You can use the group_aggregate function to aggregate measures at granularities that are different from the dimensions that you have in columns used in the search.

How aggregation formulas work

Typically, the groupings and filters used in a formula will be the same as those of the columns used in the search. The concept of a grouping equates to an attribute column.

For example, in the search “revenue ship mode”, revenue is the measure, and ship mode is the attribute or grouping. The result of this search would show total revenue for each ship mode, e.g., a dollars for air, r dollars for rail, t dollars for truck, s dollars for sea transport.

The aggregation formulas are described in Overview of aggregate formulas.

About flexible aggregation

Starting with version 5.0, ThoughtSpot provides for more flexible aggregation capability with a new function called group_aggregate. You can use this formula to pin columns in a query at a granularity different from the search bar query, using custom groupings and filters, rather than being bound to those of the search terms/columns.

The formula uses a sub-query to perform the custom aggregation. If the sub-query is at a courser grain, result column is simply added to the result of original query. Roll-up or reaggregation is used when the sub-query is at a finer grain than the original query

This is particularly useful for comparison analysis.

You can specify to use the groups and filters from the query with query_groups and query_filters, respectively, and for query_groups you can also add or exclude some groups or filters.

You can use roll-up or reaggregation to fill in a column.

Examples

For a search on revenue monthly ship mode, you can add a formula to calculate yearly revenue by ship mode:

group_aggregate(sum(revenue), {ship mode, year(commit date)}, {})

The same formula can also be written using query_groups() and query_filters() as following:

group_aggregate(sum(revenue), query_groups() - {commit date} + {year(commit date)}, {})

This is helpful to include the main query groups that are not known at formula creation time. You can use +/- to modify the set of groups included from the query.

With the flexibility of groupings for group formulas, the computed column created by a formula can be finer or courser grained than the search itself.

For example, you can have a search that shows total yearly sales and a formula that computes total sales for each month (a finer-grained calculation than the search).

In such cases, if an additional aggregation is specified by the formula, the results get reaggregated.

Reaggregation can be applied in either of these ways:

  • You can add an aggregation keyword just before a formula column in a search. For example, in this search we’ve added the keyword min just before our formula for monthly_sales:

    sum revenue yearly min monthly_sales

    where, the monthly_sales formula is written as:

       group_aggregate(sum(revenue), {start_of_month(date)}, {})

  • You can create a separate formula, such as in this search for:

    sum revenue yearly min_monthly_sales

    where, the min_monthly_sales formula is written as:

    min(monthly_sales)

Alternatively, if no aggregation is specified, then the search query also inherits the formula groupings, as in this search:

sum revenue yearly monthly_sales

where, the original query is computed at a monthly grain instead of yearly.

Reaggregation scenarios

Some scenarios require aggregation on an already aggregated result.

For example, computing minimum monthly sales per ship mode, requires two aggregations:

  • the first aggregation of sum to compute total monthly sales per ship mode.

  • the second aggregation of min to compute minimum sale that happened for any given month for that ship mode.

An example of this is this search:

ship mode min monthly_sales

where the formula monthly_sales is written as:

group_aggregate(sum(revenue), query_groups() + {start_of_month(date)}, {})

Groups and filters

Flexible group aggregate formulas allow for flexibility in both groupings and filters. The formulas give you the ability to specify only groupings or only filters.