I have produced some results through mongodb aggregation framework. So now I need to get those results to a file(text or any other format).
How can I achieve this ?
Check the $out operator in aggregation framework.
$out operator takes the documents returned by the aggregation pipeline and writes
them to a specified collection. The $out operator lets the aggregation
framework return result sets of any size. The $out operator must be
the last stage in the pipeline.
The command has the following syntax, where is
collection that will hold the output of the aggregation operation.
$out is only permissible at the end of the pipeline:
db.<collection>.aggregate( [
{ <operation> },
{ <operation> },
...,
{ $out : "<output-collection>" }
] )
Check my answer to a previous question how to export output of the aggregation framework to a new collection. After exporting to a new collection you can simply do mongodump.
Related
My mongo version is 3.4
I'm running a complex aggregation and writing the result to a collection using $out stage.
What I wish to do is, if that aggregation is ran before and result exists on target collection, just return the saved result without rerunning the whole pipeline.
Problem 1 is, when $out is used, aggregation doesn't return any results, so I have to send a separate query to the target collection to retrieve them.
Problem 2 is, I need another query to check if aggregation is ran before.
Is it possible to combine all 3 queries to a single pipeline, so it would:
check outCollection, if result with given user_id exists, return it
if doesn't, run pipeline and save the result to outCollection
return aggregation result
my current pipeline looks like:
db.getCollection('sourceCollection').aggregate([
{
$match: {
user_id: "myUserId"
}
},...//perform various steps
{
$out: "outCollection"
}],{
allowDiskUse: true
})
Result is saved to outCollection in a document like:
{ user_id: "myUserId", aggResult: [...] }
I have been reading up on some mongodb documentation and ran across some confusing terminology, namely how to differentiate when a symbol will be used as an aggregate function or as an operator.
For example, the $size function either calculates the number of items in an array, or checks if the number of elements in an array is equal to a number, is there any way to know what the function will do at what time? Through trial and error I discovered that the $size will throw an error unless a number is passed to it in the $match step, but is there some rule/guideline so I can know what it will do beforehand?
db.collection.aggregate([
{
$project: {
key: 1,
number: {
$size: "$key"
}
}
},
{
$match: {
key: {
$size: 1
}
}
}
])
For querying data in MongoDB you can use the find method or the aggregate method. There are operators which you can use with these methods.
These query operators are used with the find method. Some of these can also used with the $match stage of the aggregate method (details later in the post).
These aggregation pipeline operators are used within the aggregate's stages. Some of these can also be used with the find method (details later in the post).
You will notice that, there are common operator names; for example, $eq, $gte, $or, $type, $size, etc. But, their usage and / or functionality can be different. The $eq operator has same function but different usage syntax and the $typeoperator has different functionality (and usage syntax).
And, some of these operators can be used with both the methods.
Some Usage Scenarios:
Lets consider a users collection and some queries:
{ "_id" : 1, "age" : 21, "firstname" : "John" }
{ "_id" : 2, "age" : 18, "firstname" : "John" }
{ "_id" : 3, "age" : "39", "firstname" : "Johnson" }
The query:
db.users.find( { firstname: { $eq: "John"}, age: { $gt: 20 } } )
This query's filter is same as { firstname: "John"}, age: { $gt: 20 } }. This uses the query operators $eq and $gt. The same query can be written in the aggregate method's $match stage:
db.users.aggregate([
{ $match: { firstname: "John", age: { $gt: 20 } } },
])
The operators used in this case are the same query operators. The query comparison operators can be used with the aggregate method's $match and $lookup stages.
Another Scenario:
db.users.aggregate([
{ $project: { ageGreaterThan20: { $gt: [ "$age", 20 ] } } },
])
This is the usage of aggregation comparison operator $gt. Note this is used within the aggregation query, but within the $project stage.
As you had used the query operators in the aggregation query, you can also use the aggregation operators within the find method. But, this must be used with the "special" $expr operator. For example:
db.users.find( { $expr: { $gt: [ "$age", 20 ] } } )
The advantage of the $expr is that - there are number of aggregation operators which can be used within the find queries. For example, using the $strLenCP:
db.users.find( { $expr: { $gt: [ { $strLenCP: "$firstname" }, 4 ] } } )
You can also use the $expr within the aggregation, within the $match or $lookup stages:
db.users.aggregate([
{ $match: { $expr: { $gt: [ "$age", 20 ] } } },
])
Finally:
I have been reading up on some mongodb documentation and ran across
some confusing terminology, namely how to differentiate when a symbol
will be used as an aggregate function or as an operator. ... but is
there some rule/guideline so I can know what it will do beforehand?
