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Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.

Enterprise Grafana Cloud

MongoDB query editor

Grafana provides a query editor for MongoDB that supports the same syntax as the MongoDB Shell (mongosh), but with some limitations:

  • You can only run one command or query per query
  • Only find and aggregate read commands are supported
  • ISODate is the only supported object constructor

For an introduction to writing scripts for the MongoDB shell see Write scripts in MongoDB’s documentation. You create a query in Grafana’s query editor in the same way you would in the MongoDB shell.

Example:

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})

Additional syntax

The editor extends the MongoDB Shell syntax by means of database selection, where you can use a database name instead of db. For example, sample_mflix.movies.find(). You can still use db to refer to the default database in your connection string.

It also extends it by means of aggregate sorting. Sorting typically happens within the aggregate pipeline. The extended syntax is allowed on aggregate similarly to find. For example, sample_mflix.movies.aggregate({}).sort({"time": 1}).

Note

MongoDB does not perform the sort with this syntax. The sort happens after the results are queried from the collection.

Collections with a dot

For collections containing a dot you can use the following syntax:

my_db.getCollection("my.collection").find({})

Keyboard shortcuts

Press Ctrl + Space to show code completion, which is displayed after entering a . after a database, collection, query method, or aggregation method name.

Cmd + S runs the query.

Query as time series

Make a time series query by aliasing a date field to time.

Note

You can coerce non-date fields into date fields and alias them to time to use them to make a time series query.

The following query converts 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})

If you want to group your time series by Metric, project a field called __metric.

The following query displays the count of movies over time by movie rating using __metric:

sample_mflix.movies.aggregate([
{"$match": { "year": {"$gt" : 2000}}},
{"$group": { "_id": {"year":"$year", "rated":"$rated"}, "count": { "$sum": 1 } }},
{"$project": { "_id": 0, "time": { "$dateFromParts": {"year": "$_id.year", "month": 2}}, "__metric": "$_id.rated", "count": 1}}
]
).sort({"time": 1})

Diagnostics

For information about diagnostics commands, see Diagnostic Commands.

This plugin supports the following MongoDB diagnostic commands:

  • buildInfo
  • connPoolStats
  • connectionStatus
  • dbStats
  • getLog
  • hostInfo
  • lockInfo
  • replSetGetStatus
  • serverStatus
  • stats

Macros

To simplify syntax and to allow for dynamic times, you can write queries that contain macros.

$__timeFrom
Will be replaced by the start of the currently active time selection converted to time data type.
$__timeTo
Will be replaced by the end of the currently active time selection converted to time data type.