具有 128 维列和距离查询如下：
CREATE TABLE testes (id serial, name text, face cube);
CREATE INDEX testes_face_idx ON testes USING gist(face gist_cube_ops);
explain analyse select name from testes order by face <-> cube(array[-0.12341737002134323, 0.013954268768429756, 0.041934967041015625, -0.027295179665088654, -0.1557110995054245, -0.03121102601289749, 0.017772752791643143, -0.17166048288345337, 0.09068921208381653, -0.13417541980743408, 0.17567767202854156, -0.06697715818881989, -0.1830156147480011, -0.08423275500535965, -0.0623091384768486, 0.13855493068695068, 0.01960853487253189, -0.12219744175672531, -0.1498851776123047, -0.1448814421892166, -0.04667501151561737, 0.10095512866973877, -0.010014703497290611, 0.028698112815618515, -0.12299459427595139, -0.2449578195810318, -0.04310397803783417, -0.0786057710647583, -0.0006230985745787621, -0.012474060989916325, -0.0008601928129792213, 0.13489803671836853, -0.17316003143787384, -0.056241780519485474, 0.04442238435149193, 0.14999067783355713, -0.04893124848604202, -0.03364997357130051, 0.17365986108779907, 0.014477224089205265, -0.14650581777095795, 0.06581126153469086, 0.05907478928565979, 0.24371813237667084, 0.199946790933609, -0.07071209698915482, 0.030652550980448723, -0.06517398357391357, 0.19778677821159363, -0.3098893463611603, 0.04202471300959587, 0.06682528555393219, 0.11922725290060043, 0.04458840191364288, 0.07993366569280624, -0.09807920455932617, -0.02106720767915249, 0.17947503924369812, -0.15518437325954437, 0.11362187564373016, 0.05837336927652359, -0.11214996874332428, -0.13685055077075958, -0.10379699617624283, 0.13636618852615356, 0.1293313056230545, -0.11564487218856812, -0.10860224068164825, 0.2200884073972702, -0.16025489568710327, -0.05225272849202156, 0.10024034976959229, -0.10087429732084274, -0.1339828222990036, -0.27345386147499084, 0.1377202421426773, 0.437569797039032, 0.17741253972053528, -0.18133604526519775, -0.052022092044353485, -0.03961575776338577, 0.07023612409830093, 0.013044891878962517, 0.007585287094116211, -0.015369717963039875, -0.13501259684562683, -0.07265347242355347, 0.011824256740510464, 0.21609637141227722, -0.012745738960802555, -0.04935416579246521, 0.23810920119285583, 0.031168460845947266, 0.034897398203611374, -0.014598412439227104, 0.0809953436255455, -0.11255790293216705, -0.06797720491886139, -0.09544365853071213, -0.008347772061824799, 0.0790143683552742, -0.11389575153589249, 0.046258144080638885, 0.12429731339216232, -0.15094317495822906, 0.24766354262828827, -0.10882335901260376, 0.022879034280776978, 0.03814130276441574, -0.013778979890048504, -0.01565537415444851, 0.07461182028055191, 0.14960512518882751, -0.15471796691417694, 0.18988533318042755, 0.10148166120052338, 0.0060581183061003685, 0.1403576135635376, 0.06793759763240814, 0.04792795702815056, 0.00046137627214193344, -0.007764225825667381, -0.15212640166282654, -0.18374276161193848, 0.03233196958899498, -0.05509287118911743, -0.0091116763651371, 0.06819846481084824]) limit 3;
Limit (cost=0.41..5.44 rows=3 width=18) (actual time=1557.082..1697.857 rows=3 loops=1)
-> Index Scan using testes_face_idx on testes (cost=0.41..1859319.05 rows=1109532 width=18) (actual time=1557.081..1697.855 rows=3 loops=1)
Order By: (face <-> '(-0.123417370021343, 0.0139542687684298, 0.0419349670410156, -0.0272951796650887, -0.155711099505424, -0.0312110260128975, 0.0177727527916431, -0.171660482883453, 0.0906892120838165, -0.134175419807434, 0.175677672028542, -0.0669771581888199, -0.183015614748001, -0.0842327550053596, -0.0623091384768486, 0.138554930686951, 0.0196085348725319, -0.122197441756725, -0.149885177612305, -0.144881442189217, -0.0466750115156174, 0.100955128669739, -0.0100147034972906, 0.0286981128156185, -0.122994594275951, -0.244957819581032, -0.0431039780378342, -0.0786057710647583, -0.000623098574578762, -0.0124740609899163, -0.000860192812979221, 0.134898036718369, -0.173160031437874, -0.0562417805194855, 0.0444223843514919, 0.149990677833557, -0.048931248486042, -0.0336499735713005, 0.173659861087799, 0.0144772240892053, -0.146505817770958, 0.0658112615346909, 0.0590747892856598, 0.243718132376671, 0.199946790933609, -0.0707120969891548, 0.0306525509804487, -0.0651739835739136, 0.197786778211594, -0.30988934636116, 0.0420247130095959, 0.0668252855539322, 0.1192272529006, 0.0445884019136429, 0.0799336656928062, -0.0980792045593262, -0.0210672076791525, 0.179475039243698, -0.155184373259544, 0.11362187564373, 