我是 Mongo 的新手，使用 v3.2。我有 2 个系列，Parent & Child。我想使用 Parent.aggregate 并使用 $lookup 来“加入”Child，然后在 Child 的字段上执行 $text $search 并在父级上执行日期范围搜索。这可能...？
最佳答案
根据已经给出的评论，您确实无法执行 $text搜索 $lookup 的结果因为在第一个流水线阶段以外的任何阶段都没有可用的索引。的确，特别是考虑到您确实希望根据“子”集合的结果进行“加入”，那么搜索“子”确实会更好。
这带来了一个明显的结论，即为了做到这一点，您对具有初始 $text 的“子”集合执行聚合。查询然后 $lookup “ parent ”而不是相反。
作为一个工作示例，仅使用核心驱动程序进行演示:
MongoClient.connect('mongodb://localhost/rlookup',function(err,db) {
if (err) throw err;
var Parent = db.collection('parents');
var Child = db.collection('children');
async.series(
[
// Cleanup
function(callback) {
async.each([Parent,Child],function(coll,callback) {
coll.deleteMany({},callback);
},callback);
},
// Create Index
function(callback) {
Child.createIndex({ "text": "text" },callback);
},
// Create Documents
function(callback) {
async.parallel(
[
function(callback) {
Parent.insertMany(
[
{ "_id": 1, "name": "Parent 1" },
{ "_id": 2, "name": "Parent 2" },
{ "_id": 3, "name": "Parent 3" }
],
callback
);
},
function(callback) {
Child.insertMany(
[
{
"_id": 1,
"parent": 1,
"text": "The little dog laughed to see such fun"
},
{
"_id": 2,
"parent": 1,
"text": "The quick brown fox jumped over the lazy dog"
},
{
"_id": 3,
"parent": 1,
"text": "The dish ran away with the spoon"
},
{
"_id": 4,
"parent": 2,
"text": "Miss muffet on here tuffet"
},
{
"_id": 5,
"parent": 3,
"text": "Lady is a fox"
},
{
"_id": 6,
"parent": 3,
"text": "Every dog has it's day"
}
],
callback
)
}
],
callback
);
},
// Aggregate with $text and $lookup
function(callback) {
Child.aggregate(
[
{ "$match": {
"$text": { "$search": "fox dog" }
}},
{ "$project": {
"parent": 1,
"text": 1,
"score": { "$meta": "textScore" }
}},
{ "$sort": { "score": { "$meta": "textScore" } } },
{ "$lookup": {
"from": "parents",
"localField": "parent",
"foreignField": "_id",
"as": "parent"
}},
{ "$unwind": "$parent" },
{ "$group": {
"_id": "$parent._id",
"name": { "$first": "$parent.name" },
"children": {
"$push": {
"_id": "$_id",
"text": "$text",
"score": "$score"
}
},
"score": { "$sum": "$score" }
}},
{ "$sort": { "score": -1 } }
],
function(err,result) {
console.log(JSON.stringify(result,undefined,2));
callback(err);
}
)
}
],
function(err) {
if (err) throw err;
db.close();
}
);
});
这导致 $text来自每个 Parent 中填充的 Child 查询的匹配项，以及按 "score" 排序:
[
{
"_id": 1,
"name": "Parent 1",
"children": [
{
"_id": 2,
"text": "The quick brown fox jumped over the lazy dog",
"score": 1.1666666666666667
},
{
"_id": 1,
"text": "The little dog laughed to see such fun",
"score": 0.6
}
],
"score": 1.7666666666666666
},
{
"_id": 3,
"name": "Parent 3",
"children": [
{
"_id": 5,
"text": "Lady is a fox",
"score": 0.75
},
{
"_id": 6,
"text": "Every dog has it's day",
"score": 0.6666666666666666
}
],
"score": 1.4166666666666665
}
]
这最终是有意义的，并且比从“父”查询以查找 $lookup 中的所有“子”更有效。然后使用 $match 进行“后过滤”以删除任何不符合条件的“子项”，然后丢弃没有任何匹配项的“父项”。
同样的情况也适用于 mongoose 风格的“引用”，您在“父级”中包含了一个“子级”的“数组”，而不是记录在子级上。因此，只要子项上的 "localField"(在这种情况下为 _id)与父项数组中定义的类型相同，即 "foriegnField" (如果它与 .populate() 一起工作，那将会是这样)那么你仍然会为 $lookup 中的每个“ child ”获得匹配的“ parent ”。结果。
这一切都归结为扭转你的想法并意识到 $text 结果是最重要的，因此“that”是需要启动操作的集合。
这是可能的，但反过来就可以了。
使用 mongoose 样式和父级中引用的子级列表
仅显示父级引用的反向大小写以及日期过滤:
var async = require('async'),
mongoose = require('mongoose'),
Schema = mongoose.Schema;
mongoose.connect('mongodb://localhost/rlookup');
var parentSchema = new Schema({
"_id": Number,
"name": String,
"date": Date,
"children": [{ "type": Number, "ref": "Child" }]
});
var childSchema = new Schema({
"_id": Number,
"text": { "type": String, "index": "text" }
},{ "autoIndex": false });
var Parent = mongoose.model("Parent",parentSchema),
Child = mongoose.model("Child",childSchema);
async.series(
[
function(callback) {
async.each([Parent,Child],function(model,callback) {
model.remove({},callback);
},callback);
},
function(callback) {
Child.ensureIndexes({ "background": false },callback);
},
function(callback) {
async.parallel(
[
function(callback) {
Parent.create([
{
"_id": 1,
"name": "Parent 1",
"date": new Date("2016-02-01"),
"children": [1,2]
},
{
"_id": 2,
"name": "Parent 2",
"date": new Date("2016-02-02"),
"children": [3,4]
},
{
"_id": 3,
"name": "Parent 3",
"date": new Date("2016-02-03"),
"children": [5,6]
},
{
"_id": 4,
"name": "Parent 4",
"date": new Date("2016-01-15"),
"children": [1,2,6]
}
],callback)
},
function(callback) {
Child.create([
{
"_id": 1,
"text": "The little dog laughed to see such fun"
},
{
"_id": 2,
"text": "The quick brown fox jumped over the lazy dog"
},
{
"_id": 3,
"text": "The dish ran awy with the spoon"
},
{
"_id": 4,
"text": "Miss muffet on her tuffet"
},
{
"_id": 5,
"text": "Lady is a fox"
},
{
"_id": 6,
"text": "Every dog has it's day"
}
],callback);
}
],
callback
);
},
function(callback) {
Child.aggregate(
[
{ "$match": {
"$text": { "$search": "fox dog" }
}},
{ "$project": {
"text": 1,
"score": { "$meta": "textScore" }
}},
{ "$sort": { "score": { "$meta": "textScore" } } },
{ "$lookup": {
"from": "parents",
"localField": "_id",
"foreignField": "children",
"as": "parent"
}},
{ "$project": {
"text": 1,
"score": 1,
"parent": {
"$filter": {
"input": "$parent",
"as": "parent",
"cond": {
"$and": [
{ "$gte": [ "$$parent.date", new Date("2016-02-01") ] },
{ "$lt": [ "$$parent.date", new Date("2016-03-01") ] }
]
}
}
}
}},
{ "$unwind": "$parent" },
{ "$group": {
"_id": "$parent._id",
"name": { "$first": "$parent.name" },
"date": { "$first": "$parent.date" },
"children": {
"$push": {
"_id": "$_id",
"text": "$text",
"score": "$score"
}
},
"score": { "$sum": "$score" }
}},
{ "$sort": { "score": -1 } }
],
function(err,result) {
console.log(JSON.stringify(result,undefined,2));
callback(err);
}
)
}
],
function(err) {
if (err) throw err;
mongoose.disconnect();
}
);
输出:
[
{
"_id": 1,
"name": "Parent 1",
"date": "2016-02-01T00:00:00.000Z",
"children": [
{
"_id": 2,
"text": "The quick brown fox jumped over the lazy dog",
"score": 1.1666666666666667
},
{
"_id": 1,
"text": "The little dog laughed to see such fun",
"score": 0.6
}
],
"score": 1.7666666666666666
},
{
"_id": 3,
"name": "Parent 3",
"date": "2016-02-03T00:00:00.000Z",
"children": [
{
"_id": 5,
"text": "Lady is a fox",
"score": 0.75
},
{
"_id": 6,
"text": "Every dog has it's day",
"score": 0.6666666666666666
}
],
"score": 1.4166666666666665
}
]
请注意，由于日期不在 $filter 应用的查询范围内，因此删除了本来排名最高的 “Parent 4” .
关于node.js - 如何通过 $lookup 对 'joined' 集合执行 $text 搜索？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/36345350/