vertex AI 或 OpenAI）和开源（如 sentence-transformers）嵌入生成器创建，它们可以生成维度为 256、768、1536 和 3072 的向量嵌入。在 Neo4j 中，向量嵌入存储为节点或关系上的 LIST<INTEGER | FLOAT> 属性。

有关嵌入如何生成和存储为属性的信息，请参阅

例如，电影《教父》的 plot 为："一个有组织犯罪王朝的年迈族长将他秘密帝国的控制权移交给不情愿的儿子。" 这是其 1536 维的 embedding 属性，其中 LIST 中的每个元素代表情节含义的一个特定方面。

[0.005967312026768923, -0.03817005082964897, 0.0014667075593024492, -0.03868866711854935, -0.006505374796688557, 0.020900176838040352, -0.0027551413513720036, -0.0024731445591896772, -0.03734026849269867, -0.02228747308254242, 0.028783122077584267, 0.017905177548527718, 0.011396560817956924, 0.014235977083444595, 0.023143187165260315, -0.014184115454554558, 0.029846282675862312, -0.011928141117095947, 0.018838683143258095, -0.0019172541797161102, 0.0033483069855719805, 0.009497134014964104, -0.03516208380460739, 0.0021441481076180935, 0.002657901030033827, 0.0030760341323912144, 0.004255882930010557, -0.020809419453144073, 0.02358401007950306, -0.013808120042085648, 0.01064456906169653, -0.006975369527935982, 0.007318951655179262, -0.013872946612536907, 0.005905726458877325, -0.010689947754144669, 0.0020225979387760162, -0.016245609149336815, -0.00038815077277831733, -0.007163367234170437, 0.027668101713061333, 0.007215228863060474, -0.009380445815622807, -0.02956104464828968, -0.000863007502630353, 0.012142069637775421, 0.0012957267463207245, -0.027953339740633965, -0.016414159908890724, 0.008453421294689178, -0.0010777463903650641, 0.03311355784535408, -0.013639570213854313, -0.052457891404628754, 0.0010242642601951957, 0.0034390646032989025, -0.01049546804279089, 0.006456754636019468, 0.003970644902437925, -0.011629937216639519, 0.005280147306621075, -0.023402493447065353, -0.014689764939248562, -0.007623638026416302, -0.002453696448355913, 0.02290981076657772, 0.0017989451298490167, 0.0013427261728793383, -0.001776255783624947, -0.002414800226688385, 0.04833490028977394, 0.031142819672822952, -0.0033013075590133667, 0.017879245802760124, 0.0070077828131616116, -0.016154851764440536, -0.005772831384092569, 0.019875913858413696, -0.018008900806307793, 0.012764407321810722, 0.0055232481099665165, -0.027901478111743927, -0.0034909259993582964, 0.0307279285043478, 0.006472961511462927, 0.008861830458045006, -0.01802186481654644, 0.018281172960996628, -0.014223011210560799, -0.00018313586770091206, 0.0026352116838097572, 0.0006754148053005338, 0.014975002966821194, 0.024361930787563324, -0.017166150733828545, 0.0028880364261567593, 0.011824417859315872, 0.01710132323205471, -0.0005003822734579444, -0.018890544772148132, -0.002192768268287182, -0.0018264965619891882, 0.011033530347049236, -0.009095207788050175, -0.022689398378133774, -0.004281813744455576, 0.007092057727277279, -0.015247276052832603, 0.024115590378642082, 0.002996621420606971, -0.02834230102598667, 0.030546413734555244, 0.02350621670484543, -0.020511215552687645, 0.010190781205892563, -0.016582708805799484, 0.028238577768206596, -0.011967036873102188, 0.011623455211520195, -0.02797926962375641, 0.0026254875119775534, 0.018307102844119072, 0.0038701631128787994, -0.03850715234875679, 0.006246067117899656, -0.0006312514888122678, 0.010352848097682, -0.02358401007950306, -0.026708664372563362, -0.002863726345822215, 0.035862214863300323, 0.009860164485871792, -0.01726987399160862, 0.004275330808013678, -0.02663087099790573, 0.009140586480498314, -0.013872946612536907, 0.019136887043714523, -0.020835351198911667, -0.0250879917293787, 0.03044269047677517, 0.026280807331204414, -0.013406192883849144, 0.006683648563921452, -0.01216800045222044, 0.007824601605534554, 0.031505849212408066, 0.023726629093289375, 0.0294832531362772, -0.013678465969860554, 0.033891480416059494, 0.009211895987391472, 0.017088359221816063, -0.02183368429541588, 0.01847565360367298, 0.004644844215363264, -0.009834233671426773, -0.011344699189066887, -0.0006725785788148642, 0.00012691882147919387, 0.015338033437728882, 0.025736261159181595, -0.003967403434216976, -0.007312469184398651, -0.01312743779271841, 0.02350621670484543, -0.0006843284936621785, -0.011785522103309631, 0.006570201832801104, -0.004187814891338348, -0.0070013003423810005, 0.0165178831666708, -0.004537879955023527, 0.022715330123901367, -0.0025120405480265617, 0.025580676272511482, 0.005053253378719091, -0.0020063910633325577, -0.039285074919462204, -0.001816772622987628, 0.0007224142318591475, 0.0161029901355505, 0.04086684808135033, 0.03536953032016754, 0.009626788087189198, -0.023571044206619263, -0.009607339277863503, 0.011085391975939274, 0.020835351198911667, -0.0009027139167301357, -0.007584741804748774, 0.016958704218268394, 0.011130770668387413, -0.016829051077365875, -0.6712950468063354, -0.006511857267469168, -0.024854615330696106, -0.02663087099790573, -0.00008933950448408723, 0.0061779990792274475, 0.004605947993695736, 0.013231161050498486, -0.020187081769108772, 0.00798666849732399, -0.001847565290518105, 0.04086684808135033, 0.007519915234297514, 0.0040808506309986115, -0.034021131694316864, -0.01997963711619377, -0.004972219467163086, -0.023220978677272797, 0.012129104696214199, 0.0018329792656004429, -0.011649386025965214, 0.028446022421121597, -0.0010356089333072305, -0.006223377771675587, 0.021211346611380577, 0.004006299655884504, 0.021937407553195953, -0.02927580662071705, -0.01129283756017685, -0.009296170435845852, -0.01864420250058174, 0.02717541716992855, -0.0003555347793735564, 0.0021700789220631123, 0.048360832035541534, -0.002277043182402849, -0.009049829095602036, 0.033969271928071976, 0.004557327833026648, 0.018916476517915726, -0.000779542897362262, -0.00638544512912631, 0.022183749824762344, -0.012757924385368824, -0.027149485424160957, -0.012278205715119839, 0.0238303504884243, -0.02963883802294731, 0.005218561738729477, -0.004434156697243452, 0.013665501028299332, -0.0024520757142454386, 0.002124700229614973, -0.007273572962731123, -0.0035654769744724035, -0.0028621056117117405, 0.020640870556235313, 0.01091684214770794, -0.0006867594784125686, -0.011694764718413353, 0.011215046048164368, 0.016504917293787003, 0.00827838946133852, -0.0044471221044659615, 0.010676982812583447, 0.027771824970841408, -0.0133802630007267, 0.029820352792739868, 0.008349698968231678, -0.014573076739907265, -0.009017415344715118, 0.011655868031084538, -0.0061066895723342896, -0.013082059100270271, 0.004353123251348734, 0.00672254478558898, 0.01773662678897381, 0.012433790601789951, 0.023843316361308098, 0.015221345238387585, -0.0046221548691391945, -0.00026214358513243496, -0.016582708805799484, 0.016504917293787003, 0.028005201369524002, 0.005516765173524618, -0.04309689253568649, 0.013743292540311813, -0.0064308238215744495, -0.007176332641392946, 0.01911095716059208, 0.00446332897990942, -0.012971853837370872, -0.016919808462262154, 0.010048162192106247, 0.0032769974786788225, -0.021548446267843246, 0.001816772622987628, 0.01856641098856926, -0.04804966226220131, 0.007286538369953632, -0.007299503777176142, -0.014080392196774483, 