Below is MongoDB document.
`{
"_id" : ObjectId("588f09c8d466d7054114b456"),
"phonebook" : [
{
"pb_name_first" : "Aasu bhai",
"pb_phone_number" : [
{
"ph_id" : 2,
"ph_no" : "+91111111",
"ph_type" : "Mobile"
}
],
"pb_email_id" : [
{
"email_id" : "temp#gmail.com",
"email_type" : "Home",
"em_id" :1
},
{
"email_id" : "test#gmail.com",
"email_type" : "work",
"em_id" :2
}
],
"pb_name_prefix" : "MR."
}
]
}`
I want mongodb query that will update email_id data in pb_email_id array on basis of em_id. If i select em_id=1 then that record temp#gmail.com will update.if i select em_id=2 then test#gmail.com will update.
I don't think you can apply if-else logic in update call, you can run two separate update calls
db.collection.update({'pb_email_id.em_id':1},{$set : {'pb_email_id.$.email_id' : 'temp#gmail.com'}},{multi:true});
db.collection.update({'pb_email_id.em_id':2},{$set : {'pb_email_id.$.email_id' : 'test#gmail.com'}},{multi:true});
However you can run a script on collection to apply multiple logic
db.collection.find({}).forEach(function(doc){
if(doc.pb_email_id && doc.pb_email_id.length>0){
for(var i in doc.pb_email_id){
if(doc.pb_email_id[i].em_id === 1){
doc.pb_email_id[i].email_id = "temp#gmail.com"}
else if(doc.pb_email_id[i].em_id === 2){doc.pb_email_id[i].email_id = "test#gmail.com"}
db.collection.save(db)
}
}
})
If you have to apply multiple logic, you can run script, otherwise two update calls if that's as much as needed.
P.S - since you didn't mentioned collection name, I used db.collection.update it should be collection name like db.phonebook.find etc.
Related
I'm trying to select all objects in my database which are between two dates.
Problem is: Dates are inside of an array
Already tried using both Robo 3T and Studio 3T with SQL, with no sucess.
{
"_id" : "5d9b703fe1bc4f138c5977b5",
"Number" : 112795,
"Finalizations" : [
{
"Value" : "89.95",
"Portions" : [
{
"Expiration" : ISODate("2019-11-06T02:00:00.000Z"),
"Value" : "89.95"
}
]
}
]
}
I need to return all the objects that have an "Expiration" between 11/01 and 11/25.
Assuming your collection is called mycollection you can query using the mongo shell...
db.mycollection.find(
{
"Finalizations.Portions.Expiration": {"$gte": ISODate("2019-11-01")},
"Finalizations.Portions.Expiration": {"$lt": ISODate("2019-11-25")}
}
)
I'm a novice with mongodb so please excuse me if the question is a little basic. I have a mongo collection with a relatively complex document structure. The documents contain sub documents and arrays. I need to add additional data to some of the documents in this collection. A cut down version of the document is:
"date" : ISODate("2018-08-07T08:00:00.000+0000"),
.
. <<-- Other fields
.
"basket" :
[
{
"assetId" : NumberInt(639),
"securityId" : NumberInt(12470),
.
. <<-- Other fields
.
"exGroup" : [
. << -- Fields......
.
. << -- New Data will go here
]
}
.
. << More elements
]
The following (abridged) aggregation query finds the documents that need modifying:
{
"$match" : {
"date" : {
"$gte" : ISODate("2018-08-07T00:00:00.000+0000"),
"$lt" : ISODate("2018-08-08T00:00:00.000+0000")
}
}
},
{
"$unwind" : {
"path" : "$basket"
}
},
{
"$unwind" : {
"path" : "$basket.exGroup"
}
},
{
"$project" : {
"_id" : 1.0,
"date" : 1.0,
"assetId" : "$basket.assetId",
"securityId" : "$basket.securityId",
"exGroup" : "$basket.exGroup"
}
},
{
"$unwind" : {
"path" : "$exGroup"
}
},
{
"$match" : {
"exGroup.order" : {
"$exists" : true
}
}
}
For each document returned by the mongo query I need to (in python) retrieve a set of additional data from a SQL database and then append this data to the original mongo document as shown above. The set of new fields will be the same, the data will be different. What is not clear to me is how, once I have the data I go about updating the array values.
