使用连接字段的结果更新文档

本文介绍了使用连接字段的结果更新文档的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

考虑一个包含以下文件的集合

Consider a collection with the following documents

{ "_id" : "aaaaaaaaaaaa", "title" : "Hello, World!", "date" : "Thursday, November 12, 2015", "time" : "9:30 AM", "endtime" : "11:30 AM" }, { "_id" : "bbbbbbbbbbbb", "title" : "To B or not to B", "date" : "Thursday, November 12, 2015", "time" : "10:30 AM", "endtime" : "11:00 AM" }, { "_id" : "cccccccccccc", "title" : "Family Time", "date" : "Thursday, November 12, 2015", "time" : "10:30 AM", "endtime" : "12:00 PM" }

在这个简化的输出中，我有一些事件已经将它们作为字符串输入的开始时间，结束时间和日期。如何使用使用现有数据的 update（）中的字段计算新的正确形成的Date（） - 可以查询的类型数据。

In this simplified output, I have events that have had their start times, ending times, and dates all entered in as strings. How can I use fields in an update() that use the existing data to calculate new properly formed Date()-type data that I can actually query.

以下工作用于创建新的iso_start字段

The following works to create a new "iso_start" field

db.events.update（{} ，{$ set：{iso_start：Date（）}}，{multi：true}）

我想像我将能够构建一种类似的更新选择

I imagined I would be able to build a sort of update-select like so

db.events.update（{}，{$ set：{iso_start：Date（date + + time}}，{multi：true}）和 db.events.update（{}，{$ set：{iso_end：Date（date +时间）}}，{multi：true}）

但是我收到错误date is not defined。

but I get the error "date is not defined."

更新： this.date 和 this.time 使未定义的错误离开，但插入的日期是当前的日期时间。我尝试写新的Date（），但插入的日期是ISODate（0NaN-NaN NaNTNaN：NaN：NaNZ）

Update: this.date and this.time made the not defined error go away, however the dates inserted were for the present datetime. I tried writing new Date() but then the date inserted was ISODate("0NaN-NaN-NaNTNaN:NaN:NaNZ")

推荐答案

您需要使用 .aggregate（） 方法，它提供对聚合管道的访问。

You need use the .aggregate() method which provides access to the to the aggregation pipelines.

在您的 $项目中 阶段您需要使用 $ concat 操作符连接您的字段。

In your $project stage you need to use the $concat operator to concatenate your field.

然后，您可以使用聚合结果使用bulk操作效率

You can then use your aggregation result to update your collection using "bulk" operations for efficiency

var bulk = db.events.initializeOrderedBulkOp(); var count = 0; db.events.aggregate([ { "$project": { "iso_start": { "$concat": [ "$date", " ", "$time" ] }, "iso_end": { "$concat": [ "$date", " ", "$endtime" ] } }} ]).forEach(function(doc) { bulk.find({'_id': doc._id}).updateOne({ "$set": { "iso_start": new Date(doc.iso_start), "iso_end": new Date(doc.iso_end) } }); count++; if(count % 200 === 0) { // update per 200 operations and re-init bulk.execute(); bulk = db.events.initializeOrderedBulkOp(); } }) // Clean up queues if(count > 0) bulk.execute();

此操作后，您的文档如下所示：

After this operation your documents look like this:

{ "_id" : "aaaaaaaaaaaa", "title" : "Hello, World!", "date" : "Thursday, November 12, 2015", "time" : "9:30 AM", "endtime" : "11:30 AM", "iso_start" : ISODate("2015-11-12T06:30:00Z"), "iso_end" : ISODate("2015-11-12T08:30:00Z") } { "_id" : "bbbbbbbbbbbb", "title" : "To B or not to B", "date" : "Thursday, November 12, 2015", "time" : "10:30 AM", "endtime" : "11:00 AM", "iso_start" : ISODate("2015-11-12T07:30:00Z"), "iso_end" : ISODate("2015-11-12T08:00:00Z") }

这不是故事的结尾，因为批量 API和他的相关方法在即将发布的版本（3.2版本）中被废弃，因此从该版本开始，我们将需要使用 db.collection.bulkWrite（） 方法。

That is not the end of the story because the "Bulk" API and his associated methods are deprecated in the forthcoming release (version 3.2 ) thus from that version we will need to use the db.collection.bulkWrite() method.

var operations = []; db.events.aggregate([ { "$project": { "iso_start": { "$concat": [ "$date", " ", "$time" ] }, "iso_end": { "$concat": [ "$date", " ", "$endtime" ] } }} ]).forEach(function(doc) { var operation = { updateOne: { filter: { "_id": doc._id }, update: { "$set": { "iso_start": new Date(doc.iso_start), "iso_end": new Date(doc.iso_end) } } } }; operations.push(operation); }) operations.push({ ordered: true, writeConcern: { w: "majority", wtimeout: 5000 } }); db.events.bulkWrite(operations)