Question

我注意到$ near和$ nearSphere返回完全不同的数据，我怀疑。毕竟，当纬度接近赤道时，球距离与欧氏距离的差别不大。

db.tablebusiness.find({ "LongitudeLatitude" : { "$nearSphere" : [106.772835, -6.186753], "$maxDistance" : 0.053980478460939611 }, "Prominent" : { "$gte" : 15 }, "indexContents" : { "$all" : [/^soto/, /^nasi/] } }).limit(200);

它返回48个数据。

无论如何我会附上它

/* 0 */
{
  "_id" : "nasi-uduk-soto-ayam__-6.18_106.77",
  "BuildingID" : null,
  "Title" : "Nasi Uduk Soto Ayam",
  "InBuildingAddress" : null,
  "Building" : null,
  "Street" : "Jl. Panjang",
  "Districts" : [],
  "City" : "Jakarta",
  "Country" : "Indonesia",
  "LongitudeLatitudeFromGoogle" : null,
  "DistanceFromGoogleAddress" : 0.0,
  "Checkin" : 0,
  "Note" : null,
  "PeopleCount" : 0,
  "Prominent" : 45.5,
  "CountViews" : 0,
  "StreetAdditional" : null,
  "LongitudeLatitude" : {
    "Longitude" : 106.765673160553,
    "Latitude" : -6.17522230915668
  },
  "Rating" : {
    "Stars" : 0.0,
    "Weight" : 0.0
  },
  "CurrentlyWorkedURL" : null,
  "Reviews" : [],
  "ZIP" : null,
  "Tags" : ["Restaurant"],
  "Phones" : [],
  "Website" : null,
  "Email" : null,
  "Price" : null,
  "openingHour" : null,
  "Promotions" : [],
  "SomethingWrong" : false,
  "BizMenus" : [],
  "Brochures" : [],
  "Aliases" : [],
  "indexContents" : ["restaura", "estauran", "staurant", "taurant", "aurant", "urant", "rant", "ant", "nt", "t", "nasi", "asi", "si", "i", "uduk", "duk", "uk", "k", "soto", "oto", "to", "o", "ayam", "yam", "am", "m"]
}

/* 1 */
{
  "_id" : "nasi-soto-padang_pasar-slipi-jaya_-6.19_106.80",
  "BuildingID" : null,
  "Title" : "Nasi Soto Padang",
  "InBuildingAddress" : "Lt.1 Los Alas",
  "Building" : null,
  "Street" : "Jl.Kemanggisan Utama Raya",
  "Districts" : [],
  "City" : "Jakarta",
  "Country" : "Indonesia",
  "LongitudeLatitudeFromGoogle" : null,
  "DistanceFromGoogleAddress" : 0.0,
  "Checkin" : 0,
  "Note" : null,
  "PeopleCount" : 0,
  "Prominent" : 45.5,
  "CountViews" : 0,
  "StreetAdditional" : null,
  "LongitudeLatitude" : {
    "Longitude" : 106.79647564888,
    "Latitude" : -6.18998465381734
  },
  "Rating" : {
    "Stars" : 0.0,
    "Weight" : 0.0
  },
  "CurrentlyWorkedURL" : null,
  "Reviews" : [],
  "ZIP" : null,
  "Tags" : ["Restaurant"],
  "Phones" : [],
  "Website" : null,
  "Email" : null,
  "Price" : null,
  "openingHour" : null,
  "Promotions" : [],
  "SomethingWrong" : false,
  "BizMenus" : [],
  "Brochures" : [],
  "Aliases" : [],
  "indexContents" : ["restaura", "estauran", "staurant", "taurant", "aurant", "urant", "rant", "ant", "nt", "t", "nasi", "asi", "si", "i", "soto", "oto", "to", "o", "padang", "adang", "dang", "ang", "ng", "g"]
}

...

/* 47 */
{
  "_id" : "nasi-gandul__-7.43_109.24",
  "BuildingID" : null,
  "Title" : "Nasi Gandul",
  "InBuildingAddress" : null,
  "Building" : null,
  "Street" : "Jl. Brobahan Pr - 40 rt 004 Rw 004",
  "Districts" : [],
  "City" : "Purwokerto",
  "Country" : "Indonesia",
  "LongitudeLatitudeFromGoogle" : null,
  "DistanceFromGoogleAddress" : 0.0,
  "Checkin" : 0,
  "Note" : null,
  "PeopleCount" : 0,
  "Prominent" : 30.5,
  "CountViews" : 0,
  "StreetAdditional" : null,
  "LongitudeLatitude" : {
    "Longitude" : 109.239182174206,
    "Latitude" : -7.42585664273589
  },
  "Rating" : {
    "Stars" : 3.0,
    "Weight" : 1.0
  },
  "CurrentlyWorkedURL" : null,
  "Reviews" : [],
  "ZIP" : "53116",
  "Tags" : ["Angkringan", "Restaurant Indonesian", "Soto & Sop"],
  "Phones" : ["+62(281)7918181"],
  "Website" : null,
  "Email" : null,
  "Price" : null,
  "openingHour" : null,
  "Promotions" : [],
  "SomethingWrong" : false,
  "BizMenus" : [],
  "Brochures" : [],
  "Aliases" : [],
  "indexContents" : ["angkring", "ngkringa", "gkringan", "kringan", "ringan", "ingan", "ngan", "gan", "an", "n", "restaura", "estauran", "staurant", "taurant", "aurant", "urant", "rant", "ant", "nt", "t", "indonesi", "ndonesia", "donesian", "onesian", "nesian", "esian", "sian", "ian", "soto", "oto", "to", "o", "&", "sop", "op", "p", "nasi", "asi", "si", "i", "gandul", "andul", "ndul", "dul", "ul", "l"]
}

我将数据放入excel并使用此公式计算距离

= SQRT（POWER（E2- $ G $ 1,2）+ POWER（（F2- $ H $ 1）* COS（$ H $ 1 * PI（）/ 180），2））

那个人应该大致接近球距。还要注意纬度是-6，离赤道不远。

结果如下

0.013516826
0.023857967
0.037658667
0.038737146
0.042414787
0.046725248
0.051006427
0.053567221
0.057448344
0.061592999
0.062329244
0.065276161
0.066035611
0.076251787
0.109671831
0.112097201
0.13417281
0.136471939
0.172293693
1.058802838
1.078123028
1.079160684
1.080954023
1.081148114
1.081099449
1.092061283
1.094281476
1.094431917
1.096845722
1.097063729
1.096953691
1.097201996
1.105389179
1.105442127
1.10839237
1.108717834
1.108840349
1.111636423
1.113187903
1.118767984
1.118767984
1.133952371
1.135077548
1.154967917
1.161142923
1.185994885
1.199509086
2.756884824

