SQL Analysis Services

Introduction to MDX

Multidimensional Expressions (MDX) is a query language for multidimensional databases, such as those found in SQL Server Analysis Services (SSAS). It's designed to retrieve data from cubes and present it in a flexible, multidimensional format. MDX allows you to perform complex analytical queries, including slicing, dicing, drill-down, and roll-up operations.

Compared to traditional SQL, MDX operates on a different paradigm, focusing on dimensions, hierarchies, members, and tuples rather than tables and rows. This guide will walk you through the fundamental concepts and common use cases of MDX.

Basic Syntax

An MDX query generally consists of a SELECT statement that defines the axes (rows and columns) of the data to be returned, and a FROM clause that specifies the cube.

SELECT
  {[Measures].[Internet Sales Amount]} ON COLUMNS,
  {[Date].[Calendar Year].Members} ON ROWS
FROM
  [Adventure Works DW]

In this example:

• [Measures].[Internet Sales Amount] is a measure.
• [Date].[Calendar Year].Members selects all members from the 'Calendar Year' level of the 'Date' dimension.
• ON COLUMNS and ON ROWS define the axes.
• [Adventure Works DW] is the cube name.

Writing MDX Queries

MDX queries are structured to define what data to retrieve and how to display it. The core components include:

• SELECT Statement: Specifies the data to be retrieved and how it's arranged on axes.
• FROM Clause: Identifies the cube or perspective from which to retrieve data.
• WHERE Clause (Slicer): Filters the data context for the entire query without placing it on an axis.

Key Functions

MDX provides a rich set of functions for data manipulation and analysis:

• Member Functions:Member(), Children(), Parent(), Ancestor()
• Set Functions:{} (Set Constructor), Crossjoin(), Union(), Filter()
• Numeric Functions:Sum(), Avg(), Count(), IIF()
• String Functions:Str(), Format()

Working with Sets

A set is an ordered collection of tuples. Tuples are like rows in SQL, but can contain members from multiple dimensions. Sets are fundamental to MDX querying.

Common ways to define sets:

• Set Constructor: {([Dim1].[Member1]), ([Dim2].[Member2])}
• Function-based Sets: [Dim].[Hierarchy].Members, [Dim].[Hierarchy].CurrentMember

Hierarchies and Levels

Dimensions in multidimensional models are typically organized into hierarchies, which represent structured relationships between data. Levels define the granularity within a hierarchy.

-- Selecting members from a specific level
SELECT
  {[Measures].[Reseller Sales Amount]} ON COLUMNS,
  {[Product].[Category].[Category].Members} ON ROWS
FROM
  [Adventure Works DW]

-- Navigating hierarchies
SELECT
  {[Measures].[Internet Sales Amount]} ON COLUMNS,
  {[Date].[Hierarchy].[Fiscal Year].Members * [Date].[Hierarchy].[Fiscal Quarter].Members} ON ROWS
FROM
  [Adventure Works DW]

Performance Tuning

Optimizing MDX queries is crucial for a responsive BI solution. Key strategies include:

• Minimize Cell Count: Return only necessary data.
• Utilize the Slicer: Use the WHERE clause to set context efficiently.
• Avoid Iterators on Large Sets: Prefer set-based operations when possible.
• Use Subcubes: Pre-aggregate data where feasible.
• Leverage Aggregations: Ensure aggregations are defined in your cube.

Practical Examples

SELECT
  {[Measures].[Internet Sales Amount]} ON COLUMNS
FROM
  [Adventure Works DW]
WHERE
  ([Date].[Calendar Year].&[2003])

SELECT
  {[Measures].[Internet Sales Amount]} ON COLUMNS,
  {[Product].[Category].[Category].Members * [Geography].[Country].[Country].Members} ON ROWS
FROM
  [Adventure Works DW]
WHERE
  ([Date].[Calendar Year].&[2003])

SELECT
  TOP 5
  {[Measures].[Internet Sales Amount]} ON COLUMNS,
  {[Customer].[Customer].[Customer].Members} ON ROWS
FROM
  [Adventure Works DW]
WHERE
  ([Date].[Calendar Year].&[2003])