我在mongoDB中有几十万个文档需要更新。 以下是集合用户：
中现有文档的示例{
"_id" : "549120bcf5115900124fb6e1",
"user" : "Tom",
"country" : "United Kingdom",
"province" : "North Yorkshire",
"city" : "York",
"organization" : ""
},
{
"_id" : "143184fbf5482260184ac6e2",
"user" : "Jack",
"country" : "Not Listed",
"province" : "",
"city" : "",
"organization" : "United Nations"
},
{
"_id" : "1234567890123456748979",
"user" : "Sarah",
"country" : "Not Listed",
"province" : "",
"city" : "",
"organization" : ""
},
{
"_id" : "98765432411654987654",
"user" : "Mat"
}
每个文档都可以在这些字段中包含值：
以下是来自其他集合国家/地区：
的示例{
"_id" : "123456789",
"key" : "Not Listed",
"uuid" : "ca55b53a-ef5b-43ed-90ed-b857f45ddb6d",
"organization" : [
{
"key" : "United Nations",
"uuid" : "1c4ae4c6-00c5-405d-98fa-ca7cc9edc72a"
},
{
"key" : "FIFA",
"uuid" : "11cfe606-821f-40fb-b1d0-bb7f9abb21dc"
}
],
"province" : [],
},
{
"_id" : "1123465498742",
"key" : "United Kingdom",
"uuid" : "d756e167-25ec-4aa9-b231-4dbf6d4bfce4",
"organization" : [],
"province" : [
{
"key" : "North Yorkshire",
"uuid" : "73d07c77-eba4-4dfa-9ada-e0ba8d8a2d55",
"city" : [
{
"key" : "York",
"uuid" : "80fd18a6-c4eb-4fb9-b591-6cca62319ba7"
},
{
"key" : "Middlesbrough",
"uuid" : "26a277c4-8640-4959-a64a-00f3727975f4"
}
],
},
{
"key" : "Oxfordshire",
"uuid" : "f7b5a570-df42-4520-ba3a-8bdcdd00e7d4",
"city" : [
{
"key" : "Oxford",
"uuid" : "b931865c-a363-4958-b7e7-5503fe674eb0"
},
{
"key" : "Banbury",
"uuid" : "b8d4c63a-75a9-4c3c-a4cd-d315f06a92e0"
}
],
}
]
}
我们的想法是从用户集合中的文档中查找国家/组织/省/市场字段值，并根据的 uuid 值更新它们>国家集合。
所以结果看起来像这样：
{
"_id" : "549120bcf5115900124fb6e1",
"user" : "Tom",
"country" : "d756e167-25ec-4aa9-b231-4dbf6d4bfce4", // uuid of United Kingdom
"province" : "73d07c77-eba4-4dfa-9ada-e0ba8d8a2d55", // uuid of North Yorkshire
"city" : "80fd18a6-c4eb-4fb9-b591-6cca62319ba7", // uuid of York
"state" : ""
},
{
"_id" : "143184fbf5482260184ac6e2",
"user" : "Jack",
"country" : "ca55b53a-ef5b-43ed-90ed-b857f45ddb6d", // uuid of Not Listed
"province" : "",
"city" : "",
"state" : "1c4ae4c6-00c5-405d-98fa-ca7cc9edc72a" // uuid of United Nations
},
{
"_id" : "1234567890123456748979",
"user" : "Sarah",
"country" : "ca55b53a-ef5b-43ed-90ed-b857f45ddb6d", // uuid of Not Listed
"province" : "",
"city" : "",
"state" : ""
},
{
"_id" : "98765432411654987654",
"user" : "Mat"
}
字段的依赖关系如下：
国家＆gt;省＆gt;城市
或者：
国家＆gt;组织
父字段可能存在，但其子字段不存在或为空。
如何使用mongo脚本规则更新这些多维数组？
这是我的尝试，但这是很多 for loop ，并且不确定如何进行mongodb查找/更新/保存部分..有人可以帮助实现吗？
var usrCountry, uuidcountry, usrProvince, uuidprovince, usrOrg, uuidorg, usrCity, uuidcity;
for (var i = 0; i < users.length; i++) {
usrCountry = users[i].country;
usrProvince = users[i].province;
usrOrg = users[i].organization;
usrCity = users[i].city;
for (var j = 0; j < countries.length; j++) {