Reading helps, practicing helps better and experience helps the best. You use a specific operator in a specific scenario or use case. To achieve some functionality you use an appropriate method and operator(s).
Reference: Operators
As per my understanding, I'm pointing out few things :
Difference between aggregation and operator
You'll have certain basic functions for crud operations like .find() or .insert() or .delete() or .update() on MongoDB (There are few others like .count(), .distinct() but those are primary)
Versus
aggregation is a whole framework heavily used for complex reads, only two stages in aggregation is capable of writes $out and $merge.
Operators :
There are different types of operators :
Query and Projection Operators : These operators are crucial and are used to filter docs and to transform fields of docs in the response, Usually used in filter and project part of .find(filter, project) or .update(filter, update, project/options) etc.. These are also used in $match stage of aggregation pipeline ($match is similar to filter in .find()). Ex. :- $and, $or, $in, $or & more.
Update Operators : By name, these operators help to update documents in the collection. Usually used in update part of .update() or .findOneAndUpdate() etc.. Ex. :- $set, $unset, $inc & more.
Aggregation :
When it comes to aggregation they call it aggregation framework, definitely for a reason as you can do a lot of things with data using aggregation.
Aggregation has aggregation pipeline , which has syntax .aggregate([]). pipeline is an array with stages. Each stage in aggregation does certain operation on data flowing through them. Ex. :- $match, $project, $group etc..
As we know each document is independent on it's own, most of aggregation stages operate independently on each doc flowing through them.
Aggregation pipeline Operators :
These operators are generally used to achieve what you're looking for, certain operators can't be used in conjunction with other operators or in a stage.
Let's say in $match stage you would mostly use Query operators but not Aggregation operators as aggregation operators can't directly be used in $match in contrast with $project or $addFields stages.
Example with Stages & Operators :
Let's say you got to make Smoothie :
Out of a bunch of groceries you would filter needed fruits(docs in fruits collection) by matching with what you wanted to blend using $match stage ($and to match fruits/veggies, $lt to filter only fruits that hasn't expired and $size to limit no.of fruits needed).
You would peel off skin or chop into pieces to keep just keep useful parts of fruits(docs) using $project.
You would group all of the fruits into a blender using $group & add ingredients like cream & sugar using $addFields - You're too cautious about sugar quantity so you'll use operators like $size to check size and $multiply no.of nutrients based on conditions ($cond) you would $divide both sugar/nutrients to count nutrition value.
You'll iterate on adding ice pieces again and again using $map, $filter to remove un crushed ice pieces.
uhh, you always forget to add veggies (A different collection needs to be merged) based on fruits that already got blended you use $lookup to lookup for matching veggies(docs) & either blend in again with group or just put it on top.
Finally either you drink it from blender (just return the docs no more stages) or take into glass using $out or $merge stage (Remember as I said, only two stages that can write to a collection).
Off course every stage is Optional - You can eat fruits as is instead of blending (get all docs and all their fields) but you know what you wouldn't do that (for many reasons like performance, unnecessary data flowing through network) unless it's pre-prepared product (like a small configuration collection which has limited data with few docs & every doc is need & can be easily retrieved in one DB call).
Note :
Usually you can't use aggregation operators in filter part i.e; .find(filter) or in '$match' stage unless you use $expr.
Starting MongoDB v4.2 you can run aggregation pipeline in update-with-an-aggregation-pipeline where you can take advantage of aggregation stages/operators in update part.
While you search MongoDB's documentation often you would find the same operator in multiple places, Let's say if you search for $size you would find multiple references one is Query operator or as Projection operator or as aggregation operator - So depends on need/where you wanted to use you can refer their documentation for usage cause though name seems to be similar or does almost same but functionality may differ & syntax also differs.
You can always MongoDB for free at MongoDB University.
Can anyone tell me how to add a $match stage to an aggregation pipeline to filter for where a field MATCHES a query, (and may have other data in it too), rather than limiting results to entries where the field EQUALS the query?
The query specification...
var query = {hello:"world"};
...can be used to retrieve the following documents using the find() operation of MongoDb's native node driver, where the query 'map' is interpreted as a match...
{hello:"world"}
{hello:"world", extra:"data"}
...like...
collection.find(query);
The same query map can also be interpreted as a match when used with $elemMatch to retrieve documents with matching entries contained in arrays like these documents...
{
greetings:[
{hello:"world"},
]
}
{
greetings:[
{hello:"world", extra:"data"},
]
}
{
greetings:[
{hello:"world"},
{aloha:"mars"},
]
}
...using an invocation like [PIPELINE1] ...
collection.aggregate([
{$match:{greetings:{$elemMatch:query}}},
]).toArray()
However, trying to get a list of the matching greetings with unwind [PIPELINE2] ...
collection.aggregate([
{$match:{greetings:{$elemMatch:query}}},
{$unwind:"$greetings"},
]).toArray()
...produces all the array entries inside the documents with any matching entries, including the entries which don't match (simplified result)...
