Lag

The lag function calculates the lag (previous) value for a measure based on specified partitions and sorts.

lag is supported for use with analyses based on SPICE and direct query data sets.

Syntax

The brackets are required. To see which arguments are optional, see the following descriptions.

lag
(
     measure> 
     ,[ sortorder_field ASC_or_DESC, ... ]  
     ,lookup_index,
     ,[ partition_field, ... ] 
)

Arguments

measure

The measure that you want to get the lag for. This can include an aggregate, for example sum({Sales Amt}).

sort order field

One or more measures and dimensions that you want to sort the data by, separated by commas. You can specify either ascending (ASC) or descending (DESC) sort order.

Each field in the list is enclosed in {} (curly braces), if it is more than one word. The entire list is enclosed in [ ] (square brackets).

lookup index

The lookup index can be positive or negative, indicating a following row in the sort (positive) or a previous row in the sort (negative). The lookup index can be 1–2,147,483,647. For the engines MySQL, MariaDB, and Amazon Aurora MySQL-Compatible Edition, the lookup index is limited to just 1.

partition field

(Optional) One or more dimensions that you want to partition by, separated by commas.

Each field in the list is enclosed in {} (curly braces), if it is more than one word. The entire list is enclosed in [ ] (square brackets).

Example

The following example calculates the previous sum(sales), partitioned by the state of origin, in the ascending sort order on cancellation_code.

lag
(
     sum(Sales), 
     [cancellation_code ASC], 
     1, 
     [origin_state_nm]
)

The following example uses a calculated field with lag to display sales amount for the previous row next to the amount for the current row, sorted by Order Date. The fields in the table calculation are in the field wells of the visual.

lag(
     sum({Sales}),
     [{Order Date} ASC],
     1
)

The following screenshot shows the results of the example.

The following example uses a calculated field with lag to display the sales amount for the previous row next to the amount for the current row, sorted by Order Date partitioned by Segment.

lag
    (
        sum(Sales),
        [Order Date ASC],
        1, [Segment]
    )

The following screenshot shows the results of the example.