0.008952588774263859, 0.023908143863081932, 0.012932957150042057, -0.008433973416686058, 0.012783855199813843, 0.0430709607899189, -0.01015836838632822, 0.03534360229969025, -0.007584741804748774, -0.016453055664896965, -0.005720969755202532, -0.014871280640363693, -0.026540113613009453, 0.005228285677731037, 0.0004019264888484031, 0.005931657273322344, -0.02533433400094509, -0.018825719133019447, 0.0023353875149041414, 0.0014059323584660888, -0.02020004764199257, 0.022481953725218773, 0.034980569034814835, -0.02709762565791607, -0.022974636405706406, -0.025023166090250015, 0.00641785841435194, -0.00019822835747618228, -0.004845807328820229, 0.0003723492263816297, -0.010132437571883202, 0.01498796883970499, 0.001948046963661909, -0.0020161152351647615, -0.008842382580041885, 0.0223652645945549, -0.013574742712080479, -0.002369421534240246, 0.003275376744568348, 0.005879795644432306, 0.005789037793874741, 0.006359514314681292, -0.03549918532371521, 0.003118171589449048, -0.026993902400135994, -0.01614188589155674, 0.011578075587749481, 0.0008524731383658946, -0.013367297127842903, 0.004194297362118959, 0.019331367686390877, 0.006152068264782429, -0.015208380296826363, -0.0018005658639594913, -0.015714028850197792, -0.01681608520448208, -0.028990568593144417, 0.010676982812583447, 0.024595309048891068, -0.045560311526060104, -0.0009262136882171035, 0.014845349825918674, -0.020887212827801704, 0.015739960595965385, 0.011727177537977695, 0.0012560202740132809, -0.023052429780364037, 0.0014245701022446156, -0.013062611222267151, -0.011299320496618748, 0.022274507209658623, 0.011338216252624989, -0.007908876053988934, 0.010339883156120777, -0.006132620386779308, 0.01247916929423809, -0.007947771809995174, -0.0025347298942506313, -0.011416008695960045, 0.011027047410607338, 0.004521673079580069, 0.04880165681242943, 0.0012543996563181281, 0.02115948498249054, 0.0165178831666708, -0.025373229756951332, 0.026125222444534302, -0.0031262750271707773, 0.007669016718864441, 0.003821542952209711, -0.021561412140727043, 0.008187631145119667, 0.02358401007950306, 0.02249491773545742, 0.015247276052832603, -0.004560569301247597, 0.030753860250115395, 0.031090958043932915, -0.021457688882946968, 0.027694031596183777, -0.004823117982596159, 0.0049171168357133865, -0.018346000462770462, -0.0030355174094438553, -0.011176149360835552, 0.024102624505758286, 0.006923507899045944, 0.010009266436100006, -0.00510187353938818, 0.0007916979375295341, -0.004722636193037033, 0.019914809614419937, 0.026190048083662987, -0.013289504684507847, 0.006346548907458782, -0.015415825881063938, -0.026734594255685806, 0.003623821074143052, 0.005325525999069214, -0.003922024741768837, -0.00640813447535038, -0.014624938368797302, -0.0065021333284676075, 0.007435640320181847, -0.002808623481541872, 0.010138919577002525, -0.033813685178756714, -0.0032008260022848845, 0.01614188589155674, -0.018994268029928207, 0.008135770447552204, -0.008596041239798069, -0.015662167221307755, 0.004310985561460257, -0.014663834124803543, 0.014962038025259972, -0.03479905426502228, 0.013114472851157188, 0.01341915875673294, 0.05092797800898552, -0.011908693239092827, 0.005332008935511112, -0.013367297127842903, 0.02501020021736622, -0.00029678543796762824, -0.02454344742000103, 0.003152205841615796, -0.015454721637070179, 0.010028714314103127, -0.02102983184158802, -0.0032624113373458385, 0.03583628311753273, -0.015026864595711231, 0.00672254478558898, 0.000010907877367571928, 0.019875913858413696, 0.020161151885986328, 0.014054462313652039, -0.005675591062754393, -0.009224860928952694, 0.014793488197028637, 0.03687351569533348, -0.005442214198410511, 0.005633453372865915, -0.0030436208471655846, -0.012615305371582508, -0.009075759910047054, 0.017192082479596138, -0.002220319816842675, 0.005798762198537588, -0.0007568534929305315, 0.010378778912127018, 0.005908967927098274, -0.0158825796097517, 0.0088812792673707, 0.007766257040202618, -0.0030209312681108713, -0.013561777770519257, -0.035395462065935135, 0.022391194477677345, -0.0027049004565924406, 0.004748567007482052, -0.020433424040675163, -0.00028706141165457666, -0.005092149134725332, -0.018371930345892906, 0.006009449250996113, -0.00645027169957757, 0.015286171808838844, -0.012343033216893673, -0.008628454059362411, -0.010605673305690289, 0.009192448109388351, 0.007500466890633106, -0.013535846956074238, 0.003831267124041915, -0.02956104464828968, 0.0009724028059281409, 0.0034585127141326666, -0.00004074468961334787, -0.025139853358268738, 0.012278205715119839, 0.023519182577729225, -0.012913509272038937, -0.006301170215010643, 0.0037178201600909233, 0.004716153722256422, -0.017905177548527718, 0.009769407100975513, -0.019746258854866028, -0.011675315909087658, 0.007409709505736828, -0.022676432505249977, -0.013406192883849144, 0.003922024741768837, 0.03925914317369461, -0.011325251311063766, -0.014611972495913506, -0.022404160350561142, -0.03311355784535408, 0.0024634203873574734, 0.1057974249124527, 0.014145219698548317, 0.025956671684980392, 0.006878129206597805, -0.019914809614419937, -0.019162818789482117, -0.009231343865394592, -0.04423784464597702, 0.012018898501992226, -0.00921837892383337, 0.02408965863287449, -0.026501217857003212, 0.020225977525115013, 0.005014357157051563, 0.02053714729845524, 0.014521215111017227, -0.002670866437256336, -0.020433424040675163, -0.0015372068155556917, -0.031168751418590546, 0.0051213214173913, 0.006865163799375296, 0.010048162192106247, 0.003795612370595336, -0.009749959222972393, -0.024063728749752045, 0.026449356228113174, 0.00967864878475666, -0.009049829095602036, -0.012284688651561737, -0.02475089207291603, 0.0034844432957470417, -0.00928320549428463, 0.011772556230425835, -0.01811262220144272, -0.01918874867260456, 0.009043346159160137, 0.023843316361308098, 0.02580108679831028, 0.005980277433991432, 0.029327668249607086, -0.008103356696665287, 0.008083908818662167, -0.005490834359079599, 0.021146519109606743, -0.0023499734234064817, -0.03298390284180641, 0.005283388774842024, -0.00043352958164177835, -0.024271173402667046, 0.03181701898574829, -0.000028944177756784484, -0.004479535389691591, -0.002066355897113681, 0.017995934933423996, -0.012783855199813843, 0.013859981670975685, -0.006615580525249243, -0.0008403180981986225, 0.025489918887615204, -0.01789221167564392, -0.03189481049776077, 0.00028949242550879717, -0.03251715004444122, 0.03588814660906792, -0.03500650078058243, -0.007869980297982693, -0.024361930787563324, 0.00451519014313817, -0.018177449703216553, 0.020627904683351517, 0.003249445930123329, 0.010962220840156078, -0.005299595184624195, 0.048023734241724014, -0.0033094107639044523, 0.012971853837370872, -0.02290981076657772, 0.017918141558766365, -0.016245609149336815, -0.013179299421608448, -0.020589008927345276, 0.0037469922099262476, -0.029327668249607086, -0.007383778691291809, 0.013017232529819012, 0.006327101029455662, -0.02689017914235592, -0.004385536536574364, 0.005789037793874741, -0.005597798619419336, -0.004152160137891769, 0.012719028629362583, -0.008220044896006584, -0.01702353172004223, -0.011506766080856323, 0.0042980206198990345, 0.0018702547531574965, -0.0032964455895125866, 0.007267090491950512, -0.009581409394741058, -0.0058182100765407085, -0.005429248791188002, -0.008829417638480663, -0.0030403793789446354, -0.01194110605865717, -0.002591453492641449, 0.005756624508649111, -0.01618078351020813, -0.009821268729865551, -0.00021210535487625748, -0.01768476516008377, -0.0005562954465858638, -0.017451388761401176, -0.015545479021966457, 0.02332470193505287, 0.015960371121764183, 0.02208002656698227, 0.01369143184274435, -0.014495284296572208, -0.007701430004090071, -0.0005567006301134825, 0.027590308338403702, 0.05188741534948349, -0.023609939962625504, -0.017957039177417755, 0.015999266877770424, -0.020900176838040352, 0.003038758644834161, 0.021042795851826668, -0.009814785793423653, 0.0014083633432164788, 0.010897394269704819, -0.0167253278195858, -0.020135220140218735, -0.005273664370179176, -0.009788854978978634, -0.002986897248774767, -0.008764590136706829, -0.006729027256369591, -0.018449721857905388, -0.009166517294943333, -0.002651418326422572, 0.008245975710451603, 0.0034358231350779533, -0.028757192194461823, 0.01511762198060751, -0.008544179610908031, 0.005344973877072334, 0.013924808241426945, -0.003299686824902892, -0.04143732413649559, -0.0008403180981986225, 0.010949255898594856, -0.013600673526525497, -0.03448788449168205, -0.007863497361540794, -0.01809965819120407, -0.00444063963368535, 0.004920358303934336, 0.0330357663333416, -0.008816451765596867, 0.006683648563921452, 0.00823301076889038, -0.015947405248880386, 0.02608632668852806, 0.0037243026308715343, -0.007623638026416302, -0.028031131252646446, 0.027123555541038513, 0.01843675784766674, 0.016712361946702003, 0.040374163538217545, -0.0021538722794502974, 0.01885164901614189, -0.011740143410861492, 0.017490284517407417, -0.0004517621418926865, -0.00034439266892150044, -0.026190048083662987, -0.021729961037635803, 0.0020209772046655416, -0.014521215111017227, -0.01467679999768734, 0.002505557844415307, -0.01061863824725151, 0.015623271465301514, -0.010087057948112488, -0.0031748951878398657, 0.01631043665111065, 0.016375262290239334, -0.013257091864943504, 0.010741809383034706, -0.012932957150042057, -0.002484489232301712, 0.0027324517723172903, 0.00897203665226698, -0.004793945699930191, 0.0043466403149068356, -0.0020047705620527267, 0.0021538722794502974, 0.021263208240270615, -0.0269679706543684, -0.024115590378642082, -0.0025833500549197197, 0.030598275363445282, 0.002772968728095293, 0.01584368385374546, 0.006981851998716593, -0.0037113374564796686, -0.01273199450224638, -0.026280807331204414, -0.02182071842253208, -0.049527715891599655, 0.02195037342607975, -0.008628454059362411, -0.004353123251348734, 0.01064456906169653, -0.009698097594082355, -0.04094463959336281, 0.0238303504884243, 0.0034649954177439213, 0.032802388072013855, 0.0002048123424174264, 0.022507883608341217, 0.03770329803228378, -0.010346366092562675, 0.0028588641434907913, 0.026410460472106934, 0.019085025414824486, 0.008848865516483784, 0.015830717980861664, -0.004469811450690031, 0.013808120042085648, -0.012031864374876022, -0.02099093608558178, -0.006054827943444252, -0.045638103038072586, -0.024050762876868248, 0.014417491853237152, 0.01218744833022356, 0.0032413427252322435, -0.013302470557391644, -0.0003156257444061339, 0.006942956242710352, 0.00542600778862834, -0.0034358231350779533, 0.022067060694098473, -0.013847015798091888, -0.026942040771245956, -0.0334506556391716, -0.01835896447300911, -0.0021036313846707344, -0.001962633104994893, 0.012615305371582508, -0.0186053067445755, 0.01572699472308159, -0.02542509138584137, 0.019422125071287155, -0.013950739055871964, -0.002110114088281989, 0.02052418142557144, -0.0014197081327438354, 0.0010485743405297399, -0.004372571129351854, 0.0069299908354878426, -0.005105114541947842, -0.003756716148927808, -0.015960371121764183, 0.025554746389389038, 0.003516856813803315, 0.005951105151325464, 0.009736993350088596, 0.043459922075271606, -0.008952588774263859, 0.021315069869160652, -0.011318768374621868, -0.016375262290239334, -0.004560569301247597, -0.026656802743673325, 0.004842565860599279, 0.0004894427256658673, -0.023635871708393097, 0.007448605261743069, -0.008965553715825081, 0.0026092808693647385, -0.01999260112643242, -0.007811635732650757, 0.012142069637775421, -0.01375625841319561, -0.02102983184158802, -0.006806819699704647, 0.015869613736867905, -0.0074032265692949295, -0.001892944099381566, -0.0037016132846474648, -0.005322284530848265, 0.03293204307556152, -0.014430457726120949, 0.0418262854218483, -0.012641236186027527, 0.018216345459222794, -0.028290439397096634, 0.02576219104230404, 0.008433973416686058, 0.013963703997433186, 0.030598275363445282, -0.01225227490067482, 0.012051312252879143, 0.0014553628861904144, -0.008822934702038765, 0.01100111659616232, 0.009860164485871792, -0.004388778004795313, -0.01685498282313347, 0.01091035921126604, -0.00033223762875422835, -0.007850532419979572, -0.0006320617976598442, 0.002114976057782769, -0.007532880175858736, 0.01710132323205471, 0.015610306523740292, -0.009036863222718239, 0.008200597018003464, 0.012174483388662338, 0.00447305291891098, 0.0186053067445755, -0.019253576174378395, 0.010638087056577206, -0.02086128108203411, 0.022404160350561142, 0.010437123477458954, 0.0006920266896486282, -0.02128913812339306, -0.009296170435845852, -0.004106780979782343, 0.044808320701122284, -0.013782189227640629, -0.003750233445316553, -0.01181145291775465, 0.02764216996729374, 0.011960554867982864, -0.005043528974056244, 0.006155309733003378, -0.015584375709295273, 0.012433790601789951, -0.021600307896733284, -0.04314875230193138, -0.01214855257421732, -0.024776823818683624, 0.039077628403902054, 0.016271540895104408, 0.000348039175150916, -0.01511762198060751, 0.0014926382573321462, -0.04068533331155777, -0.0020290804095566273, -0.006904060021042824, 0.02099093608558178, 0.017049461603164673, -0.006981851998716593, 0.007364330347627401, 0.007416191976517439, 0.00766253424808383, 0.02153548039495945, -0.002995000686496496, 0.02157437615096569, -0.011312286369502544, -0.009685131721198559, 0.00414891866967082, -0.009672166779637337, -0.01308854203671217, -0.003380720503628254, -0.003168412484228611, 0.013769223354756832, -0.012615305371582508, 0.007973702624440193, 0.001315985107794404, -0.006139102857559919, -0.028212646022439003, 0.0004906582762487233, 0.0006340876570902765, 0.013289504684507847, -0.010359331034123898, -0.02956104464828968, 0.0263456329703331, 0.02621597982943058, 0.005357939284294844, -0.022754225879907608, -0.009393410757184029, 0.007053161505609751, -0.018086692318320274, -0.0012552099069580436, 0.003977127373218536, -0.010839049704372883, -0.01584368385374546, 0.007753291632980108, 