Editare

MEDIAN (Transact-SQL)

Applies to: SQL analytics endpoint in Microsoft Fabric and Warehouse in Microsoft Fabric

The MEDIAN function returns the exact median, or 50th percentile, of non-NULL numeric values. You can use it as both an aggregate function and a window (analytic) function:

  • Aggregate usage: Returns the median for an entire group.
  • Window usage: Returns the median for each partition while preserving row-level output.

Transact-SQL syntax conventions

Syntax

Aggregation function syntax:

MEDIAN ( numeric_expression )

Analytic function syntax:

MEDIAN ( numeric_expression ) OVER ( [ <partition_by_clause> ] )

Arguments

numeric_expression

The numeric expression whose median is calculated. Supported exact numeric types are int, bigint, smallint, tinyint, numeric, decimal, bit, smallmoney, and money. Supported approximate numeric types are float and real.

OVER clause

The partition_by_clause divides the result set produced by the FROM clause into partitions, and the function is applied to each partition.

If you don't specify partition_by_clause, the function treats all rows of the query result set as a single partition.

The OVER clause doesn't support ORDER BY, ROWS, or RANGE for MEDIAN.

For more information, see SELECT - OVER clause (Transact-SQL).

Return types

Returns float(53).

Remarks

MEDIAN computes the continuous 50th percentile of the ordered non-NULL input values. For an even number of input values, the function interpolates between the two middle values. The result might not be a value that exists in the input rows.

MEDIAN is equivalent to PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY numeric_expression) for aggregate usage. The analytic form has equivalent percentile-continuous semantics within each partition.

NULL values are ignored. If all input values are NULL, or if no rows qualify, MEDIAN returns NULL. When ANSI_WARNINGS is ON, eliminating NULL values produces the standard aggregate warning.

MEDIAN is nondeterministic because floating-point calculations in parallel execution paths can produce slight variations. For more information, see Deterministic and nondeterministic functions.

DISTINCT isn't supported. Character, date, time, and datetime expressions aren't supported.

The MEDIAN function is available in Fabric Data Warehouse and the SQL analytics endpoint of Fabric items. The MEDIAN function isn't supported in SQL Server, Azure SQL Database, Azure SQL Managed Instance, or SQL database in Fabric.

Use case

Use MEDIAN when an average could be distorted by unusually high or low values. For example, median order value, response time, or claim amount often represents a typical observation more clearly than the arithmetic mean. The aggregate form summarizes groups, and the analytic form adds a partition benchmark to each detail row.

Examples

A. Calculate an aggregate median

This example returns the median of eight values. Because the input has an even number of rows, MEDIAN interpolates between 4 and 5.

SELECT MEDIAN(value) AS MedianValue
FROM (VALUES (1), (2), (3), (4), (5), (6), (7), (8)) AS t(value);

The result is 4.5.

B. Calculate a median for each group

This example calculates the median order amount for each sales region.

WITH SalesOrders AS (
    SELECT *
    FROM (VALUES
        ('North', 120.00),
        ('North', 220.00),
        ('North', 320.00),
        ('South', 150.00),
        ('South', 250.00),
        ('South', 450.00)
    ) AS v(region, order_amount)
)
SELECT
    region,
    MEDIAN(order_amount) AS MedianOrderAmount
FROM SalesOrders
GROUP BY region;

C. Ignore NULL values

This example ignores the NULL input and calculates the median from the remaining values.

SELECT MEDIAN(value) AS MedianValue
FROM (VALUES (1), (2), (NULL), (3), (4)) AS t(value);

If every input value is NULL, the function returns NULL.

D. Calculate a partitioned window median

This example adds the median latency for each service to every request row.

WITH ServiceLatency AS (
    SELECT *
    FROM (VALUES
        ('Checkout', 'req-001', 180),
        ('Checkout', 'req-002', 220),
        ('Checkout', 'req-003', 260),
        ('Search', 'req-010', 90),
        ('Search', 'req-011', 110),
        ('Search', 'req-012', 130)
    ) AS v(service, request_id, latency_ms)
)
SELECT
    service,
    request_id,
    latency_ms,
    MEDIAN(latency_ms) OVER (PARTITION BY service) AS ServiceMedianLatency
FROM ServiceLatency;

Related content

  • Last updated on