Estimating Percentile Values¶

Overview¶

Snowflake provides an improved version of an implementation of the t-Digest algorithm papers by Dunning and Ertl. It has been implemented through the APPROX_PERCENTILE family of functions.

As documented, the algorithm has a constant relative error. Note that the algorithm has substantial empirical support, but no rigorous proof of any accuracy guarantees.

SQL Functions¶

The following Aggregate functions are provided for using t-Digest to approximate percentile values:

• APPROX_PERCENTILE: Returns an approximation of the desired percentile value.

• APPROX_PERCENTILE_ACCUMULATE: Skips the final estimation step and, instead, returns the intermediate t-Digest state at the end of an aggregation.

• APPROX_PERCENTILE_COMBINE: Combines (i.e. merges) multiple input states into a single output state.

• APPROX_PERCENTILE_ESTIMATE: Computes a percentile estimate of a t-Digest state produced by APPROX_PERCENTILE_ACCUMULATE or APPROX_PERCENTILE_COMBINE.

Implementation Details¶

• The estimation uses a constant amount of space regardless of the size of the input.

• The t-Digest state is independent from the percentile value. This enables calculating the t-Digest state once, and then querying the state for multiple percentile values.