Is it possible to create a sequential list of enum values in MongoDB, and more specifically MongooseJS?
What I mean is, for example, storing iPhone model like:
"model": {
"type": "string",
"enum": ["Original", "3g", "3gs", "4", "4s", "5", "5s", "6", "6s", "5SE", "7"]
}
or child clothing sizes:
"size": {
"type": "string",
"enum": ["3MO", "6MO", "9MO", "12MO", "18MO", "2T", "2", "3T"...]
}
and then use query operators like $gt and $lt to query for iPhones with
"model": { "$gte": "3g" }
Thanks.
yes you can create enum in mongoose.
refer the the documentation here. it has detailed example.
http://mongoosejs.com/docs/api.html#schema_string_SchemaString-enum
You cannot use $lte, $gte for string, it's only for numbers, but you still can query using $in operator
Schema
"field": {
"type": "string",
"enum": ["a", "b", "c"]
}
Query
myModel.find({
field: {
$in: ['a', 'some other prop']
}
})
This will find all instances that match ['a', 'some other prop'] in array
Related
I have the JSON below in mongodb and would like write a bson.M filter to get a specific JSON in collection.
JSONs in collection:
{
"Id": "3fa85f64",
"Type": "DDD",
"Status": "PRESENT",
"List": [{
"dd": "55",
"cc": "33"
}],
"SeList": {
"comm_1": {
"seId": "comm_1",
"serName": "nmf-comm"
},
"comm_2": {
"seId": "comm_2",
"serName": "aut-comm"
}
}
}
{
"Id": "3fa8556",
"Type": "CCC",
"Status": "PRESENT",
"List": [{
"dd": "22",
"cc": "34"
}],
"SeList": {
"dnn_1": {
"seId": "dnn_1",
"serName": "dnf-comm"
},
"dnn_2": {
"seId": "dnn_2",
"serName": "dn2-comm"
}
}
}
I have written below the bson.M filter to select the first JSON but did not work because I do not know how to handle the map keys in the "SeList.serName". The keys comm_1, comm_2, dnn_1, etc could be any string.
filter := bson.M{"Type": DDD, "Status": "PRESENT", "SeList.serName": nmf-comm} // does not work because the "SeList.serName" is not correct.
I need help about how to select any JSON based on the example filter above.
I have a series of deeply nested json strings in a pyspark dataframe column. I need to explode and filter based on the contents of these strings and would like to add them as columns. I've tried defining the StructTypes but each time it continues to return an empty DF.
Tried using json_tuples to parse but there are no common keys to rejoin the dataframes and the row numbers dont match up? I think it might have to do with some null fields
The sub field can be nullable
Sample JSON
{
"TIME": "datatime",
"SID": "yjhrtr",
"ID": {
"Source": "Person",
"AuthIFO": {
"Prov": "Abc",
"IOI": "123",
"DETAILS": {
"Id": "12345",
"SId": "ABCDE"
}
}
},
"Content": {
"User1": "AB878A",
"UserInfo": "False",
"D": "ghgf64G",
"T": "yjuyjtyfrZ6",
"Tname": "WE ARE THE WORLD",
"ST": null,
"TID": "BPV 1431: 1",
"src": "test",
"OT": "test2",
"OA": "test3",
"OP": "test34
},
"Test": false
}
Not sure I am using the right terminology here, but assume following oversimplified JSON structure available in Mongo :
{
"_id": 1234,
"labels": {
"label1": {
"id": "l1",
"value": "abc"
},
"label3": {
"id": "l2",
"value": "def"
},
"label5": {
"id": "l3",
"value": "ghi"
},
"label9": {
"id": "l4",
"value": "xyz"
}
}
}
{
"_id": 5678,
"labels": {
"label1": {
"id": "l1",
"value": "hjk"
},
"label5": {
"id": "l5",
"value": "def"
},
"label10": {
"id": "l10",
"value": "ghi"
},
"label24": {
"id": "l24",
"value": "xyz"
}
}
}
I know my base element name (labels in the example), but I do not know the various sub elements I can have (so in this case the labelx names).
How can I group / count the existing elements (like as if I would be using a wildcard) so I would get some distinct overview like
"label1":2
"label3":1
"label5":2
"label9":1
"label10":1
"label24":1
as a result? So far I only found examples where you actually need to know the element names. But I don't know them and want to find some way to get all possible sub element names for a given top element for easy review.
In reality the label names can be pretty wild, I used labelx for readability in the example.
You can try below aggregation in 3.4.
Use $objectToArray to transform object to array of key value pairs followed by $unwind and $group on key to count occurrences.
db.col.aggregate([
{"$project":{"labels":{"$objectToArray":"$labels"}}},
{"$unwind":"$labels"},
{"$group":{"_id":"$labels.k","count":{"$sum":1}}}
])
I am trying to figure out specific mongoDb query, so far unsuccessfully.
Documents in my collections looks someting like this (contain more attributes, which are irrelevant for this query):
[{
"_id": ObjectId("596e01b6f4f7cf137cb3d096"),
"code": "A",
"name": "name1",
"sys": {
"cts": ISODate("2017-07-18T12:40:22.772Z"),
}
},
{
"_id": ObjectId("596e01b6f4f7cf137cb3d097"),
"code": "A",
"name": "name2",
"sys": {
"cts": ISODate("2017-07-19T12:40:22.772Z"),
}
},
{
"_id": ObjectId("596e01b6f4f7cf137cb3d098"),
"code": "B",
"name": "name3",
"sys": {
"cts": ISODate("2017-07-16T12:40:22.772Z"),
}
},
{
"_id": ObjectId("596e01b6f4f7cf137cb3d099"),
"code": "B",
"name": "name3",
"sys": {
"cts": ISODate("2017-07-10T12:40:22.772Z"),
}
}]
What I need is to get current versions of documents, filtered by code or name, or both. Current version means that from two(or more) documents with same code, I want pick the one which has latest sys.cts date value.
So, result of this query executed with filter name="name3" would be the 3rd document from previous list. Result of query without any filter would be 2nd and 3rd document.
I have an idea how to construct this query with changed data model but I was hoping someone could lead me right way without doing so.
Thank you
I have the following structure in MongoDB and I try to remove the documents that contains specific tags. I can't seem to be able to get the $pull work.
In this example, I would like to pull the nested doc that has has tags :["BB"]
Any help will be appreciated !
{
"_id": 123,
"socialItems": {
"facebook": [{
"name": "firstFacebook",
"id": 2
}, {
"name": "secondFB",
"id": 43
}],
"instagram": [{
"name": "firstNstagram",
"id": 4
}],
"pc": [{
"name": "firstPC",
"id": 55,
"tags": [
"ab"
]
}, {
"name": "secondPC",
"id": 66,
"tags": [
"BB"
]
}]
}
}
I assume you are trying to drop the nested 'pc' doc, from the array? You also don't mention if you're using a specific driver for this, so I've assumed you're running this in the Mongo shell.
The following will remove documents from the 'pc' property, when containing the 'BB' tag.
db.collectionName.update({'socialItems.pc.tags': 'BB'}, {$pull: {'socialItems.pc': {tags: 'BB'}}})