Querying for a Date Range (Specific Month or Day) in the MongoDB Cookbook has a very good explanation on the matter, but below is something I tried out myself and it seems to work.
items.save({
name: "example",
created_at: ISODate("2010-04-30T00:00:00.000Z")
})
items.find({
created_at: {
$gte: ISODate("2010-04-29T00:00:00.000Z"),
$lt: ISODate("2010-05-01T00:00:00.000Z")
}
})
=> { "_id" : ObjectId("4c0791e2b9ec877893f3363b"), "name" : "example", "created_at" : "Sun May 30 2010 00:00:00 GMT+0300 (EEST)" }
Based on my experiments you will need to serialize your dates into a format that MongoDB supports, because the following gave undesired search results.
items.save({
name: "example",
created_at: "Sun May 30 18.49:00 +0000 2010"
})
items.find({
created_at: {
$gte:"Mon May 30 18:47:00 +0000 2015",
$lt: "Sun May 30 20:40:36 +0000 2010"
}
})
=> { "_id" : ObjectId("4c079123b9ec877893f33638"), "name" : "example", "created_at" : "Sun May 30 18.49:00 +0000 2010" }
In the second example no results were expected, but there was still one gotten. This is because a basic string comparison is done.
The best way to do this is in version 4.2+ which allows using of aggregation pipeline in the update document and the updateOne
, updateMany
or update
collection methods. Note that the latter has been deprecated in most if not all languages drivers.
###MongoDB 4.2+
Version 4.2 also introduced the $set
pipeline stage operator which is an alias for $addFields
. I will use $set
here as it maps with what we are trying to achieve.
db.collection.<update method>(
{},
[
{"$set": {"name": { "$concat": ["$firstName", " ", "$lastName"]}}}
]
)
Note that square brackets in the second argument to the method which define an aggregation pipeline instead of a plain update document. Using a plain document will not work correctly.
###MongoDB 3.4+
In 3.4+ you can use $addFields
and the $out
aggregation pipeline operators.
db.collection.aggregate(
[
{ "$addFields": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}},
{ "$out": "collection" }
]
)
Note that this does not update your collection but instead replace the existing collection or create a new one. Also for update operations that require "type casting" you will need client side processing, and depending on the operation, you may need to use the find()
method instead of the .aggreate()
method.
##MongoDB 3.2 and 3.0
The way we do this is by $project
ing our documents and use the $concat
string aggregation operator to return the concatenated string.
we From there, you then iterate the cursor and use the $set
update operator to add the new field to your documents using bulk operations for maximum efficiency.
###Aggregation query:
var cursor = db.collection.aggregate([
{ "$project": {
"name": { "$concat": [ "$firstName", " ", "$lastName" ] }
}}
])
###MongoDB 3.2 or newer
from this, you need to use the bulkWrite
method.
var requests = [];
cursor.forEach(document => {
requests.push( {
'updateOne': {
'filter': { '_id': document._id },
'update': { '$set': { 'name': document.name } }
}
});
if (requests.length === 500) {
//Execute per 500 operations and re-init
db.collection.bulkWrite(requests);
requests = [];
}
});
if(requests.length > 0) {
db.collection.bulkWrite(requests);
}
###MongoDB 2.6 and 3.0
From this version you need to use the now deprecated Bulk
API and its associated methods.
var bulk = db.collection.initializeUnorderedBulkOp();
var count = 0;
cursor.snapshot().forEach(function(document) {
bulk.find({ '_id': document._id }).updateOne( {
'$set': { 'name': document.name }
});
count++;
if(count%500 === 0) {
// Excecute per 500 operations and re-init
bulk.execute();
bulk = db.collection.initializeUnorderedBulkOp();
}
})
// clean up queues
if(count > 0) {
bulk.execute();
}
###MongoDB 2.4
cursor["result"].forEach(function(document) {
db.collection.update(
{ "_id": document._id },
{ "$set": { "name": document.name } }
);
})
Best Answer
If you also have documents that don't have the key, you can use:
MongoDB don't use indexes if $size is involved, so here is a better solution:
If your property can have invalid values (like
null
boolean
or others) , then you an add an additional check using$types
as proposed in this answer:With mongo >= 3.2:
With mongo < 3.2:
Since MongoDB 2.6 release, you can compare with the operator
$gt
but could lead to unexpected results (you can find a detailled explanation in this answer):