Connect to a MongoDB data source
The MongoDB Data source enables you to visualize data from MongoDB in Amazon Managed Grafana.
Note
This data source is for Grafana Enterprise only. For more information, see Manage access to Enterprise plugins.
Additionally, in workspaces that support version 9 or newer, this data source might require you to install the appropriate plugin. For more information, see Extend your workspace with plugins.
Usage
Query editor
The query editor supports the same syntax as the MongoDB Shell, with some limitations: * You can only run one command/query. * Only read commands are supported: find and aggregate * Most Object constructors are not supported (with the exception of ISODate, which is supported)
The editor expands upon the MongoDB Shell syntax in the following ways:
-
Database selection – You can supply the name of the database in place of the normal "db":
Note
You can still use "db". It will refer to the default database in your connection string.
sample_mflix.movies.find() -
Aggregate sorting – Normally sorting happens with a step within the aggregate pipeline, however the MongoDB Atlas free tier doesn’t allow sorting. We have expanded the syntax to allow it for those using the free tier.
Note
MongoDB doesn’t perform the sort with this syntax. The sort happens after the results are queried from the collection.
sample_mflix.movies.aggregate({}).sort({"time": 1}) -
With a blank editor, Ctrl + Space will show a selection of all the available databases.
-
Entering a dot after the database will show a selection of all the available collections for that database.
-
Entering a dot after the collection will show the available query methods.
-
Entering a dot after the query method will show additional functions: sort/limit.
Running the query
Press Cmd + S to run the query
Time series
When visualizing time series data, the plugin needs to know which field to use as the time. Simply project the field with a name alias of "time". The field data type must be a date.
You can coerce non-date data types to date. Doing so will allow using non-date fields as the time series time. The following example shows how to convert the int field "year" to a date that is projected as "time" using the MongoDB $dateFromParts pipeline operator.
sample_mflix.movies.aggregate([ {"$match": { "year": {"$gt" : 2000} }}, {"$group": { "_id": "$year", "count": { "$sum": 1 }}}, {"$project": { "_id": 0, "count": 1, "time": { "$dateFromParts": {"year": "$_id", "month": 2}}}} ] ).sort({"time": 1})
Diagnostics
The following diagnostic commands are currently supported: "stats", "serverStatus", "replSetGetStatus", "getLog", "connPoolStats", "connectionStatus", "buildInfo", "dbStats", "hostInfo", "lockInfo"
Examples:
admin.connectionStatus() // run the connectionStatus command admin.connectionStatus({"authInfo.authenticatedUserRoles": 1}) // run and only return the "authInfo.authenticatedUserRoles" field admin.connPoolStats({arg: "pool"}) // run the connPoolStats command and pass 1 argument admin.serverStatus({args: {repl: 0, metrics:0}}) // run the serverStatus command and pass multiple args
Macros
You can reference the dashboard time range in your queries.
-
$__timeFrom— a macro that references the dashboard start time -
$__timeTo— a macro that references the dashboard end time
$__timeTo - ``` sample_mflix.movies.find({released: {$gt: "$__timeFrom"}}).sort({year: 1})
Template variables
MongoDB supports the idea of "Compound Variables", which enable you to use one variable as multiple variables to perform complex multi-key filters.
To create a Compound Variable, use the naming convention of breaking
the variables up by using underscores (must start with underscore):
_var1_var2 When querying, the response must be in the
format: val1-val2
Example: I want to filter results on both movie name and year.
-
Create a variable of type Query:
_movie_year -
Set the variable query to a query that will return an array of items with one movie-year property, as shown in the following example.
// Example sample_mflix.movies.aggregate([ {"$match": {year: {"$gt": 2011}}}, {"$project": {_id: 0, movie_year: {"$concat": ["$title", " - ", {"$toString":"$year"}]}}} ])// [{"movie-year": "Ted - 2016"}, {"movie-year": "The Terminator - 1985"}] -
Now in your query, you can reference "Movie" and "Year" as separate template variables using the syntax "$_variable".
Using ad-hoc filters
In addition to the standard "ad-hoc filter" type variable of any name, a second helper variable must be created. It should be a "constant" type with the name `mongodb_adhoc_query` and a value compatible with the query editor. The query result will be used to populate the selectable filters. You can choose to hide this variable from view as it serves no further purpose.
sample_mflix.movies.aggregate([ {"$group": { "_id": "$year"}}, {"$project": { "year": "$_id","_id": 0 }} ] )
