问题描述
我正在尝试使用 Mongoose 在我的集合中的数组中计算字符串的出现次数.我的模式"如下所示:
I'm trying to count the number of occurrences of a string in an array in my collection using Mongoose. My "schema" looks like this:
var ThingSchema = new Schema({
tokens: [ String ]
});
我的目标是获取Thing"集合中的前 10 个令牌",每个文档可以包含多个值.例如:
My objective is to get the top 10 "tokens" in the "Thing" collection, which can contain multiple values per document. For example:
var documentOne = {
_id: ObjectId('50ff1299a6177ef9160007fa')
, tokens: [ 'foo' ]
}
var documentTwo = {
_id: ObjectId('50ff1299a6177ef9160007fb')
, tokens: [ 'foo', 'bar' ]
}
var documentThree = {
_id: ObjectId('50ff1299a6177ef9160007fc')
, tokens: [ 'foo', 'bar', 'baz' ]
}
var documentFour = {
_id: ObjectId('50ff1299a6177ef9160007fd')
, tokens: [ 'foo', 'baz' ]
}
...会给我数据结果:
...would give me data result:
[ foo: 4, bar: 2 baz: 2 ]
我正在考虑为此工具使用 MapReduce 和 Aggregate,但我不确定什么是最佳选择.
I'm considering using MapReduce and Aggregate for this tool, but I'm not certain what is the best option.
推荐答案
啊哈,我找到了解决方案.MongoDB 的 aggregate
框架允许我们在集合上执行一系列任务.特别值得注意的是$unwind
,它将文档中的数组分解为唯一的文档,因此它们可以被分组/计数en masse.
Aha, I've found the solution. MongoDB's aggregate
framework allows us to execute a series of tasks on a collection. Of particular note is $unwind
, which breaks an array in a document into unique documents, so they can be groups / counted en masse.
MongooseJS 在模型上非常容易地公开了这一点.使用上面的示例,如下所示:
MongooseJS exposes this very accessibly on a model. Using the example above, this looks as follows:
Thing.aggregate([
{ $match: { /* Query can go here, if you want to filter results. */ } }
, { $project: { tokens: 1 } } /* select the tokens field as something we want to "send" to the next command in the chain */
, { $unwind: '$tokens' } /* this converts arrays into unique documents for counting */
, { $group: { /* execute 'grouping' */
_id: { token: '$tokens' } /* using the 'token' value as the _id */
, count: { $sum: 1 } /* create a sum value */
}
}
], function(err, topTopics) {
console.log(topTopics);
// [ foo: 4, bar: 2 baz: 2 ]
});
在大约 200,000 条记录的初步测试中,它明显快于 MapReduce,因此扩展性可能更好,但这只是粗略的一瞥.YMMV.
It is noticeably faster than MapReduce in preliminary tests across ~200,000 records, and thus likely scales better, but this is only after a cursory glance. YMMV.
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