Query

Example

The examples on this page use the Sample AirBnB Listings Dataset. You can download the raw data from listingsAndReviews.json.

Query Language

Write queries as a MongoDB aggregation pipeline — an array of pipeline stages — directly in the Query Editor. Both JSON and JavaScript object syntax are supported.

JSON

Standard JSON syntax. All keys and string values must be quoted.

[
  {
    "$match": {
      "property_type": "Apartment"
    }
  },
  {
    "$limit": 10
  },
  {
    "$project": {
      "name": 1,
      "listing_url": 1
    }
  }
]

JavaScript

JavaScript object syntax allows unquoted keys and supports inline expressions, which can be useful for dynamic or computed values.

[
  {
    $match: {
      property_type: 'Apartmen' + 't',
    },
  },
  {
    $limit: 2 + 4,
  },
  {
    $project: {
      name: 1,
      listing_url: 1,
    },
  },
];

Warning

JavaScript expression support is partial, provided by mongodb-query-parser. Complex expressions may not evaluate as expected.

---

Common Query Patterns

Filter by Dashboard Time Range

Use the built-in variables $__from and $__to to filter documents within the dashboard's selected time range. Both variables represent Unix timestamps in milliseconds.

[
  {
    "$match": {
      "last_scraped": {
        "$gt": { "$date": { "$numberLong": "$__from" } },
        "$lt": { "$date": { "$numberLong": "$__to" } }
      }
    }
  },
  {
    "$project": {
      "name": 1,
      "listing_url": 1,
      "description": 1
    }
  },
  {
    "$limit": 10
  }
]

Count Documents Over Time

Group documents by a date field and count each bucket. This is the foundation for visualizing time series data in Grafana.

The example below groups listings by the month of their first_review date:

[
  {
    "$group": {
      "_id": {
        "$dateToString": { "format": "%Y-%m", "date": "$first_review" }
      },
      "count": { "$count": {} }
    }
  },
  {
    "$project": {
      "_id": 0,
      "ts": { "$toDate": "$_id" },
      "count": 1
    }
  }
]

Adjust the format string to control the granularity of your time buckets:

Granularity	Format String
Year	%Y
Month	%Y-%m
Day	%Y-%m-%d
Hour	%Y-%m-%dT%H

Break Down by Category

To plot multiple categories (e.g. one line per property type) on the same time series chart, include the category field in the group key alongside the date.

[
  {
    "$group": {
      "_id": {
        "month": {
          "$dateToString": { "format": "%Y-%m", "date": "$first_review" }
        },
        "property_type": "$property_type"
      },
      "value": { "$count": {} }
    }
  },
  {
    "$project": {
      "_id": 0,
      "ts": { "$toDate": "$_id.month" },
      "name": "$_id.property_type",
      "count": "$value"
    }
  }
]

Because the plugin returns a single data frame, you need to split it by category using Grafana's built-in transformation:

1. Open the Transform tab in your panel editor.
2. Add the "Partition by values" transformation.
3. Set the field to name.

Each category will now appear as a separate series on your visualization.

Info

Prior to v0.5, the plugin handled category partitioning automatically when the "time series" query type was selected. This was removed in v0.5 in favor of using Grafana's native Data Transformations, which offer greater flexibility.