Add existing fields to nested schema - mongodb

Question

I have documents in my db with schema:
var MySchema = new Schema({
Street: { type: String },
Age: { type: Number, default: null },
Date: { type: Date },
Stuff: [
{
_id:false,
ThisDate: { type: Date },
ThisStreet: { type: String }
}]
});
Right now it is (Stuff is empty):
db.person.findOne()
{
Street: 'TheStreet',
Age: 23,
Date: ISODate("2016-02-19T00:00:00.000Z"),
Stuff: []
}
I then want to update all documents. What I want to do is to move Street and Date fields into Stuff array and delete Street and Date fields from schema.
Like this:
db.person.findOne()
{
Age: 23,
Stuff : [
{
ThisDate : ISODate("2016-02-19T00:00:00.000Z"),
ThisStreet : "TheStreet"
}
]
}
How could I achieve this?
Best Regards

Answer 1

Since this is a "one off" operation I would do it in the shell rather than use any other framework.
For MongoDB 3.2.x releases and greater use, bulkWrite():
var ops = [];
db.person.find({
"Street": { "$exists": true },
"Date": { "$exists": true }
}).forEach(function(doc) {
ops.push({
"updateOne": {
"filter": { "_id": doc._id },
"update": {
"$unset": {
"Street": "",
"Date": ""
},
"$set": {
"Stuff": [{
"ThisDate": doc.Date,
"ThisStreet": doc.Street
}]
}
}
}
});
if ( ops.length == 1000 ) {
db.person.bulkWrite(ops);
ops = [];
}
})
if ( ops.length > 0 )
db.person.bulkWrite(ops);
Or for MongoDB 2.6.x and 3.0.x releases use this version of Bulk operations:
var bulk = db.person.initializeUnorderedBulkOp(),
count = 0;
db.person.find({
"Street": { "$exists": true },
"Date": { "$exists": true }
}).forEach(function(doc) {
bulk.find({ "_id": doc._id }).updateOne({
"$unset": {
"Street": "",
"Date": ""
},
"$set": {
"Stuff": [{
"ThisDate": doc.Date,
"ThisStreet": doc.Street
}]
}
});
if ( count % 1000 == 0 ) {
bulk.execute();
bulk = db.person.initializeUnorderedBulkOp();
}
});
if ( count % 1000 != 0 )
bulk.execute();
Bottom line is that you need to iterate the documents in the collection and write them back with the re-arranged content "one by one". At least the Bulk operations API in use in both cases will reduce the load of writing and responding with the server to only one in every 1000 documents in the collection to process.
Also, rather than rewriting the whole document you are using $unset to remove the desired fields and $set to write "just" the data you want
Working example
db.person.insert(
{
"Street": 'TheStreet',
"Age": 23,
"Date": ISODate("2016-02-19T00:00:00.000Z"),
"Stuff": []
}
)
Then after running either pdate above the result is:
{
"_id" : ObjectId("56e607c1ca8e7e3519b4ce93"),
"Age" : 23,
"Stuff" : [
{
"ThisDate" : ISODate("2016-02-19T00:00:00Z"),
"ThisStreet" : "TheStreet"
}
]
}

Answer 2

I'd suggest you to transform document using aggregation framework and update as described in code snippet below
db.person.aggregate([
{$project:{Age:1, Stuff:[{Date:"$Date", Street:"$Street"}]}}
]).forEach(function(o){
var id = o._id;
delete o._id;
db.person.update({_id:id, Street:{$exists: true}},o);
});
After successful execution, you document or documents should look like
{
"_id" : ObjectId("56e2cd45792861e14df1f0a9"),
"Age" : 23.0,
"Stuff" : [
{
"Date" : ISODate("2016-02-19T00:00:00.000+0000"),
"Street" : "TheStreet"
}
]
}