Mongodb query takes too long if no matches found - database

I have a posts collection like bellow :
{
"_id" : ObjectId("5ad249121c76fb096c0081e6"),
"slug" : "5ad2491261324",
"title" : "title",
"content" : "content here",
"tags" : [
"tag1",
"tag2"
],
"status" : 1,
"created_at" : ISODate("2018-04-12T07:23:07.000Z"),
"user_id" : ObjectId("5ad249111c76fb096c007dfd"),
"url_id" : ObjectId("5ad249121c76fb096c0081e7"),
"updated_at" : ISODate("2018-04-14T18:31:46.000Z"),
"images" : [
{
"extension" : "jpg",
"path" : "/medias/tests/4.jpg",
"thumbnail" : "/medias/tests/4-th.jpg",
"updated_at" : ISODate("2018-04-14T18:31:46.000Z"),
"created_at" : ISODate("2018-04-14T18:31:46.000Z"),
"_id" : ObjectId("5ad249121c76fb096c0081e8")
}
]
}
The collection has text index on title.
When i execute bellow query :
db.getCollection('posts').find({title: /test/})
If there is at least one matches, the query executes very fast. But when it has not matches, takes too long to execute.
Why this happening?
Edit
I have 100m record in this collection.

MongoDB facilitates creating text indexes on fields to search text contained into fields belonging to collection of MongoDB Database
According to description as mentioned into above question collection has a text index on title field.
Hence to search a string value into title field please try executing following find operation into MongoDB shell.
db.getCollection('posts').find({
$text: {
$search: 'test'
})
According to documentation of MongoDB
$text performs a text search on the content of the fields indexed with
a text index.

Related

Firebase Realtime Database orderByChild data structure - ReactJS

I'm having issues querying data with orderByChild. I would like to query all tasks where provided userID matches any approver id. Task ID is autogenerated so I need to flatten this structure somehow.
Each task has two approvers, and each approver has status, timestamp, id.
Any idea on how to flatten it so I can take advantage of orderByChild?
Tasks:{
"df234dgkjsf234" : {
"approvers" : {
"4U1D23dfsdf23e" : {
"id" : "4U1DWf95rJvgfAwDYs7m",
"status" : "pending",
"timestamp" : "pending"
},
"sdf32fdsf34sdg3" : {
"id" : "FXRkK22TjyxKV6z4UkrU",
"status" : "pending",
"timestamp" : "pending"
}
},
"reason" : "test",
"requester" : "4U1DWf95rJvgfAwDYs7m",
"requesterName" : "Dana Mayers",
"status" : "pending",
"tagetValue" : "QT1IkGHS3mmalyXqdCuD",
"taskName" : "Title Change",
"timestamp" : 1644773238,
"value" : "New Title"
},
"d4S34FSAdsf43FM" : {
...
}
}
I want to make ideally one query to get this data as opposed to querying by Approver1 and then by Approver2
Tasks:{
"df234dgkjsf234" : {
"Approver1" : "4U1DWf95rJvgfAwDYs7m",
"Approver1status" : "pending",
"Approver1timestamp" : "pending"
"Approver2" : "FXRkK22TjyxKV6z4UkrU",
"Approver2status" : "pending",
"Approver2timestamp" : "pending",
"reason" : "test",
"requester" : "4U1DWf95rJvgfAwDYs7m",
"requesterName" : "Dana Mayers",
"status" : "pending",
"tagetValue" : "QT1IkGHS3mmalyXqdCuD",
"taskName" : "Title Change",
"timestamp" : 1644773238,
"value" : "New Title"
},
"d4S34FSAdsf43FM" : {
...
}
}
There is no way to do this with one query, since you're looking for two separate values. The closest you can get is by doing two separate queries on (4Approver1 and Approver2 in) the second data structure, and then merging the results in your application code.
The alternative is to add a secondary data structure, where you map from the user ID back to the tasks they're allowed to approve:
UserTasks: {
"4U1D23dfsdf23e": {
"df234dgkjsf234": true,
"d4S34FSAdsf43FM": true
},
"sdf32fdsf34sdg3": {
"df234dgkjsf234": true
}
}
With such an additional structure you can easily find the tasks for a specific UID, and then load the task details for each.
For more on this, I recommend also reading:
Many to Many relationship in Firebase
Firebase query if child of child contains a value
Firebase Query Double Nested

Mongodb Query Multiple Levels Deep

I have the following document:
{
"_id" : ObjectId("5a202aa0728bac010a8d2467"),
"tickers" : {
"information_technology" : [
"ACN",
"ATVI",
"ADBE",
"AMD",
],
"misc" : [
"AA",
"GE",
"AAPL",
"PFE",
]
},
"name" : "S&P500"
}
I want to query the document by name ("S&P500") and return a list within the "tickers" field.
I tried db.collection.find_one("$and": [{'name': 'S&P500'}, {'tickers': 'misc'}]) but no documents were returned.
I am new to mongodb so I may have missed something in the documentation.
Thanks for any help.
The API for Collection.find_one is similar with Collection.find except that limit is ignored and a single document returned for a match or None if there is no match.
find(filter=None, projection=None, skip=0, limit=0, no_cursor_timeout=False, cursor_type=CursorType.NON_TAILABLE, sort=None, allow_partial_results=False, oplog_replay=False, modifiers=None, manipulate=True) Docs
An appropriate filter is {'name': 'S&P500'} when looking to match documents with name equals S&P500.
Also, an appropriate projection is {'tickers.misc': True} when projecting only tickers.misc.
db.collection.find_one({'name': 'S&P500'}, {'tickers.misc': True})

Updating a collection inside array of collections in MongoDB

I have a mongo collection workspaces in my MongoDB which consist of records that looks like as follows:
{
"_id" : ObjectId("58bdc4a13504f5ed743ad025"),
"name" : "My workspace",
"user_id" : ObjectId("58b6cf53988a874af070fd3b"),
"uploads" : [
{
"original" : "DE-20__450_GG_5002_N23_994__0136.tif"
},
{
"original" : "DE-20__450_GG_5002_N23_994__0134.png"
},
{
"original" : "DE-20__450_GG_5002_N23_994__0136.png"
},
{
"original" : "DE-20__450_GG_5002_N23_994__0134.tif"
}
]
}
Now my objective is that i want to append something in one of record of array uploads with the match criteria of original field value. For example i want to append "pseg" : "DE-20__450_GG_5002_N23_994__0136.pseg.tif" to the {"original" : "DE-20__450_GG_5002_N23_994__0136.tif"} collection in following way:
{
"_id" : ObjectId("58bdc4a13504f5ed743ad025"),
"name" : "Objective",
"user_id" : ObjectId("58b6cf53988a874af070fd3b"),
"uploads" : [
{
"original" : "DE-20__450_GG_5002_N23_994__0136.tif",
"pseg" : "DE-20__450_GG_5002_N23_994__0136.pseg.tif"
},
{
"original" : "DE-20__450_GG_5002_N23_994__0134.png"
},
{
"original" : "DE-20__450_GG_5002_N23_994__0136.png"
},
{
"original" : "DE-20__450_GG_5002_N23_994__0134.tif"
}
]
}
i tried using $elemMatch and then i added $addToSet in following way:
db.getCollection('workspaces').update({"_id": ObjectId("58bdc4a13504f5ed743ad025"),"uploads": {$elemMatch: {"original": "DE-20__450_GG_5002_N23_994__0136.tif"}}},{$addToSet:{"uploads.$": {"pseg" : "DE-20__450_GG_5002_N23_994__0136.pseg.tif"}}})
but it gives me following error:
Cannot apply $addToSet to a non-array field. Field named '0' has a non-array type object in the document _id: ObjectId('58bdc4a13504f5ed743ad025')
I think i crafted the query wrong can anyone tell me what is wrong and how can i solve it?
Sorry for my bad english :) hope you understood what i said.
Here is the correct syntax. You have to use $set with postional operator to reach the element.
db.getCollection('workspaces').update(
{"_id": ObjectId("58bdc4a13504f5ed743ad025"),"uploads": {$elemMatch: {"original": "DE-20__450_GG_5002_N23_994__0136.tif"}}},
{$set:{"uploads.$.pseg" : "DE-20__450_GG_5002_N23_994__0136.pseg.tif"}})
More information here https://docs.mongodb.com/manual/reference/operator/update/positional/#update-documents-in-an-array
You can simplify your query criteria. You don't need to use $elemMatch operator for single query condition. You can use dot notation.
db.getCollection('workspaces').update(
{"_id": ObjectId("58bdc4a13504f5ed743ad025"),"uploads.original": "DE-20__450_GG_5002_N23_994__0136.tif"},
{$set:{"uploads.$.pseg" : "DE-20__450_GG_5002_N23_994__0136.pseg.tif"}})
More information here
https://docs.mongodb.com/manual/reference/operator/query/elemMatch/#single-query-condition

How to find documents in MongoDb matching a field and subdocument field that are in an array

The document structure is as follows:
{
"_id" : "V001-99999999",
"vendor_number" : "V001",
"created_time" : ISODate("2016-04-26T22:15:34Z"),
"updated_time" : ISODate("2016-06-07T21:45:46.413Z"),
"items" : [
{
"sku" : "99999999-1",
"status" : "ACTIVE",
"listing_status" : "LIVE",
"inventory" : 10,
"created_time" : ISODate("2016-05-14T22:15:34Z"),
"updated_time" : ISODate("2016-05-14T20:42:21.753Z"),
},
{
"sku" : "99999999-2",
"status" : "INACTIVE",
"listing_status" : "LIVE",
"inventory" : 10,
"created_time" : ISODate("2016-04-26T22:15:34Z"),
"updated_time" : ISODate("2016-06-06T20:42:21.753Z"),
}
]
}
I want to obtain the sku from the item, the conditions are:
1) "vendor_number" = "XXX"
2) items.status = "ACTIVE" AND items.updated_time < [given_date]
Result example:
"sku" : "99999999-2"
or csv:
"sku","99999999-2"
Thank you for your support.
This should be what you want. Although I'm assuming you wanted "status": "active"?
db.getCollection('collection').aggregate([
{ $match: { "vendor_number": "XXXX" } },
{ $project: {
"items": {
$filter: {
input: "$items",
as: "item",
cond: { $eq: ["$$item.status", "ACTIVE"] } // or maybe ["$$item.listing_status", "LIVE"] ?
}
}
}
},
{ $project: { "items.sku": true } }
])
I love using aggregation to manipulate stuff. It's great all the things you can do with it. So here's what's going on:
The first part is simple. The $match step in the aggregation pipeline says just give me documents where vendor_number is "XXXX".
The next part is a bit hairy. The first projection step creates a new field, called "items", I could have called it "results" or "bob" if I wanted to. The $filter specifies which items should go into this new field. The new "items" field will be an array that will have all the results from the previous items field, hence the input: "$items", where you're using the keyword "item" to represent each input item that comes into the filter. Next, the condition says, for each item, only put it in my new "items" array if the item's status is "ACTIVE". You can change it to ["$$items.listing_status", "LIVE"] if that's what you needed. All of this will pretty much give you you're result.
The last project just get's rid of all other fields except for items.sku in each element in the new "items" array.
Hope this help. Play around with it and see what else you can do with the collection and aggregation. Let me know if you need any more clarification. If you haven't used aggregation before, take a look at the aggregation docs and the list of pipeline operators you can use with aggregation. Pretty handy tool.

How to find documents by value which match either a document's attribute or an array's element

I have a collection with the following document:
{ "_id" : "DzQuhq22NhQm5waCm", "title" : "Test", "users" : [ "wCxEmesi2M73dLze4" ], "userId" : "htMZEZTMxsQXq6sRD", "createdAt" : ISODate("2015-10-05T12:09:34.852Z") }
The attribute users is an array which contains also userIds.
Now I want to find this document if my value is either within the users array or matches the userId. So, this document should be returned if my value is htMZEZTMxsQXq6sRD or wCxEmesi2M73dLze4.
I tried the following:
db.test.find({userId: val}, {users: {$in: val}); but this does not work.
Thanks in advance.
Try this:
db.getCollection('TESTCOLLECTION').find({$or:[{'userId':'htMZEZTMxsQXq6sRD '},{'users':'wCxEmesi2M73dLze4'}]})

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