Could somebody give me a pointer?
Try this, it works for me!
mySchema.aggregate([
//your aggregation code
],function(err, docList){
//for each doc in docList
async.each(docList, function(doc, callback){
query = {$and:[{idField:doc.idField},{"myArray.ArrayId":doc.myArray.ArrayId}]}
//Update or create field in array
update = {$set:"myArray.$.FieldNameToCreateOrUpdate":value}}
projection = {field1:1, field2:1, field3:1}
mySchema.findOneAndUpdate(query, update, projection, function(err, done){
if(err){callback(err,null)}
callback(null,'done')
})
,function(err){
//code if error
//code if no error
}
})
I'm using a model tree structures with an array of ancestors and I need to check if any document is missing.
{
"_id" : "GbxvxMdQ9rv8p6b8M",
"type" : "article",
"ancestors" : [ ]
}
{
"_id" : "mtmTBW8nA4YoCevf4",
"parent" : "GbxvxMdQ9rv8p6b8M",
"ancestors" : [
"GbxvxMdQ9rv8p6b8M"
]
}
{
"_id" : "J5Dg4fB5Kmdbi8mwj",
"parent" : "mtmTBW8nA4YoCevf4",
"ancestors" : [
"GbxvxMdQ9rv8p6b8M",
"mtmTBW8nA4YoCevf4"
]
}
{
"_id" : "tYmH8fQeTLpe4wxi7",
"refType" : "reference",
"parent" : "J5Dg4fB5Kmdbi8mwj",
"ancestors" : [
"GbxvxMdQ9rv8p6b8M",
"mtmTBW8nA4YoCevf4",
"J5Dg4fB5Kmdbi8mwj"
]
}
My attempt would be to check each ancestors id if it is existing. If this fails, this document is missing and the data structure is corrupted.
let ancestors;
Collection.find().forEach(r => {
if (r.ancestors) {
r.ancestors.forEach(a => {
if (!Collection.findOne(a))
missing.push(r._id);
});
}
});
But doing it like this will need MANY db calls. Is it possible to optimize this?
Maybe I could get an array with all unique ancestor ids first and check if these documents are existing within one db call??
First take out all distinct ancesstors from your collections.
var allAncesstorIds = db.<collectionName>.distinct("ancestors");
Then check if any of the ancesstor IDs are not in the collection.
var cursor = db.<collectionName>.find({_id : {$nin : allAncesstorIds}}, {_id : 1})
Iterate the cursor and insert all missing docs in a collection.
cursor.forEach(function (missingDocId) {
db.missing.insert(missingDocId);
});
I have a mongo document that contains an array called history:
{
"_id" : ObjectId("575fe85bfe98c1fba0a6e535"),
"email" : "email#address",
"__v" : 0,
"history" : [
{
"name" : "Test123",
"organisation" : "Rat",
"field" : 4,
"another": 3
}
]
}
I want to add fields to each history object or update fields IF the name AND organisation match, however if they don't, I want to add a new object to the array with the queried name and organisation and add/update the other fields to the object when necessary.
So:
This query, finds one that matches:
db.users.find({
email:"email#address",
$and: [
{ "history.name": "Test123", "history.organisation": "Rat"}
]
})
However, I'm struggling to get the update/upsert to work IF that combination of history.name and history.organisation dont exist in the array.
What I think I need to do is a :
"If this history name does not equal 'Test123' AND the history organisation does not equal 'Rat' then add an object to the array with those fields and any other field provided in the update query."