0.005951105151325464, 0.02478978969156742, -0.00858955830335617, 0.007280055433511734, 0.013257091864943504, -0.0000065713156800484285, 0.007234676741063595, -0.00413919473066926, -0.01467679999768734, -0.018333034589886665, -0.017658835276961327, -0.01681608520448208, 0.005108356010168791, -0.007630120497196913, 0.008479352109134197, -0.02771996334195137, 0.004567051772028208, -0.018579376861453056, -0.003983610309660435, -0.0023110774345695972, 0.023065393790602684, 0.04281165450811386, -0.015273206867277622, -0.006696613971143961, 0.002272181212902069, -0.008356180973351002, -0.014508250169456005, -0.0066090975888073444, 0.00827838946133852, -0.016906842589378357, 0.003750233445316553, -0.008524730801582336, -0.0022802846506237984, -0.005156976170837879, -0.009633270092308521, -0.035940006375312805, -0.004323950968682766, 0.027771824970841408, 0.19261354207992554, -0.014547145925462246, -0.006657717749476433, 0.013808120042085648, -0.021340999752283096, 0.011869796551764011, 0.024115590378642082, 0.014080392196774483, 0.0023856281768530607, 0.0005133476224727929, -0.016206713393330574, 0.01723097823560238, 0.008012599311769009, 0.0019723570439964533, 0.006560477428138256, -0.040996503084897995, -0.010657534934580326, 0.00037032339605502784, -0.027875546365976334, -0.011727177537977695, -0.00768198212608695, -0.007299503777176142, -0.011202080175280571, -0.01939619518816471, 0.039622172713279724, -0.011668833903968334, -0.015830717980861664, 0.016919808462262154, 0.03207632899284363, 0.015960371121764183, -0.01093629002571106, -0.016842016950249672, -0.008336733095347881, -0.013244125992059708, -0.011999450623989105, -0.020122256129980087, -0.007422674912959337, -0.02501020021736622, -0.008505282923579216, -0.005526489112526178, -0.0011830900330096483, 0.01773662678897381, 0.010709396563470364, -0.007267090491950512, 0.015999266877770424, 0.02604742906987667, -0.013315435498952866, 0.01621967926621437, -0.02082238532602787, -0.01689387857913971, -0.0439007468521595, -0.03358031064271927, 0.000994281843304634, 0.03726247698068619, -0.02208002656698227, 0.000011990435268671717, 0.006949438713490963, 0.020433424040675163, 0.00515373470261693, -0.031298406422138214, 0.0031116888858377934, 0.015701064839959145, -0.02813485451042652, -0.007377295754849911, 0.007461570668965578, 0.03985555097460747, -0.010975186713039875, -0.025697365403175354, 0.0397258959710598, -0.026319703087210655, -0.0030403793789446354, -0.010067610070109367, -0.002486109733581543, -0.0088812792673707, 0.0017438423819839954, -0.001923736883327365, 0.017827384173870087, 0.006220136769115925, 0.010255607776343822, 0.001199296792037785, -0.01772366091609001, 0.035136155784130096, -0.0061066895723342896, -0.010735327377915382, -0.010651051998138428, -0.026151152327656746, 0.006981851998716593, 0.006622062996029854, -0.010048162192106247, -0.0009124379721470177, -0.00419105589389801, -0.019668467342853546, 0.00012296844215597957, 0.004894427489489317, 0.006852198392152786, 0.010437123477458954, 0.005908967927098274, 0.0038247844204306602, -0.008103356696665287, -0.006456754636019468, -0.028653468936681747, 0.018216345459222794, 0.032205980271101, 0.00022101905778981745, -0.029664767906069756, -0.008155218325555325, 0.03871459513902664, 0.03394334018230438, 0.005860347766429186, -0.013600673526525497, -0.016958704218268394, 0.006372479721903801, 0.0012543996563181281, -0.01911095716059208, -0.010437123477458954, 0.008356180973351002, -0.012855164706707, -0.008472870104014874, 0.019370263442397118, -0.029457321390509605, 0.0034487885423004627, -0.015415825881063938, -0.00047364120837301016, 0.008887761272490025, -0.0020015290938317776, 0.010501950047910213, -0.007500466890633106, -0.0017470837337896228, 0.01717911660671234, -0.024063728749752045, 0.026734594255685806, -0.024556411430239677, 0.0013573121977970004, -0.00010007645323639736, -0.00450546620413661, 0.007513432297855616, 0.027201347053050995, 0.003426099196076393, -0.022183749824762344, 0.002813485451042652, 0.008064460940659046, 0.002243009163066745, 0.009899060241878033, 0.010988151654601097, -0.004790704697370529, -0.004638361278921366, 0.006025656126439571, -0.010605673305690289, -0.01625857502222061, -0.020342666655778885, -0.016090024262666702, -0.026410460472106934, 0.0121226217597723, -0.009406376630067825, 0.0023759042378515005, -0.0273828636854887, -0.015260240994393826, -0.004832841921597719, -0.0007702240254729986, 0.01856641098856926, -0.031039098277688026, 0.0073967440985143185, 0.018721995875239372, -0.023026498034596443, -0.008200597018003464, -0.023480286821722984, -0.16450461745262146, 0.025710329413414, 0.01681608520448208, -0.009023898281157017, 0.023428425192832947, -0.022754225879907608, 0.027616240084171295, 0.015234310179948807, -0.009224860928952694, 0.005166700109839439, 0.0008131718495860696, 0.0038507150020450354, -0.03153178095817566, -0.0026757284067571163, 0.003335341578349471, 0.00672254478558898, -0.030546413734555244, 0.036277107894420624, 0.017256908118724823, 0.0010526260593906045, 0.0053125605918467045, -0.02091314271092415, -0.0016555157490074635, -0.0012454859679564834, 0.023467320948839188, 0.009497134014964104, 0.0046351198107004166, 0.005380628630518913, -0.021691065281629562, -0.013062611222267151, -0.048023734241724014, -0.0008427490829490125, 0.017321735620498657, 0.021340999752283096, 0.011740143410861492, 0.012219862081110477, -0.012984818778932095, 0.007020748220384121, -0.015130587853491306, -0.016193747520446777, 0.0071439193561673164, 0.03236156702041626, 0.024997234344482422, 0.01185683161020279, 0.010735327377915382, 0.04636416584253311, 0.014599007554352283, -0.009004450403153896, 0.019383229315280914, -0.009607339277863503, -0.00414891866967082, -0.008336733095347881, -0.019888877868652344, -0.0005830365116707981, 0.02771996334195137, 0.005620488431304693, -0.00701426574960351, 0.013730327598750591, 0.014145219698548317, 0.011331734247505665, -0.021807754412293434, 0.022857949137687683, 0.01593444123864174, -0.0031343784648925066, 0.001282761339098215, -0.028627539053559303, 0.013354332186281681, 0.0034098925534635782, -0.014689764939248562, -0.004784221760928631, -0.015208380296826363, -0.00796722061932087, -0.008693280629813671, -0.02311725541949272, 0.011629937216639519, -0.012323584407567978, -0.03243935853242874, 0.007643085904419422, 0.00766253424808383, 0.0028702090494334698, -0.017412493005394936, 0.026267841458320618, 0.010884428396821022, -0.03448788449168205, 0.004327192436903715, 0.018838683143258095, -0.02228747308254242, -0.014702730812132359, -0.01020374707877636, -0.027694031596183777, 0.006122896447777748, -0.004252641461789608, -0.012686614878475666, -0.008829417638480663, 0.03319134935736656, 0.01789221167564392, 0.021250242367386818, -0.006683648563921452, 0.009412859566509724, -0.02294870652258396, 0.0009659201023168862, -0.008336733095347881, -0.019603639841079712, -0.012116138823330402, 0.009775889106094837, 