QUANTILE_TDIGEST_WEIGHTED (Lakehouse v1)

Computes an approximate quantile of a numeric data sequence using the t-digest algorithm. This function takes into account the weight of each sequence member. Memory consumption is log(n), where n is a number of values.

Caution

NULL values are not included in the calculation.

Analyze Syntax

func.quantile_tdigest_weighted(<levels>, <expr>, <weight_expr>)

Analyze Examples

func.quantile_tdigest_weighted([0.5, 0.8], table.sales_amount, 1).alias('sales_amounts')

| sales_amounts         |
|-----------------------+
| [6000.0,7000.0]       |

SQL Syntax

QUANTILE_TDIGEST_WEIGHTED(<level1>[, <level2>, ...])(<expr>, <weight_expr>)

Arguments

Arguments	Description
<level n>	A level of quantile represents a constant floating-point number ranging from 0 to 1. It is recommended to use a level value in the range of [0.01, 0.99].
<expr>	Any numerical expression
<weight_expr>	Any unsigned integer expression. Weight is a number of value occurrences.

Return Type

Returns either a Float64 value or an array of Float64 values, depending on the number of quantile levels specified.

SQL Examples

-- Create a table and insert sample data
CREATE TABLE sales_data (
  id INT,
  sales_person_id INT,
  sales_amount FLOAT
);

INSERT INTO sales_data (id, sales_person_id, sales_amount)
VALUES (1, 1, 5000),
       (2, 2, 5500),
       (3, 3, 6000),
       (4, 4, 6500),
       (5, 5, 7000);

SELECT QUANTILE_TDIGEST_WEIGHTED(0.5)(sales_amount, 1) AS median_sales_amount
FROM sales_data;

median_sales_amount|
-------------------+
             6000.0|

SELECT QUANTILE_TDIGEST_WEIGHTED(0.5, 0.8)(sales_amount, 1)
FROM sales_data;

quantile_tdigest_weighted(0.5, 0.8)(sales_amount)|
-------------------------------------------------+
[6000.0,7000.0]                                  |