MongoDB Queries
These queries are converted to MongoDB filters and aggregations by MongoQueryProducer.
Last updated
Core Platform
These queries are converted to MongoDB filters and aggregations by MongoQueryProducer.
Last updated
These queries support all available query types and convert them to Bson maps or lists for execution. Pipeline queries are treated as aggregate pipelines and bundled queries are treated as facets.
MongoDB specific features for special use cases are as follows:
matchAfterJoin
Whether the where condition should execute after joins or before (i.e. on main collection), defaults to false
pipe
Whether the query should be generated as an aggregate pipeline instead of a find query
MongoDB query manager translates joins into $lookup statements, with 2 alternative methods:
The simple lookup method uses only a simple "EQ" type condition, where localField of "from" collection maps to "Expression" and foreignField of "join" collection maps to "Value".
The complex method uses pipeline feature of MongoDB lookups, where 2 alternative approaches can be used:
With this approach, lookup pipeline can be manually configured using the following condition parameters:
let
Map of variables to expressions as "let" statement in "$lookup" stage (e.g. {"id":"$_id"})
pipeline
List of steps for "pipeline" to run on joined collection in "$lookup" stage (as array node or string)
When a complex condition is used for joining with a collection in query designer (e.g. using AND, OR or anything other than EQ operator), MongoDB query manager automatically translates the join into a pipeline based lookup. This option allows using regular conditions (including ability to use parameters such as required variables), which will be automatically translated into $match statements.
When using this approach, it is possible to add the following parameters:
let
Map of variables to expressions as "let" statement in "$lookup" stage (e.g. {"id":"$_id"})
extra
List of steps for adding to "pipeline" after the produced $match statement (as array node or string)
Following parameters are applicable in various building blocks of a MongoDB query:
mongo
Json object to be used as the field expression
mongo.inject
Whether "mongo" parameter should be injected with variables
mongoJson
Json string to be used as the field expression
Whether "mongoJson" parameter should be parsed into a json object before injection
mongoJson.inject
Whether "mongoJson" parameter should be injected with variables
For both custom simple and aggregation fields, "Common Mongo Parameters" are applicable.
For simple conditions, MongoDB supports following custom operators:
value: Uses "filter" parameter (e.g. $eq) as the check between rhs and lhs values of the condition.
values: Same as value operator, accepting multiple values as the rhs.
bson: Uses "Common Mongo Parameters" to build a Bson statement as the condition.
It is also possible to use any mongodb operator (e.g. $exists) as a custom operator, which uses a single rhs value (e.g. "true") along with the lhs (e.g. data.records).
MongoDB Java driver automatically hides "$and" operator in certain scenarios in older versions of the library (i.e. when multiple entries with same key doesn't exist). This can result in issues in rare complex condition scenarios (e.g. $not allowed as a root level operator). In such case, conditions inside the AND operator can be written as custom expressions instead.
For pipeline steps, MongoDB supports following types:
custom: Pipeline step is produced directly from "Common Mongo Parameters" of the step content.
condition: Step content represents "where" condition of a query.
join: Step content represents "join" condition of a query.
select: Step content represents "fields" of a simple query.
aggregate: Step content represents "fields" of an aggregation query.
orderBy: Step content represents "orderBy" of a query.
skip: Uses "value" text field of the step content to skip number of records.
limit: Uses "value" text field of the step content to limit number of records.