0.03993334248661995, 0.009892578236758709, 0.017153184860944748, 0.015545479021966457, -0.01288109552115202, -0.020433424040675163, 0.013652535155415535, 0.022170783951878548, 0.024102624505758286, -0.003623821074143052, 0.03230970352888107, 0.01852751523256302, -0.03132433444261551, -0.017218012362718582, 0.011279872618615627, 0.052250444889068604, 0.005604281555861235, 0.010722361505031586, 0.006155309733003378, -0.016362298280000687, 0.0038020950742065907, -0.1179330125451088, 0.0006563718779943883, 0.006923507899045944, 0.010300987400114536, 0.010313952341675758, 0.016128921881318092, 0.010683465749025345, 0.032050397247076035, -0.0040808506309986115, 0.011318768374621868, -0.021016865968704224, -0.05787741392850876, -0.018786821514368057, -0.03155771270394325, 0.010994634591042995, -0.00672254478558898, 0.010605673305690289, -0.029042430222034454, -0.018294138833880424, 0.01147435326129198, -0.0367957204580307, 0.016906842589378357, 0.010385261848568916, -0.006301170215010643, -0.014547145925462246, -0.004356364719569683, -0.03181701898574829, -0.0031505851075053215, 0.004936564713716507, 0.012952405028045177, 0.010398227721452713, -0.018164483830332756, 0.01794407330453396, -0.020977970212697983, -0.0003221084189135581, 0.007617155089974403, 0.0036173383705317974, -0.01026209071278572, 0.037651438266038895, -0.015662167221307755, 0.011156701482832432, -0.014599007554352283, -0.00417160801589489, -0.03412485495209694, 0.010022231377661228, 0.004084091633558273, -0.005659384187310934, -0.0012973473640158772, 0.02266346849501133, -0.015195414423942566, -0.021211346611380577, -0.01056029461324215, -0.008284871466457844, -0.001761669758707285, 0.005711245816200972, 0.009205413050949574, 0.008997967466711998, -0.021470654755830765, -0.02379145473241806, 0.013872946612536907, -0.004845807328820229, -0.016193747520446777, -0.003912300802767277, 0.00304200011305511, -0.002687073079869151, -0.007617155089974403, 0.003983610309660435, -0.028575677424669266, 0.012939440086483955, -0.004434156697243452, -0.020381562411785126, 0.0030338966753333807, -0.022131888195872307, 0.0012187449028715491, -0.020251909270882607, 0.003640027716755867, -0.018449721857905388, 0.008557144552469254, 0.029042430222034454, -0.00807094294577837, -0.025502884760499, -0.025852948427200317, 0.03057234361767769, -0.032205980271101, 0.011779039166867733, 0.007481019012629986, -0.010112988762557507, 0.017114289104938507, 0.011623455211520195, -0.01751621626317501, -0.009341550059616566, -0.005238009616732597, -0.013561777770519257, -0.005001391749829054, -0.014702730812132359, 0.008609006181359291, -0.009568443521857262, 0.00857011042535305, 0.0027049004565924406, 0.009101689793169498, -0.018294138833880424, -0.0010202126577496529, -0.07286538183689117, 0.01214855257421732, -0.011403043754398823, 0.0032656528055667877, 0.0046221548691391945, -0.017568077892065048, 0.019136887043714523, -0.022546779364347458, -0.0037826469633728266, -0.004913875367492437, -0.01572699472308159, 0.034306369721889496, 0.013509916141629219, -0.014158184640109539, -0.011014082469046116, -0.010787188075482845, 0.005027322564274073, 0.002033942611888051, 0.017218012362718582, 0.02478978969156742, -0.010430640541017056, 0.0027437966782599688, 0.00802556425333023, -0.01406742725521326, 0.0038442325312644243, 0.0035038914065808058, -0.003345065750181675, 0.02386924810707569, -0.00384747376665473, -0.012550478801131248, 0.0008500420954078436, -0.012025381438434124, 0.015662167221307755, 0.019914809614419937, 0.029846282675862312, -0.026656802743673325, -0.006203929893672466, -0.011033530347049236, 0.04947585612535477, 0.03575849160552025, -0.007960737682878971, -0.024984268471598625, 0.013548812828958035, -0.02484164945781231, -0.01406742725521326, 0.011681798845529556, -0.022806087508797646, 0.0018378413515165448, 0.030961304903030396, 0.007928323931992054, 0.03251715004444122, 0.010884428396821022, 0.002808623481541872, -0.008466387167572975, 0.02379145473241806, -0.019162818789482117, 0.05357291176915169, -0.0044049848802387714, -0.0040581608191132545, -0.013471020385622978, 0.020718662068247795, 0.00829783733934164, -0.01685498282313347, -0.004100298509001732, -0.000024132808903232217, -0.014482319355010986, -0.03404706344008446, 0.007876462303102016, 0.0011855211341753602, -0.0405556783080101, -0.01225227490067482, -0.006268756929785013, 0.015312102623283863, 0.015299137681722641, 0.013548812828958035, 0.014560110867023468, 0.01471569575369358, -0.002121458761394024, -0.01100111659616232, 0.00015933225222397596, 0.01965550146996975, -0.003769681556150317, -0.02826450765132904, 0.01413225382566452, 0.029198015108704567, 0.048568278551101685, -0.005461662542074919, 0.014274872839450836, 0.0036529931239783764, 0.005160217639058828, 0.0010145402047783136, 0.017243942245841026, -0.006793854292482138, 0.0005344163510017097, 0.01341915875673294, 0.019538814201951027, -0.003721061395481229, -0.01056029461324215, 0.005033805035054684, 0.03562884032726288, -0.004832841921597719, 0.012997783720493317, -0.006443789228796959, -0.015817752107977867, -0.015947405248880386, 0.023208012804389, -0.019590675830841064, -0.0267605260014534, -0.008045012131333351, 0.0018005658639594913, 0.022935740649700165, -0.006323859561234713, -0.0033677550964057446, 0.02027783915400505, -0.020433424040675163, 0.01689387857913971, -0.027019832283258438, -0.040166717022657394, -0.0001858707400970161, 0.009393410757184029, 0.0010169713059440255, 0.00733839999884367, 0.00923782680183649, -0.011007599532604218, 0.022339332848787308, 0.01406742725521326, 0.01659567467868328, -0.021794788539409637, -0.019085025414824486, -0.008245975710451603, 0.016323402523994446, -0.0023759042378515005, -0.0077208783477544785, -0.001962633104994893, 0.0036108556669205427, -0.0008832658641040325, -0.0267605260014534, 0.02873126231133938, -0.022935740649700165, 0.02412855438888073, -0.005513523705303669, 0.00507918419316411, 0.005951105151325464, 0.005173183046281338, 0.005001391749829054, -0.0177625585347414, 0.015130587853491306, -0.01999260112643242, -0.0192406103014946, 0.02140582725405693, -0.007377295754849911, 0.02927580662071705, -0.015104657039046288, -0.01216800045222044, 0.0034552712459117174, -0.003481202060356736, 0.013561777770519257, 0.0022592158056795597, -0.01183090079575777, 0.013665501028299332, 0.017075393348932266, 0.008511765860021114, -0.007409709505736828, -0.0014261907199397683, -0.003058206755667925, 0.0031424816697835922, 0.0021846650633960962, -0.000989419873803854, -0.022144854068756104, 0.0036270625423640013, -0.006233102176338434, -0.016504917293787003, 0.003999816719442606, 0.017931107431650162, -0.025956671684980392, 0.021626237779855728, 0.002192768268287182, -0.001260882243514061, 0.018721995875239372, -0.023493250831961632, 0.030598275363445282, -0.011616972275078297, -0.019331367686390877, 0.01505279541015625, 0.01505279541015625, 0.004524914547801018, 0.0019042887724936008, -0.014962038025259972]