[
{greetings:{hello:"world"}},
{greetings:{hello:"world", extra:"data"}},
{greetings:{hello:"world"}},
{greetings:{aloha:"mars"}},
]
I have been trying to add a second match stage, but I was surprised to find that it limited results only to those where the greetings field EQUALS the query, rather than where it MATCHES the query [PIPELINE3].
collection.aggregate([
{$match:{greetings:{$elemMatch:query}}},
{$unwind:"$greetings"},
{$match:{greetings:query}},
]).toArray()
Unfortunately PIPELINE3 produces only the following entries, excluding the matching hello world entry with the extra:"data", since that entry is not strictly 'equal' to the query (simplified result)...
[
{greetings:{hello:"world"}},
{greetings:{hello:"world"}},
]
...where what I need as the result is rather...
[
{greetings:{hello:"world"}},
{greetings:{hello:"world"}},
{greetings:{"hello":"world","extra":"data"}
]
How can I add a second $match stage to PIPELINE2, to filter for where the greetings field MATCHES the query, (and may have other data in it too), rather than limiting results to entries where the greetings field EQUALS the query?
What you're seeing in the results is correct. Your approach is a bit wrong. If you want the results you're expecting, then you should use this approach:
collection.aggregate([
{$match:{greetings:{$elemMatch:query}}},
{$unwind:"$greetings"},
{$match:{"greetings.hello":"world"}},
]).toArray()
With this, you should get the following output:
[
{greetings:{hello:"world"}},
{greetings:{hello:"world"}},
{greetings:{"hello":"world","extra":"data"}
]
Whenever you're using aggregation in MongoDB and want to create an aggregation pipeline that yields documents you expect, you should always start your query with the first stage. And then eventually add stages to monitor the outputs from subsequent stages.
The output of your $unwind stage would be:
[{
greetings:{hello:"world"}
},
{
greetings:{hello:"world", extra:"data"}
},
{
greetings:{hello:"world"}
},
{
greetings:{aloha:"mars"}
}]
Now if we include the third stage that you used, then it would match for greetings key that have a value {hello:"world"} and with that exact value, it would find only two documents in the pipeline. So you would only be getting:
{ "greetings" : { "hello" : "world" } }
{ "greetings" : { "hello" : "world" } }
I have the following code based upon this question
How to efficiently perform "distinct" with multiple keys?:
collection = db.products;
result = collection.aggregate(
[
{"$group": { "_id": { "P1 Connection": "$p1c", "P1 Size": "$p1s" } } },
{"$match" : {"parentGUID":ObjectId("5509b246c519ce4b900138a3")}}
]
)
printjson(result);
The printjson statement only prints a bunch of code, and not an object. I also tried result() but that got the following error:
> result()
2015-10-29T10:31:14.892-0400 TypeError: Property 'result' of object #<Object> is not a function
How do I get the results of this aggregation? It looks like it may be possible to do this if I put my code in a file and run that, but I am having a hard time believing that there is no quick and dirty way to run this query in the mongodb command prompt.
Move the $match pipeline step to the very beginning, this will filter the documents that get into the pipeline and the $group pipeline stage will then run the pipeline with the correct documents. Since MongoDB 2.6 adds support for returning a cursor for the aggregate() method, you would need to iterate over the cursor using the forEach() method and access the documents, as in the following example:
var pipeline = [
{"$match" : {"parentGUID":ObjectId("5509b246c519ce4b900138a3")}},
{"$group": { "_id": { "P1 Connection": "$p1c", "P1 Size": "$p1s" } } }
];
var results = db.products.aggregate( pipeline );
results.forEach(printjson);
I want to save the aggregation framework result to a new collection.
I know that's impossible with the framework at the moment with the command itself.
Is there a workaround in the shell?
Starting with Mongo 2.6.0 you can do this natively without any additional manipulation.
db.<collection>.aggregate( [
{ <operation> },
{ <operation> },
...,
{ $out : "<output-collection>" }
] )
Check the new aggregation operator $out for more detailed example.
P.S. using this way you are not limited to 16Mb size.
Update: See Salvador's answer for a more efficient way to do this in MongoDB 2.6+.
Save the aggregation result in a variable and then insert its result property into a new collection:
var result = db.foo.aggregate(...);
db.bar.insert(result.result);
result.result is no longer working, try toArray().
var result = db.coll.aggregate(...);
db.bar.insert(result.toArray());