我如何(在MongoDB)结合数据从多个集合到一个集合?
我可以使用地图减少，如果是，然后如何?
我非常感谢一些例子，因为我是一个新手。
当前回答
MongoDB 3.2现在允许通过$lookup聚合阶段将多个集合中的数据合并为一个集合。作为一个实际的例子，假设您有关于书籍的数据，分为两个不同的集合。
第一种藏书，称为书籍，有以下资料:
{
"isbn": "978-3-16-148410-0",
"title": "Some cool book",
"author": "John Doe"
}
{
"isbn": "978-3-16-148999-9",
"title": "Another awesome book",
"author": "Jane Roe"
}
第二个集合名为books_selling_data，包含以下数据:
{
"_id": ObjectId("56e31bcf76cdf52e541d9d26"),
"isbn": "978-3-16-148410-0",
"copies_sold": 12500
}
{
"_id": ObjectId("56e31ce076cdf52e541d9d28"),
"isbn": "978-3-16-148999-9",
"copies_sold": 720050
}
{
"_id": ObjectId("56e31ce076cdf52e541d9d29"),
"isbn": "978-3-16-148999-9",
"copies_sold": 1000
}
要合并这两个集合，只需按以下方式使用$lookup:
db.books.aggregate([{
$lookup: {
from: "books_selling_data",
localField: "isbn",
foreignField: "isbn",
as: "copies_sold"
}
}])
在此聚合之后，图书集合将看起来如下所示:
{
"isbn": "978-3-16-148410-0",
"title": "Some cool book",
"author": "John Doe",
"copies_sold": [
{
"_id": ObjectId("56e31bcf76cdf52e541d9d26"),
"isbn": "978-3-16-148410-0",
"copies_sold": 12500
}
]
}
{
"isbn": "978-3-16-148999-9",
"title": "Another awesome book",
"author": "Jane Roe",
"copies_sold": [
{
"_id": ObjectId("56e31ce076cdf52e541d9d28"),
"isbn": "978-3-16-148999-9",
"copies_sold": 720050
},
{
"_id": ObjectId("56e31ce076cdf52e541d9d28"),
"isbn": "978-3-16-148999-9",
"copies_sold": 1000
}
]
}
有几件事值得注意:
“from”集合(在本例中为books_selling_data)不能被分片。 “as”字段将是一个数组，如上面的例子所示。 $lookup stage上的"localField"和"foreignField"选项如果在各自的集合中不存在，出于匹配目的将被视为空($lookup文档中有一个完美的例子)。
因此，作为结论，如果您想合并两个集合，在这种情况下，有一个平坦的copies_sold字段，其中包含售出的总副本，您将不得不多做一些工作，可能会使用一个中间集合，然后$out到最终集合。
其他回答
Mongorestore有这样一个特性，即在数据库中已经存在的数据之上追加数据，所以这个行为可以用于组合两个集合:
mongodump文物 collection2.rename(文物) mongorestore
还没有尝试过，但它可能比map/reduce方法执行得更快。
代码片段。礼貌-关于堆栈溢出的多个帖子，包括这一篇。
db.cust.drop();
db.zip.drop();
db.cust.insert({cust_id:1, zip_id: 101});
db.cust.insert({cust_id:2, zip_id: 101});
db.cust.insert({cust_id:3, zip_id: 101});
db.cust.insert({cust_id:4, zip_id: 102});
db.cust.insert({cust_id:5, zip_id: 102});
db.zip.insert({zip_id:101, zip_cd:'AAA'});
db.zip.insert({zip_id:102, zip_cd:'BBB'});
db.zip.insert({zip_id:103, zip_cd:'CCC'});
mapCust = function() {
var values = {
cust_id: this.cust_id
};
emit(this.zip_id, values);
};
mapZip = function() {
var values = {
zip_cd: this.zip_cd
};
emit(this.zip_id, values);
};
reduceCustZip = function(k, values) {
var result = {};
values.forEach(function(value) {
var field;
if ("cust_id" in value) {
if (!("cust_ids" in result)) {
result.cust_ids = [];
}
result.cust_ids.push(value);
} else {
for (field in value) {
if (value.hasOwnProperty(field) ) {
result[field] = value[field];
}
};
}
});
return result;
};
db.cust_zip.drop();
db.cust.mapReduce(mapCust, reduceCustZip, {"out": {"reduce": "cust_zip"}});
db.zip.mapReduce(mapZip, reduceCustZip, {"out": {"reduce": "cust_zip"}});