I tried this:
db.users.update({
email:"email#address",
$and: [
{ "history.name": "Test123", "history.organisation": "Rat"}
]
}, {
history: { name: "Test123"},
history: { organisation: "Rat"}
}, {upsert:true})
But that gave me E11000 duplicate key error index: db.users.$email_1 dup key: { : null }
Any help greatly appreciated.
Thanks community!
Not possible with a single atomic update I'm afraid, you would have to do a couple of update operations that satisfy both conditions.
Break down the update logic into two distinct update operations, the first one would require using the positional $ operator to identify the element in the history array you want and the $set to update the existing fields. This operation follows the logic update fields IF the name AND organisation match
Now, you'd want to use the findAndModify() method for this operation since it can return the updated document. By default, the returned document does not include the modifications made on the update.
So, armed with this arsenal, you can then probe your second logic in the next operation i.e. update IF that combination of "history.name" and "history.organisation" don't exist in the array. With this second
update operation, you'd need to then use the $push operator to add the elements.
The following example demonstrates the above concept. It initially assumes you have the query part and the document to be updated as separate objects.
Take for instance when we have documents that match the existing history array, it will just do a single update operation, but if the documents do not match, then the findAndModify() method will return null, use this logic in your second update operation to push the document to the array:
var doc = {
"name": "Test123",
"organisation": "Rat"
}, // document to update. Note: the doc here matches the existing array
query = { "email": "email#address" }; // query document
query["history.name"] = doc.name; // create the update query
query["history.organisation"] = doc.organisation;
var update = db.users.findAndModify({
"query": query,
"update": {
"$set": {
"history.$.name": doc.name,
"history.$.organisation": doc.organisation
}
}
}); // return the document modified, if there's no matched document update = null
if (!update) {
db.users.update(
{ "email": query.email },
{ "$push": { "history": doc } }
);
}
After this operation for documents that match, querying the collection will yield the same
db.users.find({ "email": "email#address" });
Output:
{
"_id" : ObjectId("575fe85bfe98c1fba0a6e535"),
"email" : "email#address",
"__v" : 0,
"history" : [
{
"name" : "Test123",
"organisation" : "Rat",
"field" : 4,
"another" : 3
}
]
}
Now consider documents that won't match:
var doc = {
"name": "foo",
"organisation": "bar"
}, // document to update. Note: the doc here does not matches the current array
query = { "email": "email#address" }; // query document
query["history.name"] = doc.name; // create the update query
query["history.organisation"] = doc.organisation;
var update = db.users.findAndModify({
"query": query,
"update": {
"$set": {
"history.$.name": doc.name,
"history.$.organisation": doc.organisation
}
}
}); // return the document modified, if there's no matched document update = null
if (!update) {
db.users.update(
{ "email": query.email },
{ "$push": { "history": doc } }
);
}
Querying this collection for this document
db.users.find({ "email": "email#address" });
would yield
Output:
{
"_id" : ObjectId("575fe85bfe98c1fba0a6e535"),
"email" : "email#address",
"__v" : 0,
"history" : [
{
"name" : "Test123",
"organisation" : "Rat",
"field" : 4,
"another" : 3
},
{
"name" : "foo",
"organisation" : "bar"
}
]
}
How to get subdocument element's count inside an array and how to update the subdocument's key in MongoDB
For eg, following is the whole doc stored in mongodb:
{
"CompanyCode" : "SNBN",
"EventCode" : "ET00008352",
"EventName" : "Sunburn Presents Avicii India Tour",
"TktDetail" : [
{
"Type" : "Category I",
"Qty" : {
"10-Dec" : {
"value" : 58
},
"11-Dec" : {
"value" : 83
},
"12-Dec" : {
"value" : 100
}
}
},
{
"Type" : "Category II",
"Qty" : {
"10-Dec" : {
"value" : 4
},
"11-Dec" : {
"value" : 7
},
"12-Dec" : {
"value" : 8
}
}
},
{
"Type" : "PRICE LEVEL 1",
"Qty" : {
"11-Dec" : {
"value" : 2
}
}
},
{
"Type" : "CatIV",
"Qty" : {
"18-Dec" : {
"value" : 20
}
}
}
],
"TransDate" : [
"10-Dec-2013",
"11-Dec-2013",
"12-Dec-2013",
],
"VenueCode" : "SNBN",
"VenueName" : "Sunburn",
"_id" : ObjectId("52452db273b92012c41ad612")
}
Here TktDetail is an array, inside which there is a Qty subdoc which contains multiple elements, I want to know how to get the elements count inside Qty per index?
