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Metrics View YAML

In your Rill project directory, create a metrics view, <metrics_view>.yaml, file in the metrics directory. Rill will ingest the metric view definition next time you run rill start.

Properties​

version - Refers to the version of the metrics view (required).

type — Refers to the resource type and must be metrics_view (required).

title — Refers to the display name for the metrics view (required).

description - A description for the project. (optional).

database - Refers to the database to use in the OLAP engine (to be used in conjunction with table). Otherwise, will use the default database or schema if not specified (optional).

database_schema — Refers to the schema to use in the OLAP engine (to be used in conjunction with table). Otherwise, will use the default database or schema if not specified (optional).

watermark - A SQL expression that tells us the max timestamp that the metrics are considered valid for. Usually does not need to be overwritten, (optional).

timeseries — Refers to the timestamp column from your model that will underlie x-axis data in the line charts. If not specified, the line charts will not appear (optional).

connector — Refers to the OLAP engine, if you are not using DuckDB, IE: ClickHouse OLAP engine. (optional).

model — Refers to the model powering the dashboard with no path specified; should only be used for Rill models (either model or table is required).

table — Refers to the table powering the dashboard with no path specified; should be used instead of model for dashboards create from external OLAP tables (either table or model is required).

dimensions — Relates to exploring segments or dimensions of your data and filtering the dashboard (required).

  • column — a categorical column (required)
  • expression a non-aggregate expression such as string_split(domain, '.'). One of column and expression is required but cannot have both at the same time (required)
  • name — a stable identifier for the dimension (optional)
  • label — a label for your dimension (optional)
  • description — a freeform text description of the dimension (optional)
  • unnest - if true, allows multi-valued dimension to be unnested (such as lists) and filters will automatically switch to "contains" instead of exact match (optional)

measures — Used to define the numeric aggregates of columns from your data model (required).

  • expression — a combination of operators and functions for aggregations (required)
  • name — a stable identifier for the measure (required)
  • label — a label for your measure (optional)
  • description — a freeform text description of the dimension (optional)
  • valid_percent_of_total — a boolean indicating whether percent-of-total values should be rendered for this measure (optional)
  • format_d3 — controls the formatting of this measure using a d3-format string. If an invalid format string is supplied, measures will be formatted with format_preset: humanize (described below). Measures cannot have both format_preset and format_d3 entries. (optional; if neither format_preset nor format_d3 is supplied, measures will be formatted with the humanize preset)
    • Example: to show a measure using fixed point formatting with 2 digits after the decimal point, your measure specification would include: format_d3: ".2f".
    • Example: to show a measure using grouped thousands with two significant digits, your measure specification would include: format_d3: ",.2r".
  • format_preset — controls the formatting of this measure according to option specified below. Measures cannot have both format_preset and format_d3 entries. (optional; if neither format_preset nor format_d3 is supplied, measures will be formatted with the humanize preset)
    • humanize — round off numbers in an opinionated way to thousands (K), millions (M), billions (B), etc.
    • none — raw output
    • currency_usd — output rounded to 2 decimal points prepended with a dollar sign: $
    • currency_eur — output rounded to 2 decimal points prepended with a euro symbol: €
    • percentage — output transformed from a rate to a percentage appended with a percentage sign
    • interval_ms — time intervals given in milliseconds are transformed into human readable time units like hours (h), days (d), years (y), etc.

smallest_time_grain — Refers to the smallest time granularity the user is allowed to view. The valid values are: millisecond, second, minute, hour, day, week, month, quarter, year (optional).

first_day_of_week — Refers to the first day of the week for time grain aggregation (for example, Sunday instead of Monday). The valid values are 1 through 7 where Monday=1 and Sunday=7 (optional).

first_month_of_year — Refers to the first month of the year for time grain aggregation. The valid values are 1 through 12 where January=1 and December=12 (optional).

security - Defines a security policy for the dashboard (optional).

  • access - Expression indicating if the user should be granted access to the dashboard. If not defined, it will resolve to false and the dashboard won't be accessible to anyone. Needs to be a valid SQL expression that evaluates to a boolean (optional).
  • row_filter - SQL expression to filter the underlying model by. Can leverage templated user attributes to customize the filter for the requesting user. Needs to be a valid SQL expression that can be injected into a WHERE clause (optional).
  • exclude - List of dimension or measure names to exclude from the dashboard. If exclude is defined all other dimensions and measures are included (optional).
    • if - Expression to decide if the column should be excluded or not. It can leverage templated user attributes. Needs to be a valid SQL expression that evaluates to a boolean (required).
    • names - List of fields to exclude. Should match the name of one of the dashboard's dimensions or measures (required).
  • include - List of dimension or measure names to include in the dashboard. If include is defined all other dimensions and measures are excluded (optional).
    • if - Expression to decide if the column should be included or not. It can leverage templated user attributes. Needs to be a valid SQL expression that evaluates to a boolean (required).
    • names - List of fields to include. Should match the name of one of the dashboard's dimensions or measures (required).