db.cust_zip.find();
mapCZ = function() {
var that = this;
if ("cust_ids" in this.value) {
this.value.cust_ids.forEach(function(value) {
emit(value.cust_id, {
zip_id: that._id,
zip_cd: that.value.zip_cd
});
});
}
};
reduceCZ = function(k, values) {
var result = {};
values.forEach(function(value) {
var field;
for (field in value) {
if (value.hasOwnProperty(field)) {
result[field] = value[field];
}
}
});
return result;
};
db.cust_zip_joined.drop();
db.cust_zip.mapReduce(mapCZ, reduceCZ, {"out": "cust_zip_joined"});
db.cust_zip_joined.find().pretty();
var flattenMRCollection=function(dbName,collectionName) {
var collection=db.getSiblingDB(dbName)[collectionName];
var i=0;
var bulk=collection.initializeUnorderedBulkOp();
collection.find({ value: { $exists: true } }).addOption(16).forEach(function(result) {
print((++i));
//collection.update({_id: result._id},result.value);
bulk.find({_id: result._id}).replaceOne(result.value);
if(i%1000==0)
{
print("Executing bulk...");
bulk.execute();
bulk=collection.initializeUnorderedBulkOp();
}
});
bulk.execute();
};
flattenMRCollection("mydb","cust_zip_joined");
db.cust_zip_joined.find().pretty();
非常基本的$lookup示例。
db.getCollection('users').aggregate([
{
$lookup: {
from: "userinfo",
localField: "userId",
foreignField: "userId",
as: "userInfoData"
}
},
{
$lookup: {
from: "userrole",
localField: "userId",
foreignField: "userId",
as: "userRoleData"
}
},
{ $unwind: { path: "$userInfoData", preserveNullAndEmptyArrays: true }},
{ $unwind: { path: "$userRoleData", preserveNullAndEmptyArrays: true }}
])
这里用到了
{ $unwind: { path: "$userInfoData", preserveNullAndEmptyArrays: true }},
{ $unwind: { path: "$userRoleData", preserveNullAndEmptyArrays: true }}
而不是
{ $unwind:"$userRoleData"}
{ $unwind:"$userRoleData"}
因为{$unwind:"$userRoleData"}如果在$lookup中没有找到匹配的记录，将返回空或0结果。
MongoDB 3.2现在允许通过$lookup聚合阶段将多个集合中的数据合并为一个集合。作为一个实际的例子，假设您有关于书籍的数据，分为两个不同的集合。
第一种藏书，称为书籍，有以下资料:
{
"isbn": "978-3-16-148410-0",
"title": "Some cool book",
"author": "John Doe"
}
{
"isbn": "978-3-16-148999-9",
"title": "Another awesome book",
"author": "Jane Roe"
}
第二个集合名为books_selling_data，包含以下数据:
{
"_id": ObjectId("56e31bcf76cdf52e541d9d26"),
"isbn": "978-3-16-148410-0",
"copies_sold": 12500
}
{
"_id": ObjectId("56e31ce076cdf52e541d9d28"),
"isbn": "978-3-16-148999-9",
"copies_sold": 720050
}
{
"_id": ObjectId("56e31ce076cdf52e541d9d29"),
"isbn": "978-3-16-148999-9",
"copies_sold": 1000
}
要合并这两个集合，只需按以下方式使用$lookup:
db.books.aggregate([{
$lookup: {
from: "books_selling_data",
localField: "isbn",
foreignField: "isbn",
as: "copies_sold"
}
}])
在此聚合之后，图书集合将看起来如下所示:
{
"isbn": "978-3-16-148410-0",
"title": "Some cool book",
"author": "John Doe",
"copies_sold": [
{
"_id": ObjectId("56e31bcf76cdf52e541d9d26"),
"isbn": "978-3-16-148410-0",
"copies_sold": 12500
}
]
}
{
"isbn": "978-3-16-148999-9",
"title": "Another awesome book",
"author": "Jane Roe",
"copies_sold": [
{
"_id": ObjectId("56e31ce076cdf52e541d9d28"),
"isbn": "978-3-16-148999-9",
"copies_sold": 720050
},
{
"_id": ObjectId("56e31ce076cdf52e541d9d28"),
"isbn": "978-3-16-148999-9",
"copies_sold": 1000
}
]
}
有几件事值得注意:
“from”集合(在本例中为books_selling_data)不能被分片。 “as”字段将是一个数组，如上面的例子所示。 $lookup stage上的"localField"和"foreignField"选项如果在各自的集合中不存在，出于匹配目的将被视为空($lookup文档中有一个完美的例子)。
因此，作为结论，如果您想合并两个集合，在这种情况下，有一个平坦的copies_sold字段，其中包含售出的总副本，您将不得不多做一些工作，可能会使用一个中间集合，然后$out到最终集合。
对聚合中的多个集合使用多个$查找
查询:
db.getCollection('servicelocations').aggregate([
{
$match: {
serviceLocationId: {
$in: ["36728"]
}
}
},
{
$lookup: {
from: "orders",
localField: "serviceLocationId",
foreignField: "serviceLocationId",
as: "orders"
}
},
{
$lookup: {
from: "timewindowtypes",
localField: "timeWindow.timeWindowTypeId",
foreignField: "timeWindowTypeId",
as: "timeWindow"
}
},
{
$lookup: {
from: "servicetimetypes",
localField: "serviceTimeTypeId",
foreignField: "serviceTimeTypeId",
as: "serviceTime"
}
},
{
$unwind: "$orders"
},
{
$unwind: "$serviceTime"
},
{
$limit: 14
}
])
结果:
{
"_id" : ObjectId("59c3ac4bb7799c90ebb3279b"),
"serviceLocationId" : "36728",
"regionId" : 1.0,
"zoneId" : "DXBZONE1",
"description" : "AL HALLAB REST EMIRATES MALL",
"locationPriority" : 1.0,
"accountTypeId" : 1.0,
"locationType" : "SERVICELOCATION",
"location" : {
"makani" : "",
"lat" : 25.119035,
"lng" : 55.198694
},
"deliveryDays" : "MTWRFSU",
"timeWindow" : [
{
"_id" : ObjectId("59c3b0a3b7799c90ebb32cde"),
"timeWindowTypeId" : "1",
"Description" : "MORNING",
"timeWindow" : {
"openTime" : "06:00",
"closeTime" : "08:00"
},
"accountId" : 1.0
},
{
"_id" : ObjectId("59c3b0a3b7799c90ebb32cdf"),
"timeWindowTypeId" : "1",
"Description" : "MORNING",
"timeWindow" : {
"openTime" : "09:00",
"closeTime" : "10:00"
},
"accountId" : 1.0
},
{
"_id" : ObjectId("59c3b0a3b7799c90ebb32ce0"),
"timeWindowTypeId" : "1",
"Description" : "MORNING",
"timeWindow" : {
"openTime" : "10:30",
"closeTime" : "11:30"
},
"accountId" : 1.0
}
],
"address1" : "",
"address2" : "",
"phone" : "",
"city" : "",
"county" : "",
"state" : "",
"country" : "",
"zipcode" : "",
"imageUrl" : "",
"contact" : {
"name" : "",
"email" : ""
},
"status" : "ACTIVE",
"createdBy" : "",
"updatedBy" : "",
"updateDate" : "",
"accountId" : 1.0,
"serviceTimeTypeId" : "1",
"orders" : [
{
"_id" : ObjectId("59c3b291f251c77f15790f92"),
"orderId" : "AQ18O1704264",
"serviceLocationId" : "36728",
"orderNo" : "AQ18O1704264",
"orderDate" : "18-Sep-17",
"description" : "AQ18O1704264",
"serviceType" : "Delivery",
"orderSource" : "Import",
"takenBy" : "KARIM",
"plannedDeliveryDate" : ISODate("2017-08-26T00:00:00.000Z"),
"plannedDeliveryTime" : "",
"actualDeliveryDate" : "",
"actualDeliveryTime" : "",
"deliveredBy" : "",
"size1" : 296.0,
"size2" : 3573.355,
"size3" : 240.811,
"jobPriority" : 1.0,
"cancelReason" : "",
