Mongo DB: I'm looking to make one query to return both the first and last element of an array. I realize that I can do this multiple queries, but I would really like to do it with one.
Assume a collection "test" where each objects has an array "arr" of numbers:
db.test.find({},{arr:{$slice: -1},arr:{$slice: 1}});
This will result in the following:
{ "_id" : ObjectId("xxx"), "arr" : [ 1 ] } <-- 1 is the first element
Is there a way to maybe alias the results? Similar to what the mysql AS keyword would allow in a query?
This is not possible at the moment but will be with the Aggregation Framework that's in development now if I understand your functional requirement correctly.
You have to wonder about your schema if you have this requirement in the first place though. Are you sure there isn't a more elegant way to get this to work by changing your schema accordingly?
This can be done with the aggregation framework using the operators $first and $last as follows:
db.test.aggregate([
{ '$addFields': {
'firstElem': { '$first': '$arr' },
'lastElem': { '$last': '$arr' }
} }
])
or using $slice as
db.test.aggregate([
{ '$addFields': {
'firstElem': { '$slice': [ '$arr', 1 ] },
'lastElem': { '$slice': [ '$arr', -1 ] }
} }
])
Related
new to Mongo. Trying to group across different sub fields of a document based on a condition. The condition is a regex on a field value. Looks like -
db.collection.aggregate([{
{
"$group": {
"$cond": [{
"upper.leaf": {
$not: {
$regex: /flower/
}
}
},
{
"_id": {
"leaf": "$upper.leaf",
"stem": "$upper.stem"
}
},
{
"_id": {
"stem": "$upper.stem",
"petal": "$upper.petal"
}
}
]
}
}])
Using api v4.0: cond in the docs shows - { $cond: [ <boolean-expression>, <true-case>, <false-case> ] }
The error I get with the above code is - "Syntax error: dotted field name 'upper.leaf' can not used in a sub object."
Reading up on that I tried $let to re-assign the dotted field name. But started to hit various syntax errors with no obvious issue in the query.
Also tried using $project to rename the fields, but got - Field names may not start with '$'
Thoughts on the best approach here? I can always address this at the application level and split my query into two but it's attractive potentially to solve it natively in mongo.
$group syntax is wrong
{
$group:
{
_id: <expression>, // Group By Expression
<field1>: { <accumulator1> : <expression1> },
...
}
}
You tried to do
{
$group:
<expression>
}
And even if your expression resulted in the same code, its invalid syntax for $group (check from the documentation where you are allowed to use expressions)
One other problem is that you use the query operator for regex, and not the aggregate regex operators (you can't do that, if you aggregate you can use only aggregate operators, only $match is the exception that you can use both if you add $expr)
You need this i think
[{
"$group" : {
"_id" : {
"$cond" : [ {
"$not" : [ {
"$regexMatch" : {
"input" : "$upper.leaf",
"regex" : "/flower/"}}]},
{"leaf" : "$upper.leaf","stem" : "$upper.stem"},
{"stem" : "$upper.stem","petal" : "$upper.petal"}]
}
}}]
Its similar code, but expression gets as value of the "_id" and $regexMatch
is used that is aggregate operator.
I didnt tested the code.
Given collection:
{
"_id" : "1.1000038",
"recomendation" : [
"1.6739718"
]
}
/* 2 */
{
"_id" : "1.1000069",
"recomendation" : [
"1.9185509",
"1.9051998",
"1.9034279",
"1.8288046",
"1.8152670",
"1.858775",
"1.6224229",
"1.4591674",
"1.3862464",
"1.3427739",
"1.3080062",
"1.3003608",
"1.1694619",
"1.1634683",
"1.1590664",
"1.1524146",
"1.754599",
"1.700837",
"1.763617"
]
}
I need to query the MongoDB for a list of values and get the first element of the list of values
here is the query by mongo syntax
db.getCollection('similar_articles').find({"_id":{$in:["1.1000069","1.1000038"]}})
I don't want to filter it on the python side because it's can be too big.
I didn't find any documentation on it
desire output:
Pandas DataFrame
_id recom
1.1000038 1.6739718
1.1000069 1.9185509
I don't know pymongo so well, but you need this query:
First $match by _ids into the arreay (this is like the find you have).
And later use $project to create the field recom (you can use "recomendation" to overwrite the existing field) and set the value as the first into the array.
db.collection.aggregate([
{
"$match": { "_id": { "$in": [ "1.1000069", "1.1000038" ] } }
},
{
"$project": { "recom": { "$arrayElemAt": [ "$recomendation", 0 ] } }
}
])
Example here
Looking the doumentation it seems you only need to copy and paste this query.
I am using aggregation with mongoDB now i am facing a problem here, i am trying to match my documents which are present in my input array by using $in operator. Now i want to know the index of the lement from the input array now can anyone please tell me how can i do that.
My code
var coupon_ids = ["58455a5c1f65d363bd5d2600", "58455a5c1f65d363bd5d2601","58455a5c1f65d363bd5d2602"]
couponmodel.aggregate(
{ $match : { '_id': { $in : coupons_ids }} },
/* Here i want to know index of coupon_ids element that is matched because i want to perform some operation in below code */
function(err, docs) {
if (err) {
} else {
}
});
Couponmodel Schema
var CouponSchema = new Schema({
category: {type: String},
coupon_name: {type: String}, // this is a string
});
UPDATE-
As suggested by user3124885 that aggregation is not better in performance, can anyone please tell me the performance difference between aggregation and normal query in mongodb. And which one is better ??
Update-
I read this question on SO mongodb-aggregation-match-vs-find-speed. Here the user himself commented that both take same time, also by seeing vlad-z answer i think aggregation is better. Please if anyone of you have worked on mongodb Then please tell me what are your opinion about this.
UPDATE-
I used sample json data containing 30,000 rows and tried match with aggregation v/s find query aggregation got executed in 180 ms where find query took 220ms. ALso i ran $lookup it is also taking not much than 500ms so think aggregation is bit faster than normal query. Please correct me guys if any one of you have tried using aggregation and if not then why ??
UPDATE-
I read this post where user uses below code as a replacement of $zip SERVER-20163 but i am not getting how can i solve my problem using below code. So can anybody please tell me how can i use below code to solve my issue.
{$map: {
input: {
elt1: "$array1",
elt2: "$array2"
},
in: ["$elt1", "$elt2"]
}
Now can anyone please help me, it would be really be a great favor for me.
So say we have the following in the database collection:
> db.couponmodel.find()
{ "_id" : "a" }
{ "_id" : "b" }
{ "_id" : "c" }
{ "_id" : "d" }
and we wish to search for the following ids in the collections
var coupons_ids = ["c", "a" ,"z"];
We'll then have to build up a dynamic projection state so that we can project the correct indexes, so we'll have to map each id to its corresponding index
var conditions = coupons_ids.map(function(value, index){
return { $cond: { if: { $eq: ['$_id', value] }, then: index, else: -1 } };
});
Then we can then inject this in to our aggregation pipeline
db.couponmodel.aggregate([
{ $match : { '_id' : { $in : coupons_ids } } },
{ $project: { indexes : conditions } },
{ $project: {
index : {
$filter: {
input: "$indexes", as: "indexes", cond: { $ne: [ "$$indexes", -1 ] }
}
}
}
},
{ $unwind: '$index' }
]);
Running the above will now output each _id and it's corresponding index within the coupons_ids array
{ "_id" : "a", "index" : 1 }
{ "_id" : "c", "index" : 0 }
However we can also add more items in to the pipeline at the end and reference $index to get the current matched index.
I think you could do it in a faster way simply retrieving the array and search manually. Remember that aggregation don't give you performance.
//$match,$in,$and
$match:{
$and:[
{"uniqueID":{$in:["CONV0001"]}},
{"parentID":{$in:["null"]}},
]
}
}])
I'm sorry but I'm little confuse with a query , Kindly help. suppose we've one document that contains
{
"_id":100,
"name":"Demarcus Audette",
"scores":[
{
"score":47.42608580155614,
"type":"exam"
},
{
"score":44.83416623719906,
"type":"quiz"
},
{
"score":39.01726616178844,
"type":"homework"
},
"score":89.01726616178844,
"type":"homework"
}
]
}
And I want to write a query that should return only rows which contains homework in that , that means the out put should be like below
{
"_id":100,
"name":"Demarcus Audette",
"scores":[
{
"score":39.01726616178844,
"type":"homework"
},
"score":89.01726616178844,
"type":"homework"
}
]
}
Kindly suggest. Thanks in Advance
Use the $elemMatch operator.
db.collection.find({ "scores": { $elemMatch: { "type": "homework" } } } );
EDIT
What you are asking is not possible. You will need the above query and filter out the rest in whatever language you are programming. You can also use an aggregate function using $unwind and $match.
db.collection.aggregate(
{$unwind: "$messages"},
{$match: {"scores.type": "homework"}}
);
$unwind flattens your array and $match is your actually query which will return matching documents. Please note that $unwind will create a different document for each element in your array. This means you will get two results when you filter on 'homework' according to your example.
