I'm trying to update an existing document in a MongoDb. There are many explanations how to do this if you want to update or add key/value pairs on the first level. But in my use-case, I need to create with the first updateOne (with upsert option set) a document with the following structure:
{
"_id" : "1234",
"raw" : {
"meas" : {
"meas1" : {
"data" : "blabla"
}
}
}
}
In the second command, I need to add - in the same document - a "meas2" field at the level of "meas1". My desired output is:
{
"_id" : "1234",
"raw" : {
"meas" : {
"meas1" : {
"data" : "blabla"
},
"meas2" : {
"data" : "foo"
}
}
}
}
I played with statements like
updateOne({"_id":"1234"},{$set:{"raw":{"meas":{"meas2":{"data":"foo"}}}}}, {"upsert":true})
and also with $push, both variants with insert - here only the document and also insertOne, but nothing produces the desired output. Is there a MongoDb expert who could give a hint ? ... I'm sure this functionality exists... Thanks in advance!
When you update {$set: {"raw":{"meas":{"meas2":{"data":"foo"}}}} you're not adding "mesa2" to "meas" but rather you're overriting "raw" completely.
In order to change / add one field in a document refer to it with dot notations.
The command you want is updateOne({"_id": "1234"}, {$set: {"raw.meas.mesa2": { "data" : "foo" }}}, {"upsert":"true"})
You need to understand the below concept first
Set Fields in Embedded Documents, with details document check at official documentation of mongo
For your problem, just look at the below execution on the mongo shell:
> db.st4.insert({
... "_id" : "1234",
... "raw" : {
... "meas" : {
... "meas1" : {
... "data" : "blabla"
... }
... }
... }
... })
WriteResult({ "nInserted" : 1 })
> db.st4.find()
{ "_id" : "1234", "raw" : { "meas" : { "meas1" : { "data" : "blabla" } } } }
>
> // Below query will replace the raw document with {"meas":{"meas2":{"data":"foo"}}}, will not add
> //db.st4.updateOne({"_id":"1234"},{$set:{"raw":{"meas":{"meas2":{"data":"foo"}}}}}, {"upsert":true})
>// By using the dot operator, you actually write the values inside the documents i.e you are replacing or adding at raw.meas.mesa2 i.e inside the document of mesa2.
> db.st4.updateOne({"_id":"1234"},{$set: {"raw.meas.mesa2": { "data" : "foo" }}}, {"upsert":"true"})
{ "acknowledged" : true, "matchedCount" : 1, "modifiedCount" : 1 }
> db.st4.find().pretty()
{
"_id" : "1234",
"raw" : {
"meas" : {
"meas1" : {
"data" : "blabla"
},
"mesa2" : {
"data" : "foo"
}
}
}
}
>
Related
Have a field of type "String" that contain representation of an object/document
" {"a":35,b:[1,2,3,4]}"
I know is a strange construct but i can't change it.
my goal would be to extract for example the value of "a".
As the document represented by the string are nested and repeated a regex doesnt fit.
So how can i convert in a mongo db aggregation/query this String to object so that i can process it in a following aggregation step?
(could extract string with python make a dict and extract infos, but i'd like to stay inside the aggregation pipeline and so having better performance)
In 4.4 this works
db.target.aggregate([{$project: {
X: "$AD_GRAPHIC",
Y : {
$function : {
body: function(jsonString) {
return JSON.parse(jsonString)
},
args: [ "$AD_GRAPHIC"],
lang: "js"
}
}
}
}])
Basically use the $function operator to invoke the JSON parser. (assumes you have enabled Javascript)
Results
{ "_id" : ObjectId("60093dc8f2c829000e38a8d0"), "X" : "{\"alias\":\"MEDIA_DIR\",\"path\":\"modem.jpg\"}", "Y" : { "alias" : "MEDIA_DIR", "path" : "modem.jpg" } }
{ "_id" : ObjectId("60093dc8f2c829000e38a8d1"), "X" : "{\"alias\":\"MEDIA_DIR\",\"path\":\"monitor.jpg\"}", "Y" : { "alias" : "MEDIA_DIR", "path" : "monitor.jpg" } }
{ "_id" : ObjectId("60093dc8f2c829000e38a8d2"), "X" : "{\"alias\":\"MEDIA_DIR\",\"path\":\"mousepad.jpg\"}", "Y" : { "alias" : "MEDIA_DIR", "path" : "mousepad.jpg" } }
{ "_id" : ObjectId("60093dc8f2c829000e38a8d3"), "X" : "{\"alias\":\"MEDIA_DIR\",\"path\":\"keyboard.jpg\"}", "Y" : { "alias" : "MEDIA_DIR", "path" : "keyboard.jpg" } }
>
There's no native way in the MongoDB engine to parse a blob of JSON from a field. However, I'd recommend just doing it client-side in your language of choice and then if required save it back.
Alternatively, if your data is too big and still needs to aggregate it you could use regex and project out the required fields from the JSON to then use them later to filter etc...