0.0583733692765236, -0.112149968743324, -0.13685055077076, -0.103796996176243, 0.136366188526154, 0.129331305623055, -0.115644872188568, -0.108602240681648, 0.22008840739727, -0.160254895687103, -0.0522527284920216, 0.100240349769592, -0.100874297320843, -0.133982822299004, -0.273453861474991, 0.137720242142677, 0.437569797039032, 0.177412539720535, -0.181336045265198, -0.0520220920443535, -0.0396157577633858, 0.0702361240983009, 0.0130448918789625, 0.00758528709411621, -0.0153697179630399, -0.135012596845627, -0.0726534724235535, 0.0118242567405105, 0.216096371412277, -0.0127457389608026, -0.0493541657924652, 0.238109201192856, 0.0311684608459473, 0.0348973982036114, -0.0145984124392271, 0.0809953436255455, -0.112557902932167, -0.0679772049188614, -0.0954436585307121, -0.0083477720618248, 0.0790143683552742, -0.113895751535892, 0.0462581440806389, 0.124297313392162, -0.150943174958229, 0.247663542628288, -0.108823359012604, 0.022879034280777, 0.0381413027644157, -0.0137789798900485, -0.0156553741544485, 0.0746118202805519, 0.149605125188828, -0.154717966914177, 0.189885333180428, 0.101481661200523, 0.00605811830610037, 0.140357613563538, 0.0679375976324081, 0.0479279570281506, 0.000461376272141933, -0.00776422582566738, -0.152126401662827, -0.183742761611938, 0.032331969588995, -0.0550928711891174, -0.0091116763651371, 0.0681984648108482)'::cube)
Planning time: 0.101 ms
Execution time: 1698.691 ms
然后我删除了索引，现在它更快了：
Limit (cost=186715.64..186715.65 rows=3 width=18) (actual time=1362.653..1362.667 rows=3 loops=1)
-> Sort (cost=186715.64..189489.47 rows=1109532 width=18) (actual time=1362.652..1362.652 rows=3 loops=1)
Sort Key: ((face <-> '(-0.123417370021343, 0.0139542687684298, 0.0419349670410156, -0.0272951796650887, -0.155711099505424, -0.0312110260128975, 0.0177727527916431, -0.171660482883453, 0.0906892120838165, -0.134175419807434, 0.175677672028542, -0.0669771581888199, -0.183015614748001, -0.0842327550053596, -0.0623091384768486, 0.138554930686951, 0.0196085348725319, -0.122197441756725, -0.149885177612305, -0.144881442189217, -0.0466750115156174, 0.100955128669739, -0.0100147034972906, 0.0286981128156185, -0.122994594275951, -0.244957819581032, -0.0431039780378342, -0.0786057710647583, -0.000623098574578762, -0.0124740609899163, -0.000860192812979221, 0.134898036718369, -0.173160031437874, -0.0562417805194855, 0.0444223843514919, 0.149990677833557, -0.048931248486042, -0.0336499735713005, 0.173659861087799, 0.0144772240892053, -0.146505817770958, 0.0658112615346909, 0.0590747892856598, 0.243718132376671, 0.199946790933609, -0.0707120969891548, 0.0306525509804487, -0.0651739835739136, 0.197786778211594, -0.30988934636116, 0.0420247130095959, 0.0668252855539322, 0.1192272529006, 0.0445884019136429, 0.0799336656928062, -0.0980792045593262, -0.0210672076791525, 0.179475039243698, -0.155184373259544, 0.11362187564373, 0.0583733692765236, -0.112149968743324, -0.13685055077076, -0.103796996176243, 0.136366188526154, 0.129331305623055, -0.115644872188568, -0.108602240681648, 0.22008840739727, -0.160254895687103, -0.0522527284920216, 0.100240349769592, -0.100874297320843, -0.133982822299004, -0.273453861474991, 0.137720242142677, 0.437569797039032, 0.177412539720535, -0.181336045265198, -0.0520220920443535, -0.0396157577633858, 0.0702361240983009, 0.0130448918789625, 0.00758528709411621, -0.0153697179630399, -0.135012596845627, -0.0726534724235535, 0.0118242567405105, 0.216096371412277, -0.0127457389608026, -0.0493541657924652, 0.238109201192856, 0.0311684608459473, 0.0348973982036114, -0.0145984124392271, 0.0809953436255455, -0.112557902932167, -0.0679772049188614, -0.0954436585307121, -0.0083477720618248, 0.0790143683552742, -0.113895751535892, 0.0462581440806389, 0.124297313392162, -0.150943174958229, 0.247663542628288, -0.108823359012604, 0.022879034280777, 0.0381413027644157, -0.0137789798900485, -0.0156553741544485, 0.0746118202805519, 0.149605125188828, -0.154717966914177, 0.189885333180428, 0.101481661200523, 0.00605811830610037, 0.140357613563538, 0.0679375976324081, 0.0479279570281506, 0.000461376272141933, -0.00776422582566738, -0.152126401662827, -0.183742761611938, 0.032331969588995, -0.0550928711891174, -0.0091116763651371, 0.0681984648108482)'::cube))
Sort Method: top-N heapsort Memory: 25kB
-> Seq Scan on testes (cost=0.00..172375.15 rows=1109532 width=18) (actual time=0.006..1239.698 rows=1109532 loops=1)
Planning time: 0.112 ms
Execution time: 1362.681 ms
任何想法从哪里开始调试？时间差从 100k 行到 1.1M 行。
它是否可能与“高”128 个维度有关？