I have defined a model like
Class Orders(Document):
orderAmount = fields.FloatField()
cashbackAmount = fields.FloatField()
meta = {'strict': False}
I want to get all orders where (orderAmount - cashbackAmount value > 500). I am using Mongoengine and using that I want to perform this operation. I am not using Django Framework so I cannot use solutions of that.
Let's approach this if you had to do this without Mongoengine. You would start by dividing this problem into two steps
1) How to get the difference between two fields and output it as the new field?
2) How to filter all the documents based on that field's value?
You can see that it consists of several steps, so it looks like a great use case for the aggregation framework.
The first problem can be solved using addFields and subtract operators.
{$addFields: {difference: {$subtract: ["$a", "$b"]}}}
what can be translated into "for every document add a new field called difference where difference=a-b".
The second problem is a simple filtering:
{$match: {difference:{$gt: 500}}}
"give me all documents where difference field is greater than 500"
So the whole query in MongoDB would look like this
db.collectionName.aggregate([{$addFields: {difference: {$subtract: ["$a", "$b"]}}}, {$match: {difference:{$gt: 500}}}])
Now we have to translate it into Mongoengine. It turns out that there is aggregate method defined, so we can easily make small adjustments to make this query work.
Diff.objects.aggregate({"$addFields": {"difference": {"$subtract": ["$a", "$b"]}}}, {"$match": {"difference":{"$gt": 500}}})
As a result, you get CommandCursor. You can interact with that object or just convert it to the list, to get a list of dictionaries.
Related
I'm trying to filter an influx DB query (using the nodeJS influxdb-client library).
As far as I can tell, it only works with "flux" queries.
I would like to filter out all records that share a specific attribute with any record that matches a particular condition. I'm filtering using the filter-function, but I'm not sure how I can continue from there. Is this possible in a single query?
My filter looks something like this:
|> filter(fn:(r) => r["_value"] == 1 and r["button"] == "1" ) and I would like to leave out all the record that have the same r["session"] as any that match this filter.
Do I need two queries; one to get those r["session"]s and one to filter on those, or is it possible in one?
Update:
Trying the two-step process. Got the list of r["session"]s into an array, and attempting to use the contains() flux function now to filter values included in that array called sessionsExclude.
Flux query section:
|> filter(fn:(r) => contains(value: r["session"], set: ${sessionsExclude}))
Getting an error unexpected token for property key: INT ("102")'. Not sure why. Looks like flux tries to turn the values into Integers? The r["session"] is also a String (and the example in the docs also uses an array of Strings)...
Ended up doing it in two queries. Still confused about the Strings vs Integers, but casting the value as an Int and printing out the array of r["session"] within the query seems to work like this:
'|> filter(fn:(r) => not contains(value: int(v: r["session"]), set: [${sessionsExclude.join(",")}]))'
Added the "not" to exclude instead of retain the values matching the array...
sorry for the noob question.
I'm trying to write the CRUD endpoints for a Friendship model, which holds two users' IDs.
To create a Friendship the first thing I want to do is check if there is already an instance of that model, which would hold both IDs in any given order, so I wrote:
Friendship.findOne.all({users: [user1.id, user2.id]})
.then(.....
But the server responds with a 500 error: Friendship.findOne.all is not a function
What would be the proper way to do this?
I am assuming that you want to check if both id records/documents are present in your collection or not so for that you use $in operator like this
Friendship.find({id: {$in : [user1.id, user2.id]} })
.then(.....
This will return an array of records if any of id records will be present. And it will return empty array if non of the id records will present in your db
In Marklogic, I want to search between two collections by joining the id element of doc from collection1 to id element of doc from collection2. When it is matched i need the resulting document from both collections.
I have the below code, but it is very slow. How to use cts:search or search:search to achieve the same
for $i in collection('demographic')/individual,
$j in collection('membership')/membership[enrolleIndividualId/id/text() = $i/individual/id/text()])
return {$i,$j}
Update:
I should note that your sample is not valid XQuery: return element root { $i, $j } would be valid. Also, you should not use the /text() node selector, as it's behavior can be counterintuitive. You can compare elements directly in an XPath predicate ([enrolleIndividualId/id eq $i/individual/id]). Use /fn:string() in place of /text() if you need the contents of an element as a string. I'd also recommend using the atomic equality operator eq in place of the sequence equality operator = when directly comparing individual elements.
Original Answer:
There are several approaches to implementing joins in MarkLogic, but I would first question your data model. From the names of the elements in your sample query, it looks like you are using a relational model (individuals have memberships). MarkLogic is a document database, and it's optimized for denormalized documents. You will be much better served to process your data and generate new individual documents that each contain the relevant membership data.
That being said, here's how you could join your documents:
First, you will need range indices to write performant joins. If the id element from your sample query is not unique to individuals, you will need path range indices on enrolledIndividualId/id and individual/id, otherwise, a simple element range index on id will do.