For example if we insert the following document:
> db.test.insertOne({ name: 'test', blob: '{"a":35,b:[1,2,3,4]}' })
{
"acknowledged" : true,
"insertedId" : ObjectId("5ed9fe21b5d91941c9e85cdb")
}
We can then just project out the array with some regex:
db.test.aggregate([
{ $addFields: { b: { $regexFind: { input: "$blob", regex: /\[(((\d+,*))+)\]/ } } } },
{ $addFields: { b: { $split: [ { $arrayElemAt: [ "$b.captures", 0 ] }, "," ] } } }
]);
{
"_id" : ObjectId("5ed9fe21b5d91941c9e85cdb"),
"name" : "test",
"blob" : "{\"a\":35,b:[1,2,3,4]}",
"b" : [
"1",
"2",
"3",
"4"
]
}
This means we can do some filtering, sorting and any of the other aggregation stages.
You could just use JSON.parse()
For example
db.getCollection('system').find({
a: JSON.parse('{"a":35,b:[1,2,3,4]}').a
})
For this specific case, everything works fine, except when
for the fields field1,field2 requested, and field1 is a part of field2.
Example :
> db.mycoll.findOne()
{
"_id" : 1,
"data" : {
"amounts" : {
"dollar" : 20,
"euro" : 18
},
"item" : "toy",
"sale" : false
}
}
// works well
> db.mycoll.findOne({"_id":1},{ "data.amounts.dollar":1 })
{ "_id" : 1, "data" : { "amounts" : { "dollar" : 20 } } }
// here "data" is root of "data.amounts.dollar" and "data.amounts.euro"
// takes preference, how to query for "data", so
// that all subfields of data are
// returned
> db.mycoll.findOne({"_id":1},{ "data":1 , "data.amounts.dollar":1 })
{ "_id" : 1, "data" : { "amounts" : { "dollar" : 20 } } }
Expected output :
{
"_id" : 1,
"data" : {
"amounts" : {
"dollar" : 20,
"euro" : 18
},
"item" : "toy",
"sale" : false
}
}
Yes, it is possible to format the subfields on the program side, and send the root field to mongodb query, but my question is if this is feasible on the querying side without Javascript .
This is unusual behavior, a bug to be precise.
From credible/official sources :
Jira Open Bug
Jira Bug Duplicate
Seems that the bug is still open.
Please let me know if you need any further analysis.
db.mycoll.findOne({"_id":1},{"data.amounts.dollar":1,"data":1 })
This gives as expected result
db.getCollection(coll_name).find({_id:1},{data:1});
This will give output
{
"_id" : 1,
"data" : {
"amounts" : {
"dollar" : 20,
"euro" : 18
},
"item" : "toy",
"sale" : false
}
}
Once you use a projection (the second json document in the 'find()', only those fields specified in the projection will be returned by the server (The exception is '_id' which will be returned unless explicitly turned off by _id:0).
{ "data":1 , "data.amounts.dollar":1 }
By selecting data.amounts.dollar inside the sub-document, you have essentially turned off the other members of the data.amounts document.
You can turn them on like you did with dollar, but I think you want them all projected regardless of knowing or not the field names.
I could not find in the documentation anything about order of fields in the projection field.
From the Mongo Documentation here
https://docs.mongodb.com/manual/tutorial/project-fields-from-query-results/#projection-document
I have a set of mongodb documents with the following structure:
{
"_id" : NUUID("58fbb893-dfe9-4f08-a761-5629d889647d"),
"Identifiers" : {
"IdentificationLevel" : 2,
"Identifier" : "extranet\\test#test.com"
},
"Personal" : {
"FirstName" : "Test",
"Surname" : "Test"
},
"Tags" : {
"Entries" : {
"ContactLists" : {
"Values" : {
"0" : {
"Value" : "{292D8695-4936-4865-A413-800960626E6D}",
"DateTime" : ISODate("2015-04-30T09:14:45.549Z")
}
}
}
}
}
}
How can I make a query with the mongo shell which finds all documents with a specific "Value" (e.g.{292D8695-4936-4865-A413-800960626E6D} in the Tag.Entries.ContactLists.Values path?
The structure is unfortunately locked by Sitecore, so it is not an options to use another structure.
As your sample collection structure show Values is object, it contains only one Value. Also you must check for Value as it contains extra paranthesis. If you want to get Value from given structure try following query :
db.collection.find({
"Tags.Entries.ContactLists.Values.0.Value": "{292D8695-4936-4865-A413-800960626E6D}"
})
I'm new to mongo database.Please help me in writing the query updation. I already had a collection in mongo and i would like to add a new field in existing object field.the structure is as follows.
{
"_class" : "PersistentContent",
"originalId" : "2070",
"videoInfo" : {
"test1" : ["res"]
},
}
I would like to update the structure to below format.
{
"_class" : "PersistentContent",
"originalId" : "2070",
"videoInfo" : {
"test1" : ["res"],
"test2" : ["res2"]
},
}
How to update the collection and add test2 into videoInfo tag.
use
db.test.update({"originalId" : "2070"},
{
$set : { "videoInfo.test2" : ["res2"] }
})
This is the first of 7 test/example documents, in collection "SoManySins."
{
"_id" : ObjectId("51671bb6a6a02d7812000018"),
"Treats" : "Sin1 = Gluttony",
"Sin1" : "Gluttony",
"Favourited" : "YES",
"RecentActivity" : "YES",
"GoAgain?" : "YeaSure."
}
I would like to be able to query to retrieve any info in any position,
just by referring to the position. The following document,
{
"_id" : ObjectId("51671bb6a6a02d7812000018"),
"Sin1" : "Gluttony",
"?????????" : "??????",
"RecentActivity" : "YES",
"GoAgain?" : "YeaSure."
}
One could retrieve whatever might be in the 3rd key~value
pair. Why should one have to know ahead of time what the
data is, in the key? If one has the same structure for the
collection, who needs to know? This way, you can get
double the efficiency? Like having a whole lot of mailboxes,
and your app's users supply the key and the value; your app
just queries the dbs' documents' arrays' positions.
Clara? finally? I hope?
The sample document you've provided is not saved as an array in BSON:
{
"_id" : ObjectId("51671bb6a6a02d7812000018"),
"Sin1" : "Gluttony",
"?????????" : "??????",
"RecentActivity" : "YES",
"GoAgain?" : "YeaSure."
}
Depending on the MongoDB driver you are using, the fields here are typically represented in your application code as an associative array or hash. These data structures are not order-preserving so you cannot assume that the 3rd field in a given document will correspond to the same field in another document (or even that the same field ordering will be consistent on multiple fetches). You need to reference the field by name.
If you instead use an array for your fields, you can refer by position or select a subset of the array using the $slice projection.
Example document with an array of fields:
{
"_id" : ObjectId("51671bb6a6a02d7812000018"),
"fields": [
{ "Sin1" : "Gluttony" },
{ "?????????" : "??????" },
{ "RecentActivity" : "YES" },
{ "GoAgain?" : "YeaSure." }
]
}
.. and query to find the second element of the fields array (a $slice with skip 1, limit 1):
db.SoManySins.find({}, { fields: { $slice: [1,1]} })
{
"_id" : ObjectId("51671bb6a6a02d7812000018"),
"fields" : [
{
"?????????" : "??????"
}
]
}
This is one way to Query and get back data when you may not
know what the data is, but you know the structure of the data:
examples in Mongo Shell, and in PHP
// the basics, setup:
$dbhost = 'localhost'; $dbname = 'test';
$m = new Mongo("mongodb://$dbhost");
$db = $m->$dbname;
$CursorFerWrites = $db->NEWthang;
// defining a set of data, creating a document with PHP:
$TheFieldGenerator = array( 'FieldxExp' => array(
array('Doc1 K1'=>'Val A1','Doc1 K2'=>'ValA2','Doc1 K3'=>'Val A3'),
array('Doc2 K1'=>'V1','Doc2 K2'=>'V2','Doc2 K3'=>'V3' ) ) ) ;
// then write it to MongoDB:
$CursorFerWrites->save($TheFieldGenerator);
NOTE : In the Shell : This produces the same Document:
> db.NEWthang.insert({"FieldxExp" : [
{"Doc1 K1":"Val A1","Doc1 K2":"Val A2","Doc1 K3":"Val A3"},
{"Doc2 K1":"V1", "Doc2 K2":"V2","Doc2 K3":"V3"}
]
})
#
Now, some mongodb Shell syntax:
> db.NEWthang.find().pretty()
{
"_id" : ObjectId("516c4053baa133464d36e836"),
"FieldxExp" : [
{
"Doc1 K1" : "Val A1",
"Doc1 K2" : "Val A2",
"Doc1 K3" : "Val A3"
},
{
"Doc2 K1" : "V1",
"Doc2 K2" : "V2",
"Doc2 K3" : "V3"
}
]
}
> db.NEWthang.find({}, { "FieldxExp" : { $slice: [1,1]} } ).pretty()
{
"_id" : ObjectId("516c4053baa133464d36e836"),
"FieldxExp" : [
{
"Doc2 K1" : "V1",
"Doc2 K2" : "V2",
"Doc2 K3" : "V3"
}
]
}
> db.NEWthang.find({}, { "FieldxExp" : { $slice: [0,1]} } ).pretty()
{
"_id" : ObjectId("516c4053baa133464d36e836"),
"FieldxExp" : [
{
"Doc1 K1" : "Val A1",
"Doc1 K2" : "Val A2",
"Doc1 K3" : "Val A3"
}
]
}
Finally, how about write the Query in some PHP ::
// these will be for building the MongoCursor:
$myEmptyArray = array();
$TheProjectionCriteria = array('FieldxExp'=> array('$slice' => array(1,1)));
// which gets set up here:
$CursorNEWthang1 = new MongoCollection($db, 'NEWthang');
// and now ready to make the Query/read:
$ReadomgomgPls=$CursorNEWthang1->find($myEmptyArray,$TheProjectionCriteria);
and the second document will be printed out:
foreach ($ReadomgomgPls as $somekey=>$AxMongoDBxDocFromCollection) {
var_dump($AxMongoDBxDocFromCollection);echo '<br />';
}
Hope this is helpful for a few folks.