I am inserting log items in the document in the form of an array. I have restricted document size up to 5MB to make sure that the document size is not increased.
Here one document contains one array and all the log items will be stored into the array. Lets say I have 500 log items of 5 MB size is stored in one document in the form an array.
When I delete 497 log items,It is showing the remaining 3 log items in the document but when I tried to delete one of the items from the 3 log items, the entire document was deleted, I don't know What is happening.
Is the array in the document should have some minimum number size of data.
Note: I am restricting the document size at my application level.
Here is the sample data:
activityLogDetails:
[{
"activityLog": {
"acctId": 1,
"info1": {
"itemName": "-",
"value": "-"
},
"info2": {
"itemName": "-",
"value": "-"
},
"errorCode": "",
"internalInformation": "",
"kind": "Infomation",
"loginId": "0",
"opeLogId": "G1_1",
"operation": "startDiscovery",
"result": "normal",
"targetId": "1",
"timestamp": "1470980265729",
"undoFlag": "false"
}
},{
"activityLog": {
"acctId": 2,
"info1": {
"itemName": "-",
"value": "-"
},
"info2": {
"itemName": "-",
"value": "-"
},
"errorCode": "",
"internalInformation": "",
"kind": "Infomation",
"loginId": "0",
"opeLogId": "G1_1",
"operation": "startDiscovery",
"result": "normal",
"targetId": "1",
"timestamp": "1470980265729",
"undoFlag": "false"
}
},
etc....]
Delete Query:
db.test.remove({activityLogDetails.activityLog.acctId:{$gt:2}})
Could any body tell me what could be the issue?
What you are doing in your query, will remove the whole record.
Try the following query using $pull:-
db.test.updateMany(
{'activityLogDetails.activityLog.acctId':{$gt:2}},
{$pull:{activityLogDetails:{'activityLog.acctId':{$gt:2}}}})
Refer $pull for more info on how to use.
Related
I have a collection named "devices" with roughly 50,000 documents. I'm trying to query the "routes" array within each document and have it return the document if multiple conditions are met for the individual array elements. The problem is it seems Mongo is giving back answers where the multiple conditions are satisfied for different array elements.
Sample Data:
{
"_id": 0,
"name": "example1",
"serial": "123456",
"routes": [
{
"description": "8989",
"zone": "front"
},
{
"description": "1221",
"zone": "back"
}
]
},
{
"_id": 1,
"name": "example2",
"serial": "987654",
"routes": [
{
"description": "1515",
"zone": "front"
},
{
"description": "8989",
"zone": "side"
}
]
}
I've tried simple .find() variations with no luck including
db.devices.find({"routes.description":"8989", "routes.zone":"front"})
db.devices.find({"$and": [{"routes.description":"8989"}, {"routes.zone":"front"}]})
I've also tried aggregations which seems to fail on me since my understanding of them is elementary. The desired results for the queries above would be a single document ("_id":0) and not both documents.
{ "_id" : 0, "name" : "example1", "serial" : "123456", "routes" : [ { "description" : "8989", "zone" : "front" }, { "description" : "1221", "zone" : "back" } ] }
Additionally, the ability to query the array using the $in operator would be desired. For example, the following query's desired output would be both documents since both of them have routes that match "zone":"front" and "descriptions" that are in the list.
db.devices.find({"$and": [{"routes.description": { $in: ["8989", "1515"] }}, {"routes.zone":"front"}]})
You simply need to use $elemMatch here
db.devices.find({routes: {$elemMatch: {description:"8989", zone:"front"}}})
Example
I am trying to identify documents where both key-value pairs within an array match using the aggregate pipeline. Specifically, if I want to find documents where one array contains user_attribute.Name = Quests_In_Progress and user_attribute.Value =3. Below is an example of such a document that I'm trying to match.
If I use
db.myCollection.aggregate({
$match: {
"user_attribute.Name": "Quests_In_Progress",
"user_attribute.Value": "3"
}
})
It will match every document that contains Quests_In_Progress for user_attribute.Name in one element of the array and contains "3" for user_attribute.Value, regardless of whether they exist in the same element of the array or not.
i.e.
db.myCollection.aggregate({
$match: {
"user_attribute.Name": "Quests_In_Progress",
"user_attribute.Value": "0"
}
})
will match the same document simply because one element of the array has a key:Value pair of Value:0 and another element of the array contains a key:value pair of Quests_In_Progress.
