I have a collection of the type :
{
"_id" : ObjectId("51f1fcc08188d3117c6da351"),
"cust_id" : "abc123",
"ord_date" : ISODate("2012-10-03T18:30:00Z"),
"status" : "A",
"price" : 25,
"items" : [{
"sku" : "ggg",
"qty" : 7,
"price" : 2.5
}, {
"sku" : "ppp",
"qty" : 5,
"price" : 2.5
}]
}
I want to fetch only the "items" object whose "items.qty">5 and and"items.sku"=="ggg".
I applied Map reduce:
cmd { "mapreduce" : "orders" , "map" : "function map(){var items_out={items:[]};for(i in this.items){items_out.items.push(this.items[i].sku);};emit(this._id,[items_out]);}" , "reduce" : "function reduce(key,values){return {'result':values};}" , "verbose" : true , "out" : { "replace" : "map_reduce"} , "query" : { "$where" : "return this.items.some(function(entry){return entry.qty>5})&&this.items.some(function(entry){return entry.sku=='ggg'})"}},
but I am getting all the sku values something like this:
{ "data": [ { "items": [ "ggg", "ppp" ] } ]}
Whereas it should give only ggg as this is the only value matching criteria.
Use the following command:
db.orders.aggregate(
{$unwind : "$items"},
{$match : {"items.qty": {$gt: 5 }}},
{$match : {"items.sku" : "ggg"}},
{$project : {_id:0, items:1}}
)
Related
i'm working with the restaurants db in mongo
{
"_id" : ObjectId("5c66fcf59e184ea712adfba6"),
"address" : {
"building" : "97-22",
"coord" : [
-73.8601152,
40.7311739
],
"street" : "63 Road",
"zipcode" : "11374"
},
"borough" : "Queens",
"cuisine" : "Jewish/Kosher",
"grades" : [
{
"date" : ISODate("2014-11-24T00:00:00.000Z"),
"grade" : "Z",
"score" : 20
},
{
"date" : ISODate("2013-01-17T00:00:00.000Z"),
"grade" : "A",
"score" : 13
},
{
"date" : ISODate("2012-08-02T00:00:00.000Z"),
"grade" : "A",
"score" : 13
},
{
"date" : ISODate("2011-12-15T00:00:00.000Z"),
"grade" : "B",
"score" : 25
}
],
"name" : "Tov Kosher Kitchen",
"restaurant_id" : "40356068"
}
I'm tryng to filter with match in aggregate. I want to check if any score in grades is greater than 5
db.runCommand({
aggregate: "restaurants",
pipeline : [
{$match: {"grades": {$anyElementTrue: {"score": {$gt:5}}}}}
but i'm getting this error:
"errmsg" : "unknown operator: $anyElementTrue",
thanks
Try with $eleMatch
db.restaurants.aggregate([{$match: {"grades": {$elemMatch: {"score": {$gt:5}}}}}])
I've got a lot of documents using the following structure in MongoDB:
{
"_id" : ObjectId("..."),
"plant" : "XY_4711",
"hour" : 1473321600,
"units" : [
{
"_id" : ObjectId("..."),
"unit_id" : 10951,
"values" : [
{
"quarter" : 1473321600,
"value" : 395,
},
{
"quarter" : 1473322500,
"value" : 402,
},
{
"quarter" : 1473323400,
"value" : 406,
},
{
"quarter" : 1473324300,
"value" : 410,
}
]
}
]
}
Now I need to find all embedded document values where the quarter is between some given timestamps (eg: { $gte: 1473324300, $lte: 1473328800 }).
I've only got the unit_id and the quarter timestamp from/to for filtering the documents. And I only need the quarter and value grouped and ordered by unit.
I'm new in MongoDB and read something about find() and aggregate(). But I don't know how to do it. MongoDB 3.0 is installed on the server.