语义相似的词通常由在向量空间中彼此靠近的向量表示。这使得加法和减法等数学运算能够承载语义意义。例如，“国王”的向量表示减去“男人”再加上“女人”应该接近“女王”的向量表示。换句话说，向量嵌入是特定数据对象的数值表示。

向量索引允许您根据节点或关系的嵌入属性与查询中指定的嵌入属性之间的相似性，检索节点或关系的邻域。

创建向量索引

向量索引是用于节点或单关系类型、单属性索引的单标签、单属性索引。它可用于索引节点或关系，通过索引的维度和向量相似性函数有效识别 LIST<INTEGER | FLOAT> 属性。请注意，可用的向量索引提供程序（vector-2.0（默认）和 vector-1.0（已弃用））支持不同的索引模式、属性值类型和向量维度。有关更多信息，请参阅 用于兼容性的向量索引提供程序。

向量索引使用 CREATE VECTOR INDEX [index_name] 命令创建。建议在创建时为索引命名。如果创建时未命名，则会分配一个随机名称。从 Neo4j 5.16 开始，索引名称也可以作为参数提供：CREATE VECTOR INDEX $name …​。

索引名称必须在所有索引和约束中唯一。
新创建的索引不会立即可用，而是在后台创建。
创建索引需要CREATE INDEX 权限。
为 Movie 节点的 embedding 属性创建向量索引 5.15 版本引入
CREATE VECTOR INDEX moviePlots IF NOT EXISTS (1)
FOR (m:Movie)
ON m.embedding
OPTIONS { indexConfig: {
 `vector.dimensions`: 1536,
 `vector.similarity_function`: 'cosine'
}} (2)
1 CREATE VECTOR INDEX 命令是可选幂等的。这意味着如果尝试两次创建相同的索引，其默认行为是抛出错误。使用 IF NOT EXISTS 时，如果已经存在同名、相同模式或两者都相同的索引，则不会抛出错误，也不会发生任何事情。如果存在同名约束，仍可能抛出错误。自 Neo4j 5.17 起，当什么也没发生时，会返回一条信息性通知，显示阻止创建的现有索引。
2 在 Neo4j 5.23 之前，OPTIONS 映射是强制性的，因为不设置向量维度和相似性函数就无法创建向量索引。自 Neo4j 5.23 起，两者都可以省略。要阅读有关可用配置设置的更多信息，请参阅 配置设置。在此示例中，向量维度明确设置为 1536，向量相似性函数设置为 'cosine'，这通常是文本嵌入的首选相似性函数。要阅读有关可用相似性函数的更多信息，请参阅 余弦和欧几里得相似性函数。
在 Neo4j 5.15 之前，节点向量索引是使用 db.index.vector.createNodeIndex 过程创建的。

您还可以使用以下语法为特定类型关系上的给定属性创建向量索引

在单个属性上为关系类型创建向量索引 5.18 版本引入
CREATE VECTOR INDEX name IF NOT EXISTS
FOR ()-[r:REL_TYPE]-() ON (r.embedding)
OPTIONS { indexConfig: {
 `vector.dimensions`: $dimension,
 `vector.similarity_function`: $similarityFunction
}}

配置设置

有关不同索引提供程序接受的值的更多信息，请参阅 用于兼容性的向量索引提供程序。

vector.dimensions

要索引的向量的维度。有关更多信息，请参阅 Neo4j 中的向量和嵌入。此设置可以省略，任何 LIST<INTEGER | FLOAT> 都可以被索引和查询，按其维度分隔，但只有相同维度的向量才能进行比较。设置此值会添加额外的检查，确保只有配置了维度的向量才会被索引，并且使用不同维度的向量查询索引将返回错误。

建议在创建向量索引时提供维度。
接受的值

包含 1 到 4096 的 INTEGER。

默认值

无。在 Neo4j 5.23 之前，此设置是强制性的。

vector.similarity_function

用于评估两个向量相似性的相似性函数的名称。要阅读有关可用相似性函数的更多信息，请参阅 余弦和欧几里得相似性函数。

接受的值

STRING: 'cosine', 'euclidean'。

默认值

'cosine'。在 Neo4j 5.23 之前，此设置是强制性的。

vector.quantization.enabled

量化是一种减小向量表示大小的技术。启用量化可以加速搜索性能，但可能会稍微降低准确性。建议在内存有限的机器上启用量化。在 Neo4j 5.23 之前创建的向量索引此设置实际上为 false。

接受的值

BOOLEAN: true, false。

默认值

true

高级配置设置

vector.hnsw.m

M 参数控制 HNSW（Hierarchical Navigable Small Worlds）图中每个节点的最大连接数。增加此值可能会提高准确性，但会增加索引填充和更新时间，特别是对于高维向量。在 Neo4j 5.23 之前创建的向量索引此设置实际上设置为 16。

接受的值

包含 1 到 512 的 INTEGER。

默认值

16

vector.hnsw.ef_construction

在将向量插入 HNSW 图时跟踪的最近邻居数量。增加此值会提高索引质量，并可能导致更高的准确性（回报递减），但会增加索引填充和更新时间。在 Neo4j 5.23 之前创建的向量索引此设置实际上设置为 100。

接受的值

包含 1 到 3200 的 INTEGER。

默认值

100

查询向量索引

要查询节点向量索引，请使用 db.index.vector.queryNodes 过程。

索引在其 state 为 POPULATING（创建后立即发生）时无法使用。要检查向量索引的 state — 无论是 ONLINE（可用）还是 POPULATING（仍在构建中；populationPercent 列显示索引创建的进度）— 运行以下命令：SHOW VECTOR INDEXES。
db.index.vector.queryNodes 的签名
db.index.vector.queryNodes(indexName :: STRING, numberOfNearestNeighbours :: INTEGER, query :: ANY) :: (node :: NODE, score :: FLOAT)

  • indexName 指的是要查询的向量索引的唯一名称。

  • numberOfNearestNeighbours 指的是要返回的最近邻居的数量。

  • query 向量指的是要搜索邻域的 LIST<INTEGER | FLOAT>。

该过程返回节点的邻域及其相应的相似性分数，并按分数排序。分数的范围在 0 到 1 之间，分数越接近 1，索引向量与查询向量越相似。

找到与《教父》情节最相似的 5 部电影
MATCH (m:Movie {title: 'Godfather, The'})
CALL db.index.vector.queryNodes('moviePlots', 5, m.embedding)
YIELD node AS movie, score
RETURN movie.title AS title, movie.plot AS plot, score
结果
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| title                      | plot                                                                                                                                                                                                                     | score              |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| "Godfather, The"           | "The aging patriarch of an organized crime dynasty transfers control of his clandestine empire to his reluctant son."                                                                                                    | 1.0                |
| "Godfather: Part III, The" | "In the midst of trying to legitimize his business dealings in New York and Italy in 1979, aging Mafia don Michael Corleone seeks to avow for his sins while taking a young protégé under his wing."                     | 0.9648237228393555 |
| "Godfather: Part II, The"  | "The early life and career of Vito Corleone in 1920s New York is portrayed while his son, Michael, expands and tightens his grip on his crime syndicate stretching from Lake Tahoe, Nevada to pre-revolution 1958 Cuba." | 0.9547788500785828 |
| "Goodfellas"               | "Henry Hill and his friends work their way up through the mob hierarchy."                                                                                                                                                | 0.9300689697265625 |
| "Scarface"                 | "An ambitious and near insanely violent gangster climbs the ladder of success in the mob, but his weaknesses prove to be his downfall."                                                                                  | 0.9367183446884155 |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

