I have a dataset like this:
{
"_id" : ObjectId("5ede1b6c317aca326c2f18d7"),
"createdate" : ISODate("2020-06-11T18:30:00.000Z"),
"userHolder" : [
{
"time" : "12:00",
"user" : [
"5ede1ff42b3e633edc0ba10e"
]
},
{
"time" : "16:30",
"user" : []
}
],
},
{
"_id" : ObjectId("5ede1b6c317aca326c2f18d8"),
"createdate" : ISODate("2020-06-121T18:30:00.000Z"),
"userHolder" : [
{
"time" : "12:30",
"user" : [
"5ede1ff42b3e633edc0ba10f"
]
},
{
"time" : "13:00",
"user" : [
"5ede1ff42b3e633edc0ba10e"
]
},
{
"time" : "12:00",
"user" : [
"5ede1ff42b3e633edc0ba10f"
]
},
{
"time" : "16:30",
"user" : []
}
],
}
I split the half hour entry. i,e full day 48 columns on userHolder columns. Like 12:30, 13:00, 13:30 and so on. If user not have entry then that column will not create.
So if I want to search 5ede1ff42b3e633edc0ba10e this id on the complete table then how to write the query.
I tried to use >$all operator but this not works on nested structure.
There is a $elemMatch but for that query will be too large as I have to write the 48 conditions of timestamp. Expected result is query return the _id of the entry so that it will clear that these id will exist on n numbers of entry. I want the Data not count.
Any help is really appreciated for that.
Related
We were working on a project with a 300 documents with currentValue field in a main collection, in order to track the history of each document of first collection. we created another collection named history with approximately 6.5 millions of documents.
For each input of system we have to add around 30 history item and update currentValue field of main collection, so, We tried computational field design pattern for currentValue, which lead us to have writeConfilict in concurrent situations (at concurrency of around 1000 requests).
Then we tried to compute currentValue field with sum (amount field) and groupBy(mainId field) on history collection which takes too long (> 3s).
Main collection docs:
{
"_id" : ObjectId(...),
"stock" : [
{
"currentAmount" : -313430.0,
"lastPrice" : -10.0,
"storage" : ObjectId("..."),
"alarmCapacity" : 12
},
{
"currentAmount" : 30,
"lastPrice" : 0,
"storage" : ObjectId("..."),
"alarmCapacity" : 12
},
.
.
.
],
"name" : "name",
}
History collection docs:
{
"_id" : ObjectId("..."),
"mainId" : ObjectId("..."),
"amount" : 5,
}
If you have any other idea to handle this situation(application or db level), I would be thankful.
UPDATE 1
The update query if I use computed pattern would be:
mainCollection.findOneAndUpdate(
{
$and: [
{ _id: id },
{ "stock.storage": fromId },
{ "stock.deletedAt": null }
],
},
{
$inc: {
"stock.$.currentAmount": -1 * amount,
}
},
{
session
}
)
And Aggregation pipeline if I want to calculate currentAmount everytime:
mainCollection.aggregate([
{
$match: {
branch: new ObjectId("...")
}
},
{
$group: {
_id: "$ingredient",
currentAmount: {
$sum: "$amount"
}
}
}])
in order to have computed field, mongo design patterns, suggested computed field,
The Computed Pattern is utilized when we have data that needs to be computed repeatedly in our application. link
like below:
// your main collection will look like this
{
"_id" : ObjectId(...),
"stock" : [
{
"currentAmount" : -313430.0,
"lastPrice" : -10.0,
"storage" : ObjectId("..."),
"alarmCapacity" : 12
},
{
"currentAmount" : 30,
"lastPrice" : 0,
"storage" : ObjectId("..."),
"alarmCapacity" : 12
},
"totalAmount": 20000 // for example
}
but for having concurrent there is a better way to solve this problem with cumulative summation, in this algorithm, we sum last documents inputs, with current input:
{
"_id" : ObjectId("..."),
"mainId" : ObjectId("..."),
"amount" : 5,
"cumulative": 15 // sum of last documents input
}
Hi i am mentioning the sample data
///collection - test////
{
"_id" : {
"date" : ISODate("2020-02-11T17:00:00Z"),
"userId" : ObjectId("5e43e5cdc11f750864f46820"),
"adminId" : ObjectId("5e43de778b57693cd46859eb")
},
"outstanding" : 212.39999999999998,
"totalBill" : 342.4,
"totalPayment" : 130
}
{
"_id" : {
"date" : ISODate("2020-02-11T17:00:00Z"),
"userId" : ObjectId("5e43e73169fe1e3fc07eb7c5"),
"adminId" : ObjectId("5e43de778b57693cd46859eb")
},
"outstanding" : 797.8399999999999,
"totalBill" : 797.8399999999999,
"totalPayment" : 0
}
I need to structure a query which does following things-
I need to calculate the actualOutstanding:[(totalBill+outstanding)-totalPayment],
I need to save this actualOutstanding in the same collection & in the same document according to {"_id" : {"date","userId", "adminId" }}
NOTE: userId is different in both the documents.
Introduced in Mongo version 4.2+ pipelined updates, meaning we can now use aggregate expressions to update documents.
db.collection.updateOne(
{
"adminId" : ObjectId("5e43de778b57693cd46859eb")
'_id."userId" : ObjectId("5e43e73169fe1e3fc07eb7c5"),
'_id.date': ISODate("2020-02-11T18:30:00Z"),
},
[
{ '$set': {
actualOutstanding: {
$subtract:[ {$add: ['$totalBill','$outstanding']},'$totalPayment']
}
} }
]);
For any other Mongo version you have to split it into 2 actions, first query and calculate then update the document with the calculation.
I have a document in the below format. The goal is to group the document by student name and sort it by rank in the ascending order. Once that is done, iterate through the rank(within a student) and if each subsequent rank is greater than the previous one, the version field needs to be incremented. As part of a pipeline, student_name will be passed to me so matching by student name should be good instead of grouping.
NOTE: Tried it with python and works to some extent. A python solution would also be great!
{
"_id" : ObjectId("5d389c7907bf860f5cd11220"),
"class" : "I",
"students" : [
{
"student_name" : "AAA",
"Version" : 2,
"scores" : [
{
"value" : "50",
"rank" : 2
},
{
"value" : "70",
"rank" : 1
}
]
},
{
"student_name" : "BBB",
"Version" : 5,
"scores" : [
{
"value" : 80,
"rank" : 2
},
{
"value" : 100,
"rank" : 1
},
{
"value" : 100,
"rank" : 1
}
]
}
]
}
I tried this piece of code to sort
def version(student_name):
db.column.aggregate(
[
{"$unwind": "$students"},
{"$unwind": "$students.scores"},
{"$sort" : {"students.scores.rank" : 1}},
{"$group" : {"students.student_name}
]
)
for i in range(0,(len(students.scores)-1)):
if students.scores[i].rank < students.scores[i+1].rank:
tag.update_many(
{"$inc" : {"students.Version":1}}
)
The expected output for student AAA should be
{
"_id" : ObjectId("5d389c7907bf860f5cd11220"),
"class" : "I",
"students" : [
{
"student_name" : "AAA",
"Version" : 3, #version incremented
"scores" : [
{
"value" : "70",
"rank" : 1
},
{
"value" : "50",
"rank" : 2
}
]
}
I was able to sort the document.
pipeline = [
{"$unwind": "$properties"},
{"$unwind": "$properties.values"},
{"$sort" : {"$properties.values.rank" : -1}},
{"$group": {"_id" : "$properties.property_name", "values" : {"$push" : "$properties.values"}}}
]
import pprint
pprint.pprint(list(db.column.aggregate(pipeline)))
This question already has answers here:
MongoDB Query Help - query on values of any key in a sub-object
(3 answers)
Closed 6 years ago.
This is my data set, which is part of a bigger json code. I want to write a query, which will match all fields inside the value chain.
Dataset:
"value_chain" : {
"category" : "Source, Make & Deliver",
"hpe_level0" : "gift Chain Planning",
"hpe_level1" : "nodemand to Plan",
"hpe_level2" : "nodemand Planning",
"hpe_level3" : "nodemand Sensing"
},
Example:
If someone searches for "gift", the query should scan through all fields, and if there is a match, return the document.
This is something I tried, but didnt work
db.sw_api.find({
value_chain: { $elemMatch: { "Source, Make & Deliver" } }
})
Sounds like you need to create $text index on all the text fields first since it performs a text search on the content of the fields indexed with a text index:
db.sw_api.createIndex({
"value_chain.category" : "text",
"value_chain.hpe_level0" : "text",
"value_chain.hpe_level1" : "text",
"value_chain.hpe_level2" : "text",
"value_chain.hpe_level3" : "text"
}, { "name": "value_chain_text_idx"});
The index you create is a composite index consisting of 5 columns, and mongo will automatically create the text namespace for you by default if you don't override it. With the above, if you don't specify the index name as
db.sw_api.createIndex({
"value_chain.category" : "text",
"value_chain.hpe_level0" : "text",
"value_chain.hpe_level1" : "text",
"value_chain.hpe_level2" : "text",
"value_chain.hpe_level3" : "text"
});
there is a potential error "ns name is too long (127 byte max)" since the text index will look like this:
"you_db_name.sw_api.$value_chain.category_text_value_chain.hpe_level0_text_value_chain.hpe_level1_text_value_chain.hpe_level2_text_value_chain.hpe_level3_text"
Hence the need to give it a name which is not too long if autogenerated by mongo.
Once the index is created, a db.sw_api.getIndexes() query will show you the indexes present:
/* 1 */
[
{
"v" : 1,
"key" : {
"_id" : 1
},
"name" : "_id_",
"ns" : "dbname.sw_api"
},
{
"v" : 1,
"key" : {
"_fts" : "text",
"_ftsx" : 1
},
"name" : "value_chain_text_idx",
"ns" : "dbname.sw_api",
"weights" : {
"value_chain.category" : 1,
"value_chain.hpe_level0" : 1,
"value_chain.hpe_level1" : 1,
"value_chain.hpe_level2" : 1,
"value_chain.hpe_level3" : 1
},
"default_language" : "english",
"language_override" : "language",
"textIndexVersion" : 3
}
]
Once you create the index, you can then do a $text search:
db.sw_api.find({ "$text": { "$search": "gift" } })
I have a document as below, and I want to pull all the elements in this array without any condition just via one statement. how can I do?
"energy_sent" : [
{
"player_id" : "034010000093",
"_id" : ObjectId("53675b8d251c20490d9679c6"),
"time" : ISODate("2014-05-05T09:36:13.629Z"),
"has_accepted" : 0,
"energy_value" : 2
},
{
"player_id" : "034010000094",
"_id" : ObjectId("53675cfa251c20490d9679cc"),
"time" : ISODate("2014-05-05T09:42:18.015Z"),
"has_accepted" : 0,
"energy_value" : 2
},
{
"player_id" : "034010000116",
"_id" : ObjectId("5367767889f8e3ee137dd239"),
"time" : ISODate("2014-05-05T11:31:04.457Z"),
"has_accepted" : 0,
"energy_value" : 2
}
]
If you are just after emptying the entire array just set it to empty:
db.collection.update(
{ /* query to match document */ },
{ "$set": { "energy_sent": [] }
)
So just use the $set operator