For example, the 0th index of TktDetail array contains 1 Qty subdoc, which further has a element count of 3, whereas 3rd index has element count of 1 in Qty subdoc.
If I want to update the subdoc key, like, I want to update the date in Qty from "10-Dec" to "10-Dec-2013", how is it possible?
Thanks in advance, looking for a reply ASAP..
So the first thing here is that you actually asked two questions, being "how do I get a count of the items under Qty?" and "how can I change the names?". Now while normally unrelated I'm going to treat them as the same thing.
What you need to do is change your schema and in doing so I'm going to allow you to get the count of items and I'm going to encourage you to change those field names as well. Specifically you need a schema like this:
"TktDetail" : [
{
"Type" : "Category I",
"Qty" : [
{ "date": ISODate("2013-12-10T00:00:00.000Z") , "value" : 58 },
{ "date": ISODate("2013-12-11T00:00:00.000Z"), "value" : 83 },
{ "date": ISODate("2013-12-01T00:00:00.000Z"), "value" : 100 },
]
},
All the gory details are in my answer here to a similar question. But the problem basically is that when you use sub-documents in the way you have you are ruining your chances of doing any meaningful query operations on this, as to get at each element you must specify the full path to get there.
That answer has more detail, but the case is you really want an array. The trade-off, it's a little harder to update, especially considering you have nested arrays, but it's a lot easier to add and much easier to query.
Also, and related, change your dates to be dates and not strings. The strings, are no good for comparisons inside MongoDB. With them set as proper BSON dates (noting I clipped them to the start of day) you can compare, and query ranges and do useful things. Your application code will be happy to as the driver will return a real date object, rather than something you have to manipulate "both ways".
So once you have read through, understood and implemented this, on to counting:
db.collection.aggregate([
// Unwind the TktDetail array to de-normalize
{"$unwind": "$TktDetail"},
// Also Unwind the Qty array
{"$unwind": "$Qty" },
// Get some group information and count the entries
{"$group": {
"_id": {
"_id": "$_id,
"EventCode": "$EventCode",
"Type": "$TktDetail.Type"
},
"Qty": {"$sum": 1 }
}},
// Project nicely
{"$project": {
"_id": 0,
"EventCode": "$_id.EventCode",
"Type: "$_id.Type",
"Qty": 1,
}},
// Let's even sort it
{"$sort": { "EventCode": 1, "Qty" -1 }}
])
So that allowed us to get a count of the items in Qty for each EventCode by Type with the Qty ordered higest to lowest.
And that is not possible on your current schema without loading and traversing each document in code.
So there is the case. Now if you want to ignore this and just go about changing the sub-document key names, then you'll need to do remove the key and underlying document and replace with the new key name, using update:
db.collection.update(
{ EventCode: "ET00008352"},
{ $unset:{ "TktDetail.0.Qty.10-Dec": "" }}
)
db.collection.update(
{ EventCode: "ET00008352"},
{ $set:{ "TktDetail.0.Qty.10-Dec-2013": { value: 58 } }}
)
And you'll need to do that for every item that you have.
So you either work out that schema conversion or otherwise have a lot of work anyway in order to change the keys. For myself, I'd do it properly, and only do it once so I didn't run into the next problem later.