Finally I've got it:
I simply have to take apart each array, filtering out the things I don't need and put it back together:
db.collection.aggregate([
{$match : {$and : [{"units.values.quarter" : {$gte : 1473324300}}, {"units.values.quarter" : {$lte : 1473328800 }}]}},
{$unwind: "$units"},
{$unwind: "$units.values"},
{$match : {$and : [{"units.values.quarter" : {$gte : 1473324300}}, {"units.values.quarter" : {$lte : 1473328800 }}]}},
{$project: {"units": {values: {quarter: 1, "value": 1}, unit_id: 1}}},
{$group: {"_id": "$units.unit_id", "quarter_values": {$push: "$units.values"}}} ,
{$sort: {"_id": 1}}
])
Will give:
{
"_id" : 10951,
"quarter_values" : [
{
"quarter" : 1473324300,
"value" : 410
},
{
"quarter" : 1473325200,
"value" : 412
},
{
"quarter" : 1473326100,
"value" : 412
},
{
"quarter" : 1473327000,
"value" : 411
},
{
"quarter" : 1473327900,
"value" : 408
},
{
"quarter" : 1473328800,
"value" : 403
}
]
}
See: Return only matched sub-document elements within a nested array for a detailed description!
I think I have to switch to $map or $filter in the future. Thanks to notionquest for supporting my questions :)
Please see the sample query below. I didn't exactly get your grouping requirement. However, with this sample query you should be able to change and get your desired output.
db.collection.aggregate([
{$unwind : {path : "$units"}},
{$match : {$and : [{"units.values.quarter" : {$gte : 1473324300}}, {"units.values.quarter" : {$lte : 1473328800 }}]}},
{$project : {"units" : {values : {quarter : 1, "value" : 1}, unit_id : 1}}},
{$group : { _id : "$units.unit_id", quarter_values : { $push :{ quarter : "$units.values.quarter", value : "$units.values.value"}}}},
{$sort : {_id : 1 }}
]);
Sample output:-
{
"_id" : 10951,
"quarter_values" : [
{
"quarter" : [
1473321600,
1473322500,
1473323400,
1473324300
],
"value" : [
395,
402,
406,
410
]
}
]
}
I have a following documents in my collection:
{ "_id" : ObjectId("5785e5649b732ab238cfc519"), "name" : "Apple", "category" : "Fruit", "price" : 100, "discount" : 5 }
{ "_id" : ObjectId("5785e5709b732ab238cfc51a"), "name" : "Orange", "category" : "Fruit", "price" : 90, "discount" : 5 }
{ "_id" : ObjectId("5785e5819b732ab238cfc51b"), "name" : "PineApple", "category" : "Fruit", "price" : 60, "discount" : 2 }
{ "_id" : ObjectId("5785e5969b732ab238cfc51c"), "name" : "Potatto", "category" : "Vegetable", "price" : 10, "discount" : 1 }
{ "_id" : ObjectId("5785e5c39b732ab238cfc51d"), "name" : "Cabbage", "category" : "Vegetable", "price" : 5, "discount" : 1 }
And Expected Result
{ "_id" : { "category" : "Vegetable" }, "total" : 15 }
And I am using mongoDB query to find the Sum of total with vegetable category as follows
db.stall.aggregate([{$group: {_id: {category: "Vegetable" }, total: {$sum: "$price"}}}]);
But I am getting the following result
{ "_id" : { "category" : "Vegetable" }, "total" : 265 }
How should I find the sum of total and discount columns with vegetable category.
I'm not sure if I'm getting your question right but this will filter the sume of Price and sum of Discount for Vegetable category.
