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R2 SQL now supports approximate aggregation functions

Feb 09, 2026

R2 SQL now supports five approximate aggregation functions for fast analysis of large datasets. These functions trade minor precision for improved performance on high-cardinality data.

New functions

APPROX_PERCENTILE_CONT(column, percentile) — Returns the approximate value at a given percentile (0.0 to 1.0). Works on integer and decimal columns.
APPROX_PERCENTILE_CONT_WITH_WEIGHT(column, weight, percentile) — Weighted percentile calculation where each row contributes proportionally to its weight column value.
APPROX_MEDIAN(column) — Returns the approximate median. Equivalent to APPROX_PERCENTILE_CONT(column, 0.5).
APPROX_DISTINCT(column) — Returns the approximate number of distinct values. Works on any column type.
APPROX_TOP_K(column, k) — Returns the k most frequent values with their counts as a JSON array.

All functions support WHERE filters. All except APPROX_TOP_K support GROUP BY.

Examples

-- Percentile analysis on revenue data
SELECT approx_percentile_cont(total_amount, 0.25),
       approx_percentile_cont(total_amount, 0.5),
       approx_percentile_cont(total_amount, 0.75)
FROM my_namespace.sales_data

-- Median per department
SELECT department, approx_median(total_amount)
FROM my_namespace.sales_data
GROUP BY department

-- Approximate distinct customers by region
SELECT region, approx_distinct(customer_id)
FROM my_namespace.sales_data
GROUP BY region

-- Top 5 most frequent departments
SELECT approx_top_k(department, 5)
FROM my_namespace.sales_data

-- Combine approximate and standard aggregations
SELECT COUNT(*),
       AVG(total_amount),
       approx_percentile_cont(total_amount, 0.5),
       approx_distinct(customer_id)
FROM my_namespace.sales_data
WHERE region = 'North'

For the full syntax and additional examples, refer to the SQL reference.