What I want to do is identify documents where both of those conditions are met within one element of the array.
I tried to do this with $elemMatch, but I couldn't get it to work. Plus the aggregate documentation doesn't indicate that $elemMatch works, so maybe that's why I couldn't get it to work.
Lastly, I need to use the aggregate pipeline, because there are a bunch of other things I have to do after finding these documents- specifically unwinding them.
{
"_id": ObjectId("5555bb32de938ce667f78ce00"),
"user_attribute": [{
"Value": "Facebook",
"Name": "Social_Connection"
}, {
"Name": "Total_Fireteam_Missions_Initiated",
"Value": "0"
}, {
"Name": "Quests_Completed",
"Value": "3"
}, {
"Name": "Item_Slots_Owned",
"Value": "36"
}, {
"Name": "Quests_In_Progress",
"Value": "3"
}, {
"Name": "Player_Progression",
"Value": "0"
}, {
"Value": "1",
"Name": "Characters_Owned"
}, {
"Name": "Quests_Started",
"Value": "6"
}, {
"Name": "Total_Friends",
"Value": "0"
}, {
"Name": "Device_Type",
"Value": "Phone"
}]
}
Try using $elemMatch
db.myCollection.aggregate([{$match: {"user_attribute": {$elemMatch: {"Name":"Quests_In_Progress", "Value":"0"}}}}, { $out, "temp"}])
That query will find anyone who has element of their array "Quests_In_Progress" with a value of 0 and put it into the collection temp
I'm new in Node.JS and I'm able to parse the JSON data and do a console log to print out name and badges.
var details = JSON.parse(body);
console.log(details.name, details.badges.length);
But I don't know how I can get the data inside the arrays of the bagdes such as id, name, url.
I tried
console.log(details.badges.length.id);
But nothing shows up. How can I access that? Thank you.
{
"name": "Andrew Chalkley",
"badges": [
{
"id": 49,
"name": "Newbie",
"url": "http:\/\/teamtreehouse.com\/chalkers",
"icon_url": "https:\/\/achievement-images.teamtreehouse.com\/Generic_Newbie.png",
"earned_date": "2012-07-23T19:59:34.000Z",
"courses": [
]
},
{
"id": 26,
"name": "Introduction",
"url": "http:\/\/teamtreehouse.com\/library\/html\/introduction",
"icon_url": "https:\/\/achievement-images.teamtreehouse.com\/HTML_Basics.png",
"earned_date": "2012-07-23T21:57:24.000Z",
"courses": [
{
"title": "HTML",
"url": "http:\/\/teamtreehouse.com\/library\/html",
"badge_count": 1
},
{
"title": "Introduction",
"url": "http:\/\/teamtreehouse.com\/library\/html\/introduction",
"badge_count": 1
}
]
}
}
It is an array, so you need the index, for example: details.badges[0].id
This will return the first (index 0) element id.
.length only returns the length of the array, so it will not be useful to get the data in it.
I've been looking at some StackOverflow cases such as this case, but I cannot find an example with a document structure close to this one.
Below is an example of one document within my collection artistTags. All documents follow the same structure.
{
"_id": ObjectId("5500aaeaa7ef65c7460fa3d9"),
"toptags": {
"tag": [
{
"count": "100",
"name": "Hip-Hop"
},
{
"count": "97",
"name": "french rap"
},
...{
"count": "0",
"name": "seen live"
}
],
"#attr": {
"artist": "113"
}
}
}
1) How can I find() this document using the "artist" value (here "113")?
2) How can I retrieve all "artist" values having a specific "name" value (say "french rap") ?
Referring to chridam answer here above:
db.collection.find({"toptags.#attr.artist": "113"})
I'm trying to figure out what the best schema is for a dating site like app. User's have a listing (possibly many) and they can view other user listings to 'like' and 'dislike' them.
Currently i'm just storing the other persons listing id in a likedBy and dislikedBy array. When a user 'likes' a listing, it puts their listing id into the 'liked' listings arrays. However I would now like to track the timestamp that a user likes a listing. This would be used for a user's 'history list' or for data analysis.