以下是我的Excel工作表 enter image description here

的屏幕截图

这是实际的excel

            106.772835  -6.186753
  "_id"      "nasi-uduk-soto-ayam__-6.18_106.77",   106.7656732 -6.175222309    0.013516826
  "_id"      "nasi-soto-padang_pasar-slipi-jaya_-6.19_106.80",  106.7964756 -6.189984654    0.023857967
  "_id"      "nasi-uduk-soto-ayam__-6.22_106.77",   106.7718959 -6.224620499    0.037658667
  "_id"      "nasi-campur-%26-soto-babat-kenanga_komp.-ruko-permata-senayan%2C_-6.22_106.79",   106.79199   -6.22062    0.038737146
  "_id"      "soto-mie-nasi_indomaret-(univ.-mercu-buana)_-6.21_106.74",    106.7379928 -6.211082144    0.042414787
  "_id"      "soto-kudus%2C-soto-ayam-%26amp%3B-nasi-pindang_plaza-senayan_-6.23_106.80",   106.7989969 -6.225694167    0.046725248
  "_id"      "soto-kudus%2C-soto-ayam-%26amp%3B-nasi-pindang_plaza-bri-ii_-6.22_106.81",    106.8136847 -6.217476287    0.051006427
  "_id"      "soto-kudus%2C-soto-ayam-%26amp%3B-nasi-pindang_automall-indonesia_-6.23_106.81",  106.8096431 -6.225898946    0.053567221
  "_id"      "soto-kudus%2C-soto-ayam-%26amp%3B-nasi-pindang_menara-mulia_-6.22_106.82",    106.81656   -6.224232983    0.057448344
  "_id"      "nasi-gule-gandaria__-6.24_106.80",    106.795285  -6.244444863    0.061592999
  "_id"      "nasi-soto-monggo-mampir__-6.24_106.80",   106.7971516 -6.244479441    0.062329244
  "_id"      "nasi-soto-ayam-\"pak-min\"__-6.24_106.82",    106.8151546 -6.236743573    0.065276161
  "_id"      "nasi-soto-ayam-pak-min---santa__-6.24_106.81",    106.812959  -6.239508   0.066035611
  "_id"      "soto-mie-nasi-bogor__-6.23_106.83",   106.8322349 -6.234845139    0.076251787
  "_id"      "nasi-uduk-soto-ayam__-6.24_106.87",   106.8693781 -6.239089942    0.109671831
  "_id"      "soto-ayam-%2F-nasi-uduk-betawi__-6.28_106.71",    106.714092  -6.282785   0.112097201
  "_id"      "soto-minang-roda-jaya_ruko-tongkol-indah_-6.12_106.89",   106.889044  -6.119294471    0.13417281
  "_id"      "nasi-bebek-dan-soto-mas-muchlis_summarecon-kelapa-gading_-6.16_106.91",   106.9059021 -6.156281135    0.136471939
  "_id"      "nasi-liwet-%26-soto-kwali-kalimalang__-6.25_106.93",  106.9338112 -6.248527508    0.172293693
  "_id"      "soto-ayam-nasi-rames__-6.88_107.58",  107.5751638 -6.881692483    1.058802838
  "_id"      "nasi-liwet-soto-solo_rumah-mode_-6.88_107.60",    107.5998616 -6.882452292    1.078123028
  "_id"      "nasi-soto-ayam-madura__-6.91_107.57", 107.5749707 -6.912900474    1.079160684
  "_id"      "nasi-soto-mie__-6.89_107.60", 107.5969434 -6.890355658    1.080954023
  "_id"      "nasi-rames-soto-bandung-enjoi__-6.89_107.60", 107.5970721 -6.890504777    1.081148114
  "_id"      "nasi-soto-ayam__-6.91_107.58",    107.5769877 -6.913560825    1.081099449
  "_id"      "nasi-soto-ayam__-6.91_107.60",    107.5977552 -6.90656    1.092061283
  "_id"      "nasi-soto-ayam-madura__-6.89_107.62", 107.6157832 -6.888615935    1.094281476
  "_id"      "nasi-goreng-soto-ayam__-6.90_107.61", 107.6093245 -6.89662571 1.094431917
  "_id"      "nasi-soto-gulai-kambing__-6.90_107.61",   107.6090455 -6.900715755    1.096845722
  "_id"      "putra-bengawan-nasi-goreng-%26-soto__-6.89_107.62",   107.617187  -6.891298   1.097063729
  "_id"      "nasi-soto-ayam__-6.90_107.61",    107.6088095 -6.901163102    1.096953691
  "_id"      "nasi-uduk-%26amp%3B-soto-kikil-cak-khohar__-6.89_107.61", 107.6144958 -6.894765295    1.097201996
  "_id"      "nasi-soto-ayam__-6.90_107.62",    107.6204395 -6.900453028    1.105389179
  "_id"      "nasi-goreng-soto-ayam__-6.90_107.62", 107.6206326 -6.900303912    1.105442127
  "_id"      "nasi-soto-ayam-madura__-6.91_107.62", 107.6169634 -6.909279174    1.10839237
  "_id"      "nasi-soto_pasar-baru_-6.92_107.61",   107.605226  -6.923423387    1.108717834
  "_id"      "nasi-soto-ayam-madura_pasar-baru_-6.92_107.61",   107.6053333 -6.92348729 1.108840349
  "_id"      "nasi-soto-sarinah__-6.90_107.63", 107.631175  -6.897282   1.111636423
  "_id"      "nasi-uduk-soto__-6.89_107.64",    107.6361465 -6.893636262    1.113187903
  "_id"      "nasi-soto-ayam-madura__-6.91_107.63", 107.629376  -6.910677   1.118767984
  "_id"      "nasi-soto-ayam__-6.91_107.63",    107.629376  -6.910677   1.118767984
  "_id"      "nasi-uduk-soto__-6.94_107.62",    107.6248813 -6.93937772 1.133952371
  "_id"      "nasi-soto-ayam-khas-madura__-6.94_107.63",    107.625749  -6.940099   1.135077548
  "_id"      "nasi-uduk-%26amp%3B-soto__-6.96_107.64",  107.638936  -6.955310213    1.154967917
  "_id"      "nasi-soto-ayam_ruko-metro-trade-center_-6.94_107.66", 107.6600504 -6.940208438    1.161142923
  "_id"      "nasi-soto-ayam-khas-madura__-6.94_107.69",    107.6948118 -6.937141164    1.185994885
  "_id"      "nasi-soto-ayam-khas-madura-cak-nonk__-6.93_107.72",   107.7156472 -6.932668019    1.199509086
  "_id"      "nasi-gandul__-7.43_109.24",   109.2391822 -7.425856643    2.756884824

再次查询查询中的术语

"$maxDistance" : 0.053980478460939611

去图。

顺便说一句$ maxDistance是DEFINETLY正确使用的。减少它确实会导致较少的结果。问题似乎来自这样一个事实，即mongodb用于计算距离的公式是不准确的。

Answer 1

我回复了你在stackexchange上发表的同一篇文章： https://dba.stackexchange.com/questions/23869/nearsphere-returns-too-many-data-what-am-i-missing-am-i-wrong-is-it-a-bug-d

这有帮助吗？

谢谢，安德鲁

$ nearSphere返回太多数据

1 个答案: