MDX (Multi Dimensional Expressions) Introduction


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MDX (Multi Dimensional Expressions) Introduction

  1. 1. Digvendra Singh
  2. 2.  Introduction ◦ What is MDX ◦ Where MDX is required Syntax and examples on MDX Basics of MDX  Axis  Member Reference  Tuple  Partial Tuple  Sets  Calculated Members  Calculