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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.
All functions support
For the full syntax and additional examples, refer to the SQL reference.
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New functions
https://developers.cloudflare.com/changelog/rss/#new-functionsAPPROX_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 toAPPROX_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 thekmost frequent values with their counts as a JSON array.
All functions support
WHERE filters. All except APPROX_TOP_K support GROUP BY.Examples
https://developers.cloudflare.com/changelog/rss/#examples
Code:
-- 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
Code:
-- Median per department
SELECT department, approx_median(total_amount)
FROM my_namespace.sales_data
GROUP BY department
Code:
-- Approximate distinct customers by region
SELECT region, approx_distinct(customer_id)
FROM my_namespace.sales_data
GROUP BY region
Code:
-- Top 5 most frequent departments
SELECT approx_top_k(department, 5)
FROM my_namespace.sales_data
Code:
-- 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.
Continue reading...