I would need to do two separate queries:
find all active listings that this user has not liked or disliked before
and for a user's history of 'liked'/'disliked' choices
find all the listings user X has liked in chronological order
My current schema is:
listings
_id: 'sdf3f'
likedBy: ['12ac', 'as3vd', 'sadf3']
dislikedBy: ['asdf', 'sdsdf', 'asdfas']
active: bool
Could I do something like this?
listings
_id: 'sdf3f'
likedBy: [{'12ac', date: Date}, {'ds3d', date: Date}]
dislikedBy: [{'s12ac', date: Date}, {'6fs3d', date: Date}]
active: bool
I was also thinking of making a new collection for choices.
choices
Id
userId // id of current user making the choice
userlistId // listing of the user making the choice
listingChoseId // the listing they chose yes/no
type
date
I'm not sure of the performance implications of having these choices in another collection when doing the find all active listings that this user has not liked or disliked before.
Any insight would be greatly appreciated!
Well you obviously thought it was a good idea to have these embedded in the "listings" documents so your additional usage patterns to the cases presented here worked properly. With that in mind there is no reason to throw that away.
To clarify though, the structure you seem to want is something like this:
{
"_id": "sdf3f",
"likedBy": [
{ "userId": "12ac", "date": ISODate("2014-04-09T07:30:47.091Z") },
{ "userId": "as3vd", "date": ISODate("2014-04-09T07:30:47.091Z") },
{ "userId": "sadf3", "date": ISODate("2014-04-09T07:30:47.091Z") }
],
"dislikedBy": [
{ "userId": "asdf", "date": ISODate("2014-04-09T07:30:47.091Z") },
{ "userId": "sdsdf", "date": ISODate("2014-04-09T07:30:47.091Z") },
{ "userId": "asdfas", "date": ISODate("2014-04-09T07:30:47.091Z") }
],
"active": true
}
Which is all well and fine except that there is one catch. Because you have this content in two array fields you would not be able to create an index over both of those fields. That is a restriction where only one array type of field (or multikey) can be be included within a compound index.
So to solve the obvious problem with your first query not being able to use an index, you would structure like this instead:
{
"_id": "sdf3f",
"votes": [
{
"userId": "12ac",
"type": "like",
"date": ISODate("2014-04-09T07:30:47.091Z")
},
{
"userId": "as3vd",
"type": "like",
"date": ISODate("2014-04-09T07:30:47.091Z")
},
{
"userId": "sadf3",
"type": "like",
"date": ISODate("2014-04-09T07:30:47.091Z")
},
{
"userId": "asdf",
"type": "dislike",
"date": ISODate("2014-04-09T07:30:47.091Z")
},
{
"userId": "sdsdf",
"type": "dislike",
"date": ISODate("2014-04-09T07:30:47.091Z")
},
{
"userId": "asdfas",
"type": "dislike",
"date": ISODate("2014-04-09T07:30:47.091Z")
}
],
"active": true
}
This allows an index that covers this form:
db.post.ensureIndex({
"active": 1,
"votes.userId": 1,
"votes.date": 1,
"votes.type": 1
})
Actually you will probably want a few indexes to suit your usage patterns, but the point is now can have indexes you can use.
Covering the first case you have this form of query:
db.post.find({ "active": true, "votes.userId": { "$ne": "12ac" } })
That makes sense considering that you clearly are not going to have both an like and dislike option for each user. By the order of that index, at least active can be used to filter because your negating condition needs to scan everything else. No way around that with any structure.
For the other case you probably want the userId to be in an index before the date and as the first element. Then your query is quite simple:
db.post.find({ "votes.userId": "12ac" })
.sort({ "votes.userId": 1, "votes.date": 1 })
But you may be wondering that you suddenly lost something in that getting the count of "likes" and "dislikes" was as easy as testing the size of the array before, but now it's a little different. Not a problem that cannot be solved using aggregate:
db.post.aggregate([
{ "$unwind": "$votes" },
{ "$group": {
"_id": {
"_id": "$_id",
"active": "$active"
},
"likes": { "$sum": { "$cond": [
{ "$eq": [ "$votes.type", "like" ] },
1,
0
]}},
"dislikes": { "$sum": { "$cond": [
{ "$eq": [ "$votes.type", "dislike" ] },
1,
0
]}}
])
So whatever your actual usage form you can store any important parts of the document to keep in the grouping _id and then evaluate the count of "likes" and "dislikes" in an easy manner.
You may also not that changing an entry from like to dislike can also be done in a single atomic update.
There is much more you can do, but I would prefer this structure for the reasons as given.