MSDN Community Articles

Introduction to MDX Functions

Multidimensional Expressions (MDX) is a query language used with Microsoft SQL Server Analysis Services. It allows you to retrieve data from cubes, perform complex calculations, and analyze multidimensional data. A key component of MDX is its extensive set of functions, which enable sophisticated data manipulation and analysis. This article provides an overview of MDX functions, their categories, and common examples.

Categories of MDX Functions

MDX functions can be broadly categorized to better understand their purpose and application:

• Numeric Functions: Perform mathematical and statistical operations on numeric values.
• String Functions: Manipulate and process text data.
• Date and Time Functions: Work with dates and times, enabling temporal analysis.
• Set Functions: Manipulate sets of members or tuples, crucial for navigation and aggregation.
• Hierarchical Functions: Navigate and extract information from dimension hierarchies.
• Aggregate Functions: Compute aggregate values over specified sets.
• Property Functions: Retrieve specific properties of members, levels, or dimensions.
• Control Flow Functions: Implement conditional logic within MDX queries.
• Tuple and Cell Functions: Work with tuples and retrieve cell values.

Commonly Used MDX Functions

Here are some of the most frequently used MDX functions that are essential for any Analysis Services developer:

• SUM(): Calculates the sum of an expression over a set.
• COUNT(): Returns the number of elements in a set.
• AVG(): Computes the average of an expression over a set.
• MAX(): Returns the maximum value in a set.
• MIN(): Returns the minimum value in a set.
• HEAD(): Returns the first n elements of a set.
• TAIL(): Returns the last n elements of a set.
• MEMBER(): Returns a member given its fully qualified name or a string.
• IIF(): Evaluates a condition and returns one value if true, another if false.
• NONEMPTY(): Returns a set of non-empty tuples.

Mathematical and String Functions Example

Mathematical functions are vital for performing calculations on your data. For instance, you might want to calculate a moving average or a year-over-year growth rate. String functions, while less common for core OLAP analysis, can be useful for formatting or manipulating dimension member names.

Mathematical Functions:

The AVG() function is often used:

SELECT
    { [Measures].[Internet Sales Amount] } ON COLUMNS,
    [Date].[Calendar Year].MEMBERS ON ROWS
FROM [Adventure Works]
WHERE
    (
        [Measures].[Internet Sales Amount] /
        IIF(
            [Measures].[Internet Order Quantity] = 0,
            NULL,
            [Measures].[Internet Order Quantity]
        )
    )

String Functions:

The SUBSTRING() function can extract parts of a string:

SELECT
    SUBSTRING([Product].[Product Name].CURRENTMEMBER.NAME, 1, 10)
FROM [Adventure Works]
WHERE [Product].[Category].&[1]

Time Intelligence Functions

Time intelligence functions are a specialized and powerful set of functions designed for analyzing data over time. They simplify common business calculations such as year-to-date, period-to-date, and prior-period comparisons.

• YTD(): Calculates the year-to-date aggregate.
• CUMULATIVE(): Calculates a cumulative sum over time.
• PARALLELPERIOD(): Returns a set of members from the same level as the given set, but in a previous period.
• SAMEPERIODLASTYEAR(): Returns a set of dates from the previous year corresponding to the dates in the input set.

Example of using YTD():

SELECT
    { [Measures].[Sales Amount].YTD } ON COLUMNS
FROM [Adventure Works]
WHERE [Date].[Calendar Year].&[2023]

Conclusion

Mastering MDX functions is crucial for unlocking the full potential of your Analysis Services cubes. By understanding the various categories and common functions, you can build powerful reports, perform detailed analysis, and gain deeper insights into your business data. Experiment with these functions in your own MDX queries to see their impact.