"cancelDate" : "",
"cancelBy" : "",
"reasonCode" : "",
"reasonText" : "",
"status" : "",
"lineItems" : [
{
"ItemId" : "BNWB020",
"size1" : 15.0,
"size2" : 78.6,
"size3" : 6.0
},
{
"ItemId" : "BNWB021",
"size1" : 20.0,
"size2" : 252.0,
"size3" : 11.538
},
{
"ItemId" : "BNWB023",
"size1" : 15.0,
"size2" : 285.0,
"size3" : 16.071
},
{
"ItemId" : "CPMW112",
"size1" : 3.0,
"size2" : 25.38,
"size3" : 1.731
},
{
"ItemId" : "MMGW001",
"size1" : 25.0,
"size2" : 464.375,
"size3" : 46.875
},
{
"ItemId" : "MMNB218",
"size1" : 50.0,
"size2" : 920.0,
"size3" : 60.0
},
{
"ItemId" : "MMNB219",
"size1" : 50.0,
"size2" : 630.0,
"size3" : 40.0
},
{
"ItemId" : "MMNB220",
"size1" : 50.0,
"size2" : 416.0,
"size3" : 28.846
},
{
"ItemId" : "MMNB270",
"size1" : 50.0,
"size2" : 262.0,
"size3" : 20.0
},
{
"ItemId" : "MMNB302",
"size1" : 15.0,
"size2" : 195.0,
"size3" : 6.0
},
{
"ItemId" : "MMNB373",
"size1" : 3.0,
"size2" : 45.0,
"size3" : 3.75
}
],
"accountId" : 1.0
},
{
"_id" : ObjectId("59c3b291f251c77f15790f9d"),
"orderId" : "AQ137O1701240",
"serviceLocationId" : "36728",
"orderNo" : "AQ137O1701240",
"orderDate" : "18-Sep-17",
"description" : "AQ137O1701240",
"serviceType" : "Delivery",
"orderSource" : "Import",
"takenBy" : "KARIM",
"plannedDeliveryDate" : ISODate("2017-08-26T00:00:00.000Z"),
"plannedDeliveryTime" : "",
"actualDeliveryDate" : "",
"actualDeliveryTime" : "",
"deliveredBy" : "",
"size1" : 28.0,
"size2" : 520.11,
"size3" : 52.5,
"jobPriority" : 1.0,
"cancelReason" : "",
"cancelDate" : "",
"cancelBy" : "",
"reasonCode" : "",
"reasonText" : "",
"status" : "",
"lineItems" : [
{
"ItemId" : "MMGW001",
"size1" : 25.0,
"size2" : 464.38,
"size3" : 46.875
},
{
"ItemId" : "MMGW001-F1",
"size1" : 3.0,
"size2" : 55.73,
"size3" : 5.625
}
],
"accountId" : 1.0
},
{
"_id" : ObjectId("59c3b291f251c77f15790fd8"),
"orderId" : "AQ110O1705036",
"serviceLocationId" : "36728",
"orderNo" : "AQ110O1705036",
"orderDate" : "18-Sep-17",
"description" : "AQ110O1705036",
"serviceType" : "Delivery",
"orderSource" : "Import",
"takenBy" : "KARIM",
"plannedDeliveryDate" : ISODate("2017-08-26T00:00:00.000Z"),
"plannedDeliveryTime" : "",
"actualDeliveryDate" : "",
"actualDeliveryTime" : "",
"deliveredBy" : "",
"size1" : 60.0,
"size2" : 1046.0,
"size3" : 68.0,
"jobPriority" : 1.0,
"cancelReason" : "",
"cancelDate" : "",
"cancelBy" : "",
"reasonCode" : "",
"reasonText" : "",
"status" : "",
"lineItems" : [
{
"ItemId" : "MMNB218",
"size1" : 50.0,
"size2" : 920.0,
"size3" : 60.0
},
{
"ItemId" : "MMNB219",
"size1" : 10.0,
"size2" : 126.0,
"size3" : 8.0
}
],
"accountId" : 1.0
}
],
"serviceTime" : {
"_id" : ObjectId("59c3b07cb7799c90ebb32cdc"),
"serviceTimeTypeId" : "1",
"serviceTimeType" : "nohelper",
"description" : "",
"fixedTime" : 30.0,
"variableTime" : 0.0,
"accountId" : 1.0
}
}
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