请注意，返回的所有电影情节都围绕着犯罪家族组织展开。score 结果按降序返回，最佳匹配结果条目排在第一位（在这种情况下，《教父》的相似性分数为 1.0，这与使用此特定属性查询索引是预期结果）。如果不需要查询向量本身，添加谓词 WHERE score < 1 可以移除相同的向量。

要查询关系向量索引，请使用 db.index.vector.queryRelationships 过程。

db.index.vector.queryRelationships 的签名 5.18 版本引入
db.index.vector.queryRelationships(indexName :: STRING, numberOfNearestNeighbours :: INTEGER, query :: ANY) :: (relationship :: RELATIONSHIP, score :: FLOAT)

db.index.vector.queryRelationships 具有与 db.index.vector.queryNodes 相同的参数描述。

使用向量函数计算两个特定向量对之间的相似性分数，而无需使用向量索引。

性能建议

向量索引可以利用孵化中的 Java Vector API 显著提高速度。如果您使用的是兼容的 Java 版本，可以将以下设置添加到您的配置设置中

配置设置
server.jvm.additional=--add-modules=jdk.incubator.vector
虽然 Neo4j 5 系列至少需要 Java 17，但在 Neo4j 5.14-5.26 中，要利用此性能改进，至少需要 Java 20。如果您使用的是 Neo4j 2025.01 或更高版本，则需要 Java 21。有关不同 Neo4j 版本支持的 Java 版本的更多信息，请参阅操作手册 → 系统要求 → Java。

显示向量索引

要列出数据库中的所有向量索引，请使用 SHOW VECTOR INDEXES 命令。这与其他索引的 SHOW 命令相同，索引类型过滤为 VECTOR。

列出索引需要SHOW INDEX 权限。
示例 1. 显示所有向量索引
显示具有默认返回列的向量索引
SHOW VECTOR INDEXES
结果
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| id | name         | state    | populationPercent | type     | entityType | labelsOrTypes | properties        | indexProvider | owningConstraint | lastRead                 | readCount |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| 2  | "moviePlots" | "ONLINE" | 100.0             | "VECTOR" | "NODE"     | ["Movie"]     | ["embedding"]     | "vector-2.0"  | NULL             | 2024-05-07T09:19:09.225Z | 47        |
+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

有关所有返回列的完整描述，请参阅搜索性能索引 → 列出索引的结果列。

示例 2. 显示具有完整或过滤详细信息的向量索引

要返回完整的向量索引详细信息，请使用 YIELD *。

显示所有向量索引以及所有返回列
SHOW VECTOR INDEXES YIELD *
结果
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| id | name        | state    | populationPercent | type     | entityType | labelsOrTypes | properties        | indexProvider | owningConstraint| lastRead                  | readCount | trackedSince              | options                                                                                                                                                                                                       | failureMessage | createStatement                                                                                                                                                                                                                                              |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| 2  | "moviePlots"| "ONLINE" | 100.0             | "VECTOR" | "NODE"     | ["Movie"]     | ["embedding"]     | "vector-2.0"  | NULL            | 2024-05-07T09:19:09.225Z  | 47        | 2024-05-07T08:26:19.072Z  | {indexConfig: {`vector.dimensions`: 1536, `vector.hnsw.m`: 16, `vector.quantization.enabled`: TRUE, `vector.similarity_function`: "COSINE", `vector.hnsw.ef_construction`: 100}, indexProvider: "vector-2.0"} | ""             | "CREATE VECTOR INDEX `moviePlots` FOR (n:`Movie`) ON (n.`embedding`) OPTIONS {indexConfig: {`vector.dimensions`: 1536,`vector.hnsw.ef_construction`: 100,`vector.hnsw.m`: 16,`vector.quantization.enabled`: true,`vector.similarity_function`: 'COSINE'}}"   |
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

要仅返回特定详细信息，请在 YIELD 子句后指定所需的列名。

显示所有向量索引以及过滤后的返回列
SHOW VECTOR INDEXES YIELD name, type, entityType, labelsOrTypes, properties
结果
+----------------------------------------------------------------------+
| name         | type     | entityType | labelsOrTypes | properties    |
+----------------------------------------------------------------------+
| "moviePlots" | "VECTOR" | "NODE"     | ["Movie"]     | ["embedding"] |
+----------------------------------------------------------------------+

删除向量索引

向量索引使用与其他索引相同的命令 DROP INDEX 删除。从 Neo4j 5.16 开始，删除索引时也可以将索引名称作为参数：DROP INDEX $name。

删除索引需要DROP INDEX 权限。
删除向量索引
DROP INDEX moviePlots

用于兼容性的向量索引提供程序

自 Neo4j 5.18 起，默认的索引提供程序是 vector-2.0。自 Neo4j 5.26 起，创建索引时不再可能指定索引提供程序。相反，Neo4j 会选择性能最佳的提供程序（目前是 vector-2.0）。

以前创建的 vector-1.0 索引将继续运行。

了解有关向量索引提供程序差异的更多信息
支持 vector-1.0 vector-2.0

索引模式

用于节点的单标签、单属性索引。

 

不支持关系。

用于节点的单标签、单属性索引。

 

用于关系的单类型、单属性索引。

索引属性值类型

LIST<FLOAT>

LIST<INTEGER | FLOAT>

索引向量维度

INTEGER，介于 1 和 2048 之间（含）。

INTEGER，介于 1 和 4096 之间（含）。

余弦相似度向量有效性

所有向量分量都可以用 IEEE 754 单精度浮点数有限表示。

 

其 l2-范数非零且可以用 IEEE 754 单精度浮点数有限表示。

所有向量分量都可以用 IEEE 754 双精度浮点数有限表示。

 

其 l2-范数非零且可以用 IEEE 754 双精度浮点数有限表示。

 

每个向量分量与其 l2-范数之比可以用 IEEE 754 单精度浮点数有限表示。

余弦和欧几里得相似性函数

相似性函数的选择会影响哪些索引向量被认为是相似的，以及哪些是有效的。向量的语义含义本身可能决定选择哪种相似性函数。请参考您正在使用的特定向量嵌入模型的文档，因为它可能会建议某些相似性函数的偏好。否则，能够区分各种相似性函数可以帮助做出更明智的决定。

表 1. 相似性函数
名称 不区分大小写的参数 关键相似性特征

余弦

"cosine"

角度

欧几里得

"euclidean"

距离

对于 l2-归一化向量（单位向量），余弦和欧几里得相似性函数产生相同的相似性排序。

了解有关余弦相似性函数的更多信息

当向量之间的角度决定两个向量的相似程度时，使用余弦相似性。

余弦向量索引的有效向量是当

  • 所有向量分量都可以用 IEEE 754 双精度浮点数有限表示。[2]

  • 其 l2-范数非零且可以用 IEEE 754 双精度浮点数有限表示。

  • 每个向量分量与其 l2-范数之比可以用 IEEE 754 单精度浮点数有限表示。

余弦相似性在笛卡尔坐标系中解释向量。该度量与两个向量之间的角度相关。然而，角度可以用许多单位、符号约定和周期来描述。该角度的三角余弦既与上述角度约定无关，又是有界的。余弦相似性会反弹三角余弦。

The cosine of vector v and vector u is defined as half of the quanity 1 plus the scalar product of v hat u hat, which equals half of the quantity 1 plus the scalar product of vector v vector u over the product of the l2-norm of vector v and the l2 norm ov vector u, which exists in the bounded set of real numbers between 0 inclusive and 1 inclusive.

