With the determined precision computes the quantile of a numeric data sequence.
The result is deterministic (it doesn’t depend on the query processing order). The function is optimized for working with sequences which describe distributions like loading web pages times or backend response times.
When using multiple
quantile* functions with different levels in a query, the internal states are not combined (that is, the query works less efficiently than it could). In this case, use the quantiles function.
level— Level of quantile. Optional parameter. Constant floating-point number from 0 to 1. We recommend using a
levelvalue in the range of
[0.01, 0.99]. Default value: 0.5. At
level=0.5the function calculates median.
- If negative values are passed to the function, the behavior is undefined.
- If the value is greater than 30,000 (a page loading time of more than 30 seconds), it is assumed to be 30,000.
The calculation is accurate if:
- Total number of values doesn’t exceed 5670.
- Total number of values exceeds 5670, but the page loading time is less than 1024ms.
Otherwise, the result of the calculation is rounded to the nearest multiple of 16 ms.
For calculating page loading time quantiles, this function is more effective and accurate than quantile.
- Quantile of the specified level.
If no values are passed to the function (when using
quantileTimingIf), NaN is returned. The purpose of this is to differentiate these cases from cases that result in zero. See ORDER BY clause for notes on sorting
┌─response_time─┐ │ 72 │ │ 112 │ │ 126 │ │ 145 │ │ 104 │ │ 242 │ │ 313 │ │ 168 │ │ 108 │ └───────────────┘
SELECT quantileTiming(response_time) FROM t
┌─quantileTiming(response_time)─┐ │ 126 │ └───────────────────────────────┘