a!measure(field, function, alias, label)
Determines the numerical values to display on a query or chart. The measure should incorporate a record field or a related record field, the appropriate calculation to run on the field, and an alias. If your record type has data sync enabled, you can also apply filters to determine which values are included in the calculation.
This configuration is used when a record type is defined as the data source for a chart or query. This function can be within the measure
parameter in a bar, column, line, or pie chart or a query with records.
See also:
Name | Keyword | Types | Description |
---|---|---|---|
Field |
|
Any Type |
The record field or related record field to use in this calculation, configured using the |
Function |
|
Text |
Function to use with calculations on the field provided. Accepts |
Alias |
|
Text |
The short name by which the result of the measure field can be referenced in other places in the chart configuration or |
Label |
|
Text |
Text to display in the legend or tooltip when using the measure in a chart. If no label is defined, the label displays with the function name and field name. The label only displays if a single grouping is used on a bar, column, or line chart. This parameter is ignored when used in |
Filter |
|
Any Type |
A single, logical expression or a list of query filters to filter the record set. Queries also apply the default filters defined on the referenced record type. This parameter is only available on record types that have sync enabled. |
SUM
, MIN
, MAX
, and AVG
can only be used with fields of type integer or decimal.DISTINCT_COUNT
is only supported with entity-backed or synced record types.The COUNT
function will count the total number of values in a record field, whereas the DISTINCT_COUNT
function will only count the unique values in a record field.
For example, say you want to count the number of customers who've placed an order. Since one customer can place many orders, the COUNT
function would count the same customer twice; however, the DISTINCT_COUNT
function will only count that customer once, even if they've placed multiple orders.
a!measure()
in a query, the alias is required.a!queryRecordType
.Count of id
.You can filter on a record field or a related record field, and the field reference must start from the aggregated record type.
For example, you have a Customer record type that has a one-to-many relationship with the Order record type. In a report, you want to calculate the number of orders for each customer that include the order item "Printer". Since you're aggregating on the Order record type, the field reference in the filter must start from recordType!Order
.
The a!measure
function would look something like this:
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a!measure(
function: "COUNT",
! field: recordType!Customer.relationships.orders.fields.id,
alias: "count_of_id",
/* Since the Order record type is the related record type used in the field parameter,
we'll use that record type reference in the filter.*/
filters: {
a!queryFilter(
! field: recordType!Order.relationships.orderItem.fields.itemName,
operator: "=",
value: "Printer"
)
}
)
When you filter on a field from a related record type in a one-to-many relationship (the "many" side of the relationship), the filter returns all records from the base record type (the "one" side of the relationship) that have at least one related record that meets the filter condition.
For example, an order can have many order items. So using the filter above, the aggregation will count all customer orders that have at least one order item called "Printer".
The following patterns include usage of the Measure Component.
Aggregate Data and Conditionally Display in a Chart or Grid (Reports, Charts, Query Data, Grids, Records): Aggregate data and conditionally display it in a pie chart or grid. In this pattern, we will calculate the total number of employees in each department and display it in a pie chart and a read-only grid. Then, we'll use a link field to conditionally display each component.
Aggregate Data and Display in a Chart (Reports, Charts, Query Data, Records): Aggregate data, specifically the total number of employees in a given department, to display in a pie chart.
Aggregate Data by Multiple Fields and Display in a Chart (Reports, Charts, Query Data, Records): Aggregate data by multiple fields and display it in a stacked column chart. In this pattern, we will calculate the total number of employees for each title in each department and display it in a stacked column chart.
Aggregate Data on a Date or Date and Time Field (Reports, Query Data, Grids, Records): Aggregate data, specifically the total number of employees by date.
Aggregate Data using a Filter and Display in a Chart (Reports, Charts, Query Data, Filtering, Records): Aggregate data, specifically the total number of employees for each title in the Engineering department, to display in a bar chart.
Configure a Chart Drilldown to a Grid (Charts, Grids, Query Data, Records): Displays a column chart with aggregate data from a record type and conditionally shows a grid with filtered records when a user selects a column on the chart.
Dynamically Show Sales by Product Category Compared to Total Sales (Records, Reports, Charts, Filtering): This pattern illustrates how to create a line chart that dynamically displays sales generated by product category compared to total sales over the last year.
Filter the Data in a Grid Using a Chart (Charts, Grids, Filtering, Records): Display an interactive pie chart with selectable sections so that a user may filter the results in a grid.
Percentage of Online Sales (Records, Reports, Formatting): This pattern illustrates how to calculate the percent of sales generated from online orders and display it in a gauge component.
Sales by Region (Records, Reports, Charts): This pattern illustrates how to create a bar chart that shows sales per U.S. sales region.
Total Orders Compared to Orders Purchased with Promo Codes (Records, Reports, Charts): This pattern illustrates how to create a column chart that compares the number of total orders and the number of orders that had at least one item purchased with a promo code.
Year-Over-Year Sales Growth (Records, Reports, Formatting): This pattern illustrates how to calculate year-over-year sales growth and display it in a KPI.