# quantileTDigestWeighted

Computes an approximate quantile of a numeric data sequence using the t-digest algorithm. The function takes into account the weight of each sequence member. The maximum error is 1%. Memory consumption is `log(n)`, where `n` is a number of values.

The performance of the function is lower than performance of quantile or quantileTiming. In terms of the ratio of State size to precision, this function is much better than `quantile`.

The result depends on the order of running the query, and is nondeterministic.

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.

##### note

Using `quantileTDigestWeighted` is not recommended for tiny data sets and can lead to significat error. In this case, consider possibility of using `quantileTDigest` instead.

Syntax

``quantileTDigestWeighted(level)(expr, weight)``

Alias: `medianTDigestWeighted`.

Arguments

• `level` — Level of quantile. Optional parameter. Constant floating-point number from 0 to 1. We recommend using a `level` value in the range of `[0.01, 0.99]`. Default value: 0.5. At `level=0.5` the function calculates median.
• `expr` — Expression over the column values resulting in numeric data types, Date or DateTime.
• `weight` — Column with weights of sequence elements. Weight is a number of value occurrences.

Returned value

• Approximate quantile of the specified level.

Type:

• Float64 for numeric data type input.
• Date if input values have the `Date` type.
• DateTime if input values have the `DateTime` type.

Example

Query:

``SELECT quantileTDigestWeighted(number, 1) FROM numbers(10)``

Result:

``┌─quantileTDigestWeighted(number, 1)─┐│                                4.5 │└────────────────────────────────────┘``