在上述等式中，三角余弦由两个单位向量的标量积给出。

了解有关欧几里得相似性函数的更多信息

当向量之间的距离决定两个向量的相似程度时，欧几里得相似性非常有用。

欧几里得向量索引的有效向量是当所有向量分量都可以用 IEEE 754 单精度浮点数有限表示时。

欧几里得相似性在笛卡尔坐标系中解释向量。该度量与欧几里得距离相关，即两点之间的距离。然而，该距离是无界的，作为相似性分数用处不大。欧几里得相似性限制了欧几里得距离的平方。

The Euclidean of vector v and vector u is defined as 1 over the quantity 1 plus the square of the l2-norm of vector v subtract vector u, which exists in the bounded set of real numbers between 0 exclusive and 1 inclusive.

向量索引过程

用法 过程 描述

创建节点向量索引。

db.index.vector.createNodeIndex

使用给定的向量维度和相似性函数，为指定的标签和属性创建向量索引。已被 CREATE VECTOR INDEX 命令取代。

使用节点向量索引。

db.index.vector.queryNodes

查询给定的节点向量索引。返回请求数量的近似最近邻节点及其相似性分数，并按分数排序。

使用关系向量索引。

db.index.vector.queryRelationships

查询给定的关系向量索引。返回请求数量的近似最近邻关系及其相似性分数，并按分数排序。5.18 版本引入

设置节点向量属性。

db.create.setNodeVectorProperty

以比直接使用SET更节省空间的方式，使用给定向量更新给定节点属性。取代了db.create.setVectorProperty。测试版 5.13 版本引入

设置节点向量属性。

db.create.setVectorProperty

已被db.create.setNodeVectorProperty取代。已弃用 测试版

设置关系向量属性。

db.create.setRelationshipVectorProperty

以比直接使用SET更节省空间的方式，使用给定向量更新给定关系属性。测试版 5.18 版本引入

限制和已知问题

自 Neo4j 5.13 起，向量索引不再是测试版功能。但是，它仍然存在一些限制

  • 查询是近似最近邻搜索。所请求的 k 个最近邻居可能不是精确的 k 个最近邻居，但在更广泛的邻域中是接近的。

  • 对于请求的大量最近邻居 k，如果 k 接近索引向量的总数，搜索可能会检索少于 k 个结果。

  • 一个模式上只能有一个向量索引。例如，您不能在相同的标签-属性键对上同时拥有一个欧几里得和一个余弦向量索引。

  • 同一事务中的更改对索引不可见。

向量索引还包含一些已知问题。下表列出了这些问题，如果已修复，则列出了修复版本。

表 2. 已知问题
已知问题 修复于

在 Neo4j 5.18 及更高版本中，如果数据库上次写入是在 Neo4j 5.11 之前的版本中进行的，并且旧版过程是新版本上使用的第一个写入操作，则使用旧版过程 db.index.vector.createNodeIndex 创建向量索引可能会失败并出现错误。在 Neo4j 5.20 中，此错误已得到澄清。

使用 CREATE VECTOR INDEX 命令可以避免此问题。如果无法避免使用此过程，则在使用此过程之前，在新版二进制文件上对数据库执行任何其他写入操作将避免此问题。

SHOW PROCEDURES 中的过程签名将向量参数的类型渲染为 ANY，而不是语义正确的 LIST<INTEGER | FLOAT> 类型。

类型仍强制为 LIST<INTEGER | FLOAT>。

没有提供用于调整索引的设置或选项。

Neo4j 5.23

仅支持节点向量索引。

Neo4j 5.18

向量索引无法自动生成名称。

Neo4j 5.15

没有用于创建向量索引的 Cypher 语法。

使用过程 db.index.vector.createNodeIndex 创建向量索引。过程签名

db.index.vector.createNodeIndex(indexName :: STRING, label :: STRING, propertyKey :: STRING, vectorDimension :: INTEGER, vectorSimilarityFunction :: STRING)

Neo4j 5.15

缺少 SHOW INDEXES 命令的标准索引类型过滤。

向量索引的过滤也可以通过 WHERE 子句完成

SHOW INDEXES
WHERE type = 'VECTOR'

Neo4j 5.15

在集群设置中，向量索引可能错误地拒绝有效查询。这是由于在处理跟随者上的索引功能时出现问题。

由于索引功能将在重启后正确配置，因此可以通过在创建向量索引后滚动集群来解决此问题。

有关 Neo4j 中集群的更多信息，请参阅操作手册 → 集群。

Neo4j 5.14

查询索引中的单个近似最近邻居会失败验证检查。传递 null 值也会导致无用的异常。

Neo4j 5.13

如果事务状态包含更改，向量索引查询会抛出异常。这意味着写入操作只能在事务中最后一次向量索引查询之后进行。

如果需要运行多个向量索引查询并根据结果进行更改，可以将其放入 CALL { ... } IN TRANSACTIONS 子句中运行，以将它们与外部事务的状态隔离，从而解决此问题。

Neo4j 5.13

SHOW PROCEDURES 不显示向量索引过程。

这些过程仍然可用，只是不可见。

Neo4j 5.12

将 null 作为参数传递给某些过程参数可能会生成令人困惑的异常。

Neo4j 5.12

向量索引的创建跳过了将维度限制为 2048 的检查。

在 Neo4j 5.11 中配置维度大于 2048 的向量索引在应用限制后应继续工作。

Neo4j 5.12

余弦相似度的验证会验证向量的 l2-范数是否可以用 IEEE 754 双精度浮点数有限表示，而不是单精度。这可能导致某些大分量向量被错误索引，并返回 ±0.0 的相似度分数。

Neo4j 5.12

使用余弦向量索引时，db.index.vector.queryNodes 查询向量验证不正确。l2-范数验证仅考虑向量的最后一个分量。如果该分量为 ±0.0，则一个否则有效的查询向量将被抛出为无效。这还可能导致一些无效向量被用于查询，并返回 ±0.0 的相似度分数。

对于 l2-归一化向量（单位向量），即具有单位长度 向量 v 的 l2-范数为 1的向量，欧几里得和余弦相似性函数产生相同的相似性排序。建议对您的向量进行归一化（如果需要），并使用欧几里得向量索引。

Neo4j 5.12

SHOW INDEXES 中的向量索引 createStatement 字段未能正确转义索引名称、标签和属性键中的单引号。

Neo4j 5.12

复制带向量索引的数据库存储不会记录重新创建命令，而是记录一个错误

ERROR: [StoreCopy] Unable to format statement for index 'index-name'

由于

java.lang.IllegalArgumentException: Did not recognize index type VECTOR

如果需要存储复制，请记下 SHOW INDEX 命令返回的 createStatement 列中的信息。例如

SHOW INDEXES YIELD type, createStatement
WHERE type = 'VECTOR'
RETURN createStatement

Neo4j 5.12

一些阻止在数据库滚动升级期间使用新功能的保护措施缺失。这可能导致在运行 Neo4j 5.11 的集群成员上创建向量索引的事务分发到运行旧版 Neo4j 的其他集群成员。旧版 Neo4j 将无法理解该事务。

在 system 数据库上调用 dbms.upgrade() 之前，请确保所有集群成员都已更新为使用 Neo4j 5.11（或更高版本）。提交后，可以在集群上安全地创建向量索引。

Neo4j 5.12
1. Lucene 实现了一个分层可导航小世界 (HNSW) 图，以对向量字段执行 k 近似最近邻 (k-ANN) 查询。有关更多信息，请参阅 使用分层可导航小世界图进行高效和稳健的近似最近邻搜索 — Yury A. Malkov 和 Dmitry A. Yashunin
2. IEEE 浮点算术标准
© . All rights reserved.