Dashboard Query Reference

This reference guide details the YAML configuration syntax (DSL) used for widget queries, layout sizing, and calculations in the Dashboard plugin.

Widget Queries

Widgets load data through query. The same query shape supports raw rows, grouped aggregate rows, per-measure filters, ordering, and calculated fields.

query:
  resource: cars
  select:
    - field: body_type
      as: body_type
    - agg: count
      as: total_cars
    - agg: avg
      field: price
      as: avg_price
  group_by:
    - body_type
  order_by:
    - field: total_cars
      direction: desc

Step-based charts use a steps query when each step needs its own resource, measure, and filters. Funnel charts can also use this query shape; like every other chart, they accept a single-resource query as well.

Depending on the widget, query can also use limit, offset, calcs, bucket, and formatting.

Widget-scoped constants can be defined with variables. They are available inside query.calcs through lookup($variables.path, field, default).

label: Average Car Price by Database
target: chart
variables:
  price_multipliers:
    cars_sl: 0.84
    cars_mysql: 1.12
chart:
  type: bar
  x:
    field: name
  y:
    field: adjusted_value
query:
  source: steps
  steps:
    - name: SQLite
      resource: cars_sl
      select:
        - agg: avg
          field: price
          as: value
    - name: MySQL
      resource: cars_mysql
      select:
        - agg: avg
          field: price
          as: value
  calcs:
    - calc: value * lookup($variables.price_multipliers, resource, 1)
      as: adjusted_value

Define variables on each widget config. Dashboard root variables are not merged into widget data queries.

Widget Examples

The examples below are widget configs as they appear in the dashboard widget editor. When you edit the whole dashboard_configs.config record directly, every widget also needs its persisted id, group_id, and order fields.

Table

label: Latest Cars
target: table
size: wide
height: 360
table:
  columns:
    - model
    - price
    - body_type
    - production_year
  page_size: 10
query:
  resource: cars
  select:
    - field: model
    - field: price
    - field: body_type
    - field: production_year
  order_by:
    - field: production_year
      direction: desc

Table widgets use pagination by default. Set table.page_size to choose how many rows each request loads, or table.pagination to false to request all rows at once.

Pie Chart

label: Cars by Body Type
target: chart
size: medium
height: 360
chart:
  type: pie
  label:
    field: body_type
  value:
    field: value
query:
  resource: cars
  select:
    - field: body_type
    - agg: count
      as: value
  group_by:
    - body_type

Bar Chart

label: Cars by Production Year
target: chart
size: wide
height: 360
chart:
  type: bar
  x:
    field: production_year
  y:
    field: value
query:
  resource: cars
  select:
    - field: production_year
    - agg: count
      as: value
  group_by:
    - production_year

Chart With Multiple Sources

Use query.source: steps when chart data comes from different resources. Each step returns one row with name, resource, and the selected aggregate aliases.

label: Sales Funnel
target: chart
size: large
height: 360
chart:
  type: funnel
  title: Sales funnel
query:
  source: steps
  steps:
    - name: Leads
      resource: leads
      select:
        - agg: count
          as: value
    - name: Qualified
      resource: leads
      select:
        - agg: count
          as: value
      filters:
        and:
          - field: status
            eq: qualified
    - name: Customers
      resource: orders
      select:
        - agg: count_distinct
          field: customer_id
          as: value

For the same numeric buckets across multiple resources, add query.bucket and render the result as a stacked bar chart. The dashboard runs every step once per bucket and returns rows with label, name, resource, and the aggregate aliases:

label: Cars by Price Range and Database
target: chart
size: wide
height: 360
chart:
  type: stacked_bar
  x:
    field: label
  y:
    field: count
  series:
    field: name
query:
  source: steps
  bucket:
    field: price
    buckets:
      - label: Budget
        max: 3500
      - label: Mid-range
        min: 3500
        max: 7000
      - label: Premium
        min: 7000
  steps:
    - name: SQLite
      resource: cars_sl
      select:
        - agg: count
          as: count
    - name: MySQL
      resource: cars_mysql
      select:
        - agg: count
          as: count

KPI Card

label: Average Car Price
target: kpi_card
size: small
card:
  value:
    field: value
    prefix: $
query:
  resource: cars
  select:
    - agg: avg
      field: price
      as: value

Gauge Card

label: Average Car Price
target: gauge_card
size: small
card:
  value:
    field: value
    suffix: $
  target:
    field: max
  color: '#2563eb'
query:
  resource: cars
  select:
    - agg: avg
      field: price
      as: value
    - agg: max
      field: price
      as: max

Pivot Table

label: Cars Summary by Body Type
target: pivot_table
size: full
height: 420
pivot:
  rows:
    - body_type
  values:
    - field: total_cars
    - field: avg_price
query:
  resource: cars
  select:
    - field: body_type
    - agg: count
      as: total_cars
    - agg: avg
      field: price
      as: avg_price
  group_by:
    - body_type

Aggregation aliases such as total_cars and avg_price become table columns.

Layout

Widgets support these layout fields:

size: small
width: 320
height: 360
min_width: 240
max_width: 640

size can be small, medium, large, wide, or full. Explicit width, height, min_width, and max_width can be used when a widget needs more precise sizing.