mongoimport -d test -c test——type csv——file SampleCSVFile_119kb.csv——headerline .csv

检查采集数据:—

var collections = db.getCollectionNames(); For (var I = 0;我< collections.length;我+ +) ｛ print('Collection: ' + collections[i]); //打印每个集合的名称 db.getCollection(集合[我]);().forEach (printjson); //然后打印每个元素的json ｝

以上这些答案都很棒。这也是开发一个功能齐全的应用程序的方法。

但是如果你想要快速创建原型，想要在集合不断变化时保持灵活性，以及最小化你早期的代码库，有一种更简单的方法，但很少讨论。

你现在基本上可以放弃蒙古进口了。如果在这里提到这个问题，我可以节省3个小时。让我分享给大家:

Mongodb有一个名为Mongo Compass的GUI，它有csv和json导入功能，只需点击即可开箱即用。它是Mongo生态系统的正式组成部分。在撰写本文时，它是免费的，并且非常适合我的用例。 https://www.mongodb.com/products/compass

You simply get MongoDB compass running on your machine by following the simple installation. A couple of fields for DB connection and authentication directly in the GUI. Import the csv/json file. It took less than a second on a 30KB file to be parsed before user (me) validates. Validate the "type" of each property. Great feature, I could directly mention the property types such as booleans, integers, etc. In my experience, they seem all default to string. You can update before importing. Dates were more finicky and needed special attention on the coding side. One click further the csv is a collection in your mongo db local or on the cloud. Voila!

检查文件末尾是否有空行，否则在某些版本的mongoimport上最后一行将被忽略

奇怪的是，没有人提到——uri flag:

mongoimport --uri connectionString -c questions --type csv --file questions.csv --headerline 

对于3.4版本，请使用以下语法:

mongoimport -u "username" -p "password" -d "test" -c "collections" --type csv --file myCsv.csv --headerline

3天后，我终于靠自己做到了。感谢所有支持我的用户。

您的示例适用于MongoDB 1.6.3和1.7.3。下面的示例是针对1.7.3的。您使用的是旧版本的MongoDB吗?

$ cat > locations.csv
Name,Address,City,State,ZIP
Jane Doe,123 Main St,Whereverville,CA,90210
John Doe,555 Broadway Ave,New York,NY,10010
 ctrl-d
$ mongoimport -d mydb -c things --type csv --file locations.csv --headerline
connected to: 127.0.0.1
imported 3 objects
$ mongo
MongoDB shell version: 1.7.3
connecting to: test
> use mydb
switched to db mydb
> db.things.find()
{ "_id" : ObjectId("4d32a36ed63d057130c08fca"), "Name" : "Jane Doe", "Address" : "123 Main St", "City" : "Whereverville", "State" : "CA", "ZIP" : 90210 }
{ "_id" : ObjectId("4d32a36ed63d057130c08fcb"), "Name" : "John Doe", "Address" : "555 Broadway Ave", "City" : "New York", "State" : "NY", "ZIP" : 10010 }