I just upgraded to Mongo 2.6.1 and one update statement that was working before is not returning an error. The update statement is:
db.post.update( { 'answers.comments.name': 'jeff' },
{ '$set': {
'answers.$.comments.$.name': 'joe'
}},
{ multi: true }
)
The error I get is:
WriteResult({
"nMatched" : 0,
"nUpserted" : 0,
"nModified" : 0,
"writeError" : {
"code" : 2,
"errmsg" : "Too many positional (i.e. '$') elements found in path 'answers.$.comments.$.createUsername'"
}
})
When I update an element just one level deep instead of two (i.e. answers.$.name instead of answers.$.comments.$.name), it works fine. If I downgrade my mongo instance below 2.6, it also works fine.
You CAN do this, you just need Mongo 3.6! Instead of redesigning your database, you could use the Array Filters feature in Mongo 3.6, which can be found here:
https://thecodebarbarian.com/a-nodejs-perspective-on-mongodb-36-array-filters
The beauty of this is that you can bind all matches in an array to a variable, and then reference that variable later. Here is the prime example from the link above:
Use arrayFilters.
MongoDB 3.5.12 extends all update modifiers to apply to all array
elements or all array elements that match a predicate, specified in a
new update option arrayFilters. This syntax also supports nested array
elements.
Let us assume a scenario-
"access": {
"projects": [{
"projectId": ObjectId(...),
"milestones": [{
"milestoneId": ObjectId(...),
"pulses": [{
"pulseId": ObjectId(...)
}]
}]
}]
}
Now if you want to add a pulse to a milestone which exists inside a project
db.users.updateOne({
"_id": ObjectId(userId)
}, {
"$push": {
"access.projects.$[i].milestones.$[j].pulses": ObjectId(pulseId)
}
}, {
arrayFilters: [{
"i.projectId": ObjectId(projectId)
}, {
"j.milestoneId": ObjectId(milestoneId)
}]
})
For PyMongo, use arrayFilters like this-
db.users.update_one({
"_id": ObjectId(userId)
}, {
"$push": {
"access.projects.$[i].milestones.$[j].pulses": ObjectId(pulseId)
}
}, array_filters = [{
"i.projectId": ObjectId(projectId)
}, {
"j.milestoneId": ObjectId(milestoneId)
}])
Also,
Each array filter must be a predicate over a document with a single
field name. Each array filter must be used in the update expression,
and each array filter identifier $[] must have a corresponding
array filter. must begin with a lowercase letter and not contain
any special characters. There must not be two array filters with the
same field name.
https://jira.mongodb.org/browse/SERVER-831
The positional operator can be used only once in a query. This is a limitation, there is an open ticket for improvement: https://jira.mongodb.org/browse/SERVER-831
As mentioned; more than one positional elements not supported for now. You may update with mongodb cursor.forEach() method.
db.post
.find({"answers.comments.name": "jeff"})
.forEach(function(post) {
if (post.answers) {
post.answers.forEach(function(answer) {
if (answer.comments) {
answer.comments.forEach(function(comment) {
if (comment.name === "jeff") {
comment.name = "joe";
}
});
}
});
db.post.save(post);
}
});
db.post.update(
{ 'answers.comments.name': 'jeff' },
{ '$set': {
'answers.$[i].comments.$.name': 'joe'
}},
{arrayFilters: [ { "i.comments.name": { $eq: 'jeff' } } ]}
)
check path after answers for get key path right
I have faced the same issue for the as array inside Array update require much performance impact. So, mongo db doest not support it. Redesign your database as shown in the given link below.
https://pythonolyk.wordpress.com/2016/01/17/mongodb-update-nested-array-using-positional-operator/
db.post.update( { 'answers.comments.name': 'jeff' },
{ '$set': {
'answers.$.comments.$.name': 'joe'
}},
{ multi: true }
)
Answer is
db.post.update( { 'answers.comments.name': 'jeff' },
{ '$set': {
'answers.0.comments.1.name': 'joe'
}},
{ multi: true }
)