I need some help with a Firebase query.
How can I retrieve all users where in the child "groups" a specific group exists?
Every user object in de database looks like this:
"067f010c-5580-450a-84ba-6e94880886c2": {
"goal":
{
"distance": "10",
"time": "20"
},
"groups":
{
"-KH0O99wyxT61xVfjnH5":
{
"group_id": "-KH0O99wyxT61xVfjnH5",
"name": "Test"
},
"-KH0OFDI9jjReE75y7Dj":
{
"group_id": "-KH0OFDI9jjReE75y7Dj",
"name": "Beest"
}
},
"name": "Arnoud",
"uid": "067f010c-5580-450a-84ba-6e94880886c2"
}
That could be an expensive query as your data set grows. What about having a separate child ('groups') that stores all of your groups and in each group object you keep a reference id to each member that is a part of that group? Then you can query the data from that direction.
Related
I am able to fetch the subscription id and name from azure cli. Need to remove the subscriptions which has a particular string in their names. How to achieve this in groovy?
My code is as below
az account list --query '[].{name:name,id:id}
It returns the below values
[
{
"id": "66666666666666",
"name": "sub-demo-1"
},
{
"id": "22222222222222",
"name": "sub-demo-2"
},
{
"id": "000000000000000",
"name": "sub-prod-1"
},
{
"id": "888888888888888",
"name": "sub-prod-2"
}
]
I need to remove all the subscriptions which has the name demo in it. Secondly it should save only the subscription ids to another array after removing the unwanted items.
I want the below output
[
000000000000000,
888888888888888
]
I'm using Firebase DataBase in my application.
Below is my Collection data
Object {
"buyer": Object {
"firstName": "firstname",
"lastName": "lastName",
"phoneNumber": "9876543210",
},
"buyerId": "TfHemJat3L3kkz0t3qDn",
"orderDate": "Sat May 29 18:55:47 2021",
"orderDetails": Array [
Object {
"itemId": "3iPDW2OJePJBCuR6xA09",
"status": "Pending",
},
Object {
"itemId": "jDJDHaBLI2kQ4reaaWI8",
"status": "Pending",
},
],
"orderId": "t20212941855550",
}
I want to update the Status from Pending to Accepted where only
ItemId == "3iPDW2OJePJBCuR6xA09".
I don't know how to update, Can you please suggest the solution to the same.
Thank in Advance.
You can use the update function predefined in the firebase library and inside that function pass the argument and variable in which you want to update with the values in the same format as it was created in the database also vote if it works
I have a noSql (Cloudant) database
-Within the database we have documents where one of the document fields represents “table” (type of document)
-Within the documents we have fields that represent links other documents within the database
For example:
{_id: 111, table:main, user_id:222, field1:value1, other1_id: 333}
{_id: 222, table:user, first:john, other2_id: 444}
{_id: 333, table:other1, field2:value2}
{_id: 444, table:other2, field3:value3}
We want of way of searching for _id:111
And the result be one document with data from linked tables:
{_id:111, user_id:222, field1:value1, other1_id: 333, first:john, other2_id: 444, field2:value2, field3:value3}
Is there a way to do this?
There is flexibility on the structure of how we store or get the data back—any suggestions on how to better structure the data to make this possible?
The first thing to say is that there are no joins in Cloudant. If you're schema relies on lots of joining then you're working against the grain of Cloudant which may mean extra complication for you or performance hits.
There is a way to de-reference other documents' ids in a MapReduce view. Here's how it works:
create a MapReduce view to emit the main document's body and its linked document's ids in the form { _id: 'linkedid'}
query the view with include_docs=true to pull back the document AND the de-referenced ids in one go
In your case, a map function like this:
function(doc) {
if (doc.table === 'main') {
emit(doc._id, doc);
if (doc.user_id) {
emit(doc._id + ':user', { _id: doc.user_id });
}
}
}
would allow you to pull back the main document and its linked user document in one API by hitting the GET /mydatabase/_design/mydesigndoc/_view/myview?startkey="111"&endkey="111z"&include_docs=true endpoint:
{
"total_rows": 2,
"offset": 0,
"rows": [
{
"id": "111",
"key": "111",
"value": {
"_id": "111",
"_rev": "1-5791203eaa68b4bd1ce930565c7b008e",
"table": "main",
"user_id": "222",
"field1": "value1",
"other1_id": "333"
},
"doc": {
"_id": "111",
"_rev": "1-5791203eaa68b4bd1ce930565c7b008e",
"table": "main",
"user_id": "222",
"field1": "value1",
"other1_id": "333"
}
},
{
"id": "111",
"key": "111:user",
"value": {
"_id": "222"
},
"doc": {
"_id": "222",
"_rev": "1-6a277581235ca01b11dfc0367e1fc8ca",
"table": "user",
"first": "john",
"other2_id": "444"
}
}
]
}
Notice how we get two rows back, the first is the main document body, the second the linked user.
MongoDb Collection Example (Person):
{
"id": "12345",
"schools": [
{
"name": "A",
"zipcode": "12345"
},
{
"name": "B",
"zipcode": "67890"
}
]
}
Desired output:
{
"id": "12345",
"schools": [
{
"zipcode": "12345"
},
{
"zipcode": "67890"
}
]
}
My current partial code for retrieving all:
collection.find({}, {id: true, schools: true})
I am querying the entire collection. But I only want to return zipcode part of school element, not other fields (because the actual school object might contain much more data which I do not need). I could retrieve all and remove those un-needed fields (like "name" of school) in code, but that's not what I am looking for. I want to do a MongoDb query.
You can use the dot notation to project specific fields inside documents embedded in an array.
db.collection.find({},{id:true, "schools.zipcode":1}).pretty()
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.