if (countries[j].key === usrCountry) {
uuidcountry = countries[j].uuid;
console.log('uuidcountry: ', uuidcountry)
if (countries[j].province.length){
for (var k = 0; k < countries[j].province.length; k++) {
if (countries[j].province[k].key === usrProvince){
uuidprovince = countries[j].province[k].uuid;
console.log('uuidprovince', uuidprovince)
for (var l = 0; l < countries[j].province[k].city.length; l++) {
if (countries[j].province[k].city[l].key === usrCity){
uuidcity = countries[j].province[k].city[l].uuid
console.log('uuidcity: ', uuidcity)
}
}
}
}
}
}
}
}
答案 0 :(得分：1)
您可以尝试使用聚合管道执行此操作，并使用该信息进行更新
db.u.aggregate(
[
{
$lookup: {
from : "c",
localField : "country",
foreignField : "key",
as : "countryInfo"
}
},
{
$project: {
"_id" : 1,
"user" : 1,
"province" : 1,
"country" : 1,
"city" : 1,
"organization" : 1,
"country_uuid" : {$arrayElemAt : ["$countryInfo.uuid",0]},
"province_uuid" : { $arrayElemAt : [{ $map : { input : { $filter : { input : {$arrayElemAt : ["$countryInfo.province" ,0 ]} , as : "pro", cond : { $eq : [ "$$pro.key", "$province" ] } } } , as : "pr", in : "$$pr.uuid" } }, 0 ] },
"city_uuid" : {$arrayElemAt : [{$map : { input : { $arrayElemAt : [ {$filter : { input : { $map : { input : { $arrayElemAt : ["$countryInfo.province.city" ,0 ] }, as : "ct", in : { $filter : { input : "$$ct" , as : "ctyy", cond : { $eq : ["$$ctyy.key", "$city"] } } } } }, as : "o", cond : {$ne : [ {$size : "$$o"} , 0 ] } } } , 0]}, as : "o", in :"$$o.uuid"}}, 0]}
}
}
]
)
结果
> db.u.aggregate( [ { $lookup: { from : "c", localField : "country", foreignField : "key", as : "countryInfo" } }, { $project: { "_id" : 1, "user" : 1, "province" : 1, "country" : 1, "city" : 1, "organization" : 1, "country_uuid" : {$arrayElemAt : ["$countryInfo.uuid",0]}, "province_uuid" : { $arrayElemAt : [{ $map : { input : { $filter : { input : {$arrayElemAt : ["$countryInfo.province" ,0 ]} , as : "pro", cond : { $eq : [ "$$pro.key", "$province" ] } } } , as : "pr", in : "$$pr.uuid" } }, 0 ] }, "city_uuid" : {$arrayElemAt : [{$map : { input : { $arrayElemAt : [ {$filter : { input : { $map : { input : { $arrayElemAt : ["$countryInfo.province.city" ,0 ] }, as : "ct", in : { $filter : { input : "$$ct" , as : "ctyy", cond : { $eq : ["$$ctyy.key", "$city"] } } } } }, as : "o", cond : {$ne : [ {$size : "$$o"} , 0 ] } } } , 0]}, as : "o", in :"$$o.uuid"}}, 0]} } } ] ).pretty()
{
"_id" : "549120bcf5115900124fb6e1",
"user" : "Tom",
"country" : "United Kingdom",
"province" : "North Yorkshire",
"city" : "York",
"organization" : "",
"country_uuid" : "d756e167-25ec-4aa9-b231-4dbf6d4bfce4",
"province_uuid" : "73d07c77-eba4-4dfa-9ada-e0ba8d8a2d55",
"city_uuid" : "80fd18a6-c4eb-4fb9-b591-6cca62319ba7"
}