The most common join pattern in MarkLogic uses a "shotgun-OR" query; first retrieving values from the lexicon backing a range index, and then constructing an or-query from those values to retrieve the relevant documents. This won't work directly in your case, as you want to retrieve both sides of the join. You can either run a search for each pair of documents, or run a single search for one side, and then an additional document read for each document.
pairs:
for $value in cts:values(cts:path-reference("individual/id"))
return
cts:search(/,
cts:or-query((
cts:and-query((
cts:collection-query("demographic"),
cts:path-range-query("individual/id", "=", $value))),
cts:and-query((
cts:collection-query("membership"),
cts:path-range-query("enrolledIndividualId/id", "=", $value))))),
"unfiltered")
shotgun-OR plus iteration:
for $doc in
cts:search(/,
cts:and-query((
cts:collection-query("demographic"),
cts:path-range-query("individual/id", "=",
cts:values(cts:path-reference("individual/id"))))),
"unfiltered")
return
cts:search(/,
cts:and-query((
cts:collection-query("membership"),
cts:path-range-query("enrolledIndividualId/id", "=", $doc/individual/id))),
"unfiltered")
As you can see, each approach requires I/O proportionate to the number of docs/values you want to join. If you only needed the shotgun-OR (ie, a query for documents based on criteria from other documents), you would only need to make two requests, the initial cts:values() call to retrieve values from a lexicon, and the cts:search() call using a query built from those values.
Note: the cts:query objects used in these examples could be used in conjunction with the Search API by means of the search:resolve() function.
Given your apparent data model, you will be much better served by processing your data into individual, de-normalized documents.
Considering:
doc profile
{
_id:"1",
name:"john",
likes: ["2222","1111"]
}
doc likes
{
_id:"2222",
value:"true"
}
{
_id:"1111",
value:"false"
}
I have a filter on my xamarin app to get the profile, and it works well but I need to include the "children" (linked) docs... I can do this with a view setting include_docs=true but I want couchdb to filter so I can use replication.
Also, it would be possible to accomplish the same result if I could use a reduce function to filter data, but I can't make the filter use the reduce function.. So, any idea?
the expected result would be:
doc profile
{
_id:"1",
name:"john",
likes: {
{_id:"2222",
value:"true"},
{_id:"1111",
value:"false"]
}
}
Thanks!
I can do this with a view setting include_docs=true but I want couchdb to filter so I can use replication
You might already know this but you can use couchdb views as filters.
Also, it would be possible to accomplish the same result if I could use a reduce function to filter data
The reduce function is for "reducing" the values that are returned by the map function. The map function returns a key and a value like so:
emit(key,value)
The reduce function only gets the keys and the values that are returned from a map function. For example if you call a view with
?key=abc
and it returns results like
[{
_id:...,
type: abc
},
{
_id:...,
type:abc
}
....
]
You already have all the documents filtered by the key "abc". The reduce function will get as inputs the key, the value and a rereduce parameters. If you use the reduce function as a post map processing step to further filter the results from the view there will be two problems:
There is no way to pass a parameter to a reduce. The keys that you specify will only be used by the map function and then passed as they are to reduce.
It is not a good idea anyway. With reduce you want to return a small value that aggregates the results you get from a view. So taking the above example if you return say an integer as a value from the map function ( in emit(key,value)//suppose that the value is an integer) the reduce function may return a sum or aggregate of those values. But trying to return a modified document is not what reduce function is for. From the docs
"A reduce function must reduce the input values to a smaller output value. If you are building a composite return structure in your reduce, or only transforming the values field, rather than summarizing it, you might be misusing this feature. "
List functions might be more suited to what you are trying to do. If you want to process the results of the view query before returning them they are they way to go.
In list functions you get a set of results returned by the view function. You can even pass additional parameters if you'd like to apply complex filters on them. But you won't be able to use list functions for replication.
Finally replication works on a document level. Documents have _rev fields that is used by the replicator process to check what version the document is in before the replication is performed. So you won't be able to replicate the results returned by a view. Only the documents will be replicated.
location: {lat: Number,
lng: Number}
location is a 2d index in my mongodb and I have been using this for geospatial search, which is working fine.
Now if I need to search as db.find({lat:12.121212, lng:70.707070}), will it use the same index ? or, do I need to define a new index ? If so, how ?
I am using mongoose driver in node.js
The 2d index used for doing the geospatial commands is not going to help for an equivalency match on the two fields. For that you will need to define a compound index on the two sub-documents, something like this:
db.collection.ensureIndex({"location.lat" : 1, "location.lng" : 1})
This worked best for me with a test set of data - you can also define a normal index on the location field itself but that will be less efficient. You can test out the relative performance using hint and explain for any index combination. For example:
db.collection.find({"location.lat" : 179.45, "location.lng" : 90.23}).hint("location.lat_1_location.lng_1").explain()
You can do this for any index you wish in fact, though to check the results returned you will need to drop the .explain()
Please also bear in mind that a query can only use one index at a time, so if you are looking to combine the two (equivalency and a geospatial search) then the 2d index will be the only one used.
Note: all of the above examples are from the MongoDB JS shell, not node.js