db.stall.aggregate([
{
{$match : {category : "Vegetable"}},
{$group : {_id: "$category", sumOfTotal : {$sum : "$price"}, sumOfDiscount : {$sum : "$discount"}}}
}
])
I have a collection of the following data:
{
"_id" : ObjectId("51f1fcc08188d3117c6da351"),
"cust_id" : "abc123",
"ord_date" : ISODate("2012-10-03T18:30:00Z"),
"status" : "A",
"price" : 25,
"items" : [{
"sku" : "ggg",
"qty" : 7,
"price" : 2.5
}, {
"sku" : "ppp",
"qty" : 5,
"price" : 2.5
}]
}
I am using the query:
cmd { "aggregate" : "orders" , "pipeline" : [
{ "$unwind" : "$items"} ,
{ "$match" : { "items" : { "$elemMatch" : { "qty" : { "$in" : [ 7]}}}}} ,
{ "$group" : { "price" : { "$first" : "$price"} , "items" : { "$push" : { "sku" : "$items.sku"}} , "_id" : { "items" : "$items"}}} ,
{ "$sort" : { "price" : -1}} ,
{ "$project" : { "_id" : 0 , "price" : 1 , "items" : 1}}
]}
Not able to understand what is going wrong
It's because you're doing $match after $unwind. $unwind generates a new stream of documents where items is no longer an array (see docs).
It emits each document as many times as there are items in it.
If you want to select documents with desired element in it and then process all of its documents, you should call $match first:
db.orders.aggregate(
{ "$match" : { "items" : { "$elemMatch" : { "qty" : { "$in" : [ 7]}}}}},
{ "$unwind" : "$items"},
...
);
If you want to select items to be processed after $unwind, you shoul remove $elemMatch:
db.orders.aggregate(
{ "$unwind" : "$items"},
{ "$match" : { "items.qty" : { "$in" : [7]}}},
...
);
In first case you'll get two documents:
{
"price" : 25,
"items" : [
{"sku" : "ppp"}
]
},
{
"price" : 25,
"items" : [
{"sku" : "ggg"}
]
}
and in second case you'll get one:
{
"price" : 25,
"items" : [
{"sku" : "ggg"}
]
}
Update. After $unwind your documents will look like:
{
"_id" : ObjectId("51f1fcc08188d3117c6da351"),
"cust_id" : "abc123",
"ord_date" : ISODate("2012-10-03T18:30:00Z"),
"status" : "A",
"price" : 25,
"items" : {
"sku" : "ggg",
"qty" : 7,
"price" : 2.5
}
}
For small number of documents, unwind and match is fine. But large number of documents, it better to do - match ($elemMatch), unwind, and match again.
db.orders.aggregate(
{ "$match" : { "items" : { "$elemMatch" : { "qty" : { "$in" : [ 7]}}}}},
{ "$unwind" : "$items"},
{ "$match" : { "items.qty" : { "$in" : [7]}}}
...
...
);
The first match will filter only documents that match qty criteria. Among the selected documents, the second match will remove the subdocuments not matching the qty criteria.
I have a collection which has a field of array kind. I want to sort on the basis of a field of sub-array but Mongo is not sorting the data.
My collection is:
{
"_id" : ObjectId("51f1fcc08188d3117c6da351"),
"cust_id" : "abc123",
"ord_date" : ISODate("2012-10-03T18:30:00Z"),
"status" : "A",
"price" : 25,
"items" : [{
"sku" : "ggg",
"qty" : 7,
"price" : 2.5
}, {
"sku" : "ppp",
"qty" : 5,
"price" : 2.5
}]
}
My Query is:
db.orders.aggregate([
{ "$unwind" : "$items"} ,
{ "$match" : { }} ,
{ "$group" : { "items" : { "$addToSet" : { "sku" : "$items.sku"}} , "_id" : { }}} ,
{ "$sort" : { "items.sku" : 1}} ,
{ "$project" : { "_id" : 0 , "items" : 1}}
])
Result is:
"result" : [
{
"items" : [
{
"sku" : "ppp"
},
{
"sku" : "ggg"
}
]
}
],
"ok" : 1
}
Whereas "sku":"ggg" should come first when it is ascending.
You weant to do the sort BEFORE you regroup:
db.orders.aggregate([
{ "$unwind" : "$items"} ,
{ "$sort" : { "items.sku" : 1}},
{ "$match" : { }} ,
{ "$group" : { "items" : { "$push" : { "sku" : "$items.sku"}} , "_id" : null}} ,
{ "$project" : { "_id" : 0 , "items" : 1}}
])