window_count

Knowledge Checkpoint

Readings that will help you understand this documentation better:

• Window Functions Overview

Definition

A window aggregation function that returns the count of rows in a range relative to the current row.

Syntax

window_count(agg_expr)
window_count(agg_expr, order: order_expr, ...)
window_count(agg_expr, range, order: order_expr, ...)
window_count(agg_expr, range, order: order_expr, ..., reset: partition_expr, ...)
window_count(agg_expr, range, order: order_expr, ..., partition: partition_expr, ...)

Examples

window_count(count(users.id))
window_count(count(users.id), order: count(users.id) | desc())
window_count(count(users.id), -2..2, order: users.created_at | month())
window_count(count(users.id), order: users.created_at | month(), reset: users.gender)

// Axis-aware examples
window_count(revenue, order: 'rows')                        // Running count across rows
window_count(revenue, order: 'columns', partition: 'rows')  // Running count within each row
window_count(revenue, order: 'x_axis' | desc())             // Running count in reverse row order
window_count(revenue, order: 'legend', partition: 'x_axis') // Running count within each column

Input

• agg_expr (required): An aggregation expression that we want to count.
• range (optional): A range of rows to include in the count. Negative values indicate rows before the current row, and positive values indicate rows after the current row, while 0 indicates the current row. If the beginning or end of the range is not specified, the range will include all rows from the beginning or end of the table. By default, if the range is not specified:
  • If order is specified, the range is ..0 (from the first row to the current row).
  • If order is not specified, the range is .. (from the first row to the last row).
• order (required, repeatable): A field that is used for ordering. The order defaults to ascending. The order can be set explicitly with asc() or desc(). You can also use axis references:
  • 'rows' or 'x_axis': Order by dimensions mapped to rows/x-axis
  • 'columns' or 'legend': Order by dimensions mapped to columns/legend
  • Axis references can be modified with asc() or desc(): order: 'rows' | desc()
  warning

  If the specified order does not uniquely identify rows, the result of the function can be non-deterministic. For example, if you use order: users.age, and there are multiple users with the same age in the same partition, the result can be unexpected.

• partition or reset (repeatable, optional): A field that is used for partitioning the table. You can also use axis references like 'rows', 'columns', 'x_axis', or 'legend'. If partitions are not specified:
  • If order is specified, the table will be partitioned by all other grouping columns.
  • If order is not specified, the table will be considered as a single partition.

Output

The count of the current row and the rows within the specified range.

Sample Usages

Refer to the sample usages in window_sum.

Axis-Aware Usage

You can use axis references to create running counts that adapt to your visualization structure:

explore {
  dimensions {
    rows {
      _quarter: orders.created_at | quarter()
    }
    columns {
      _status: orders.status
    }
  }

  measures {
    order_count: count(orders.id),

    // Running count across quarters for each status
    running_by_quarter: window_count(order_count, order: 'rows'),

    // Running count across statuses for each quarter
    running_by_status: window_count(order_count, order: 'columns'),

    // Override visualization sort order
    running_reverse: window_count(order_count, order: 'x_axis' | desc())
  }
}

This approach is particularly useful when:

• Your visualization structure might change dynamically
• You want calculations to automatically adapt to different groupings
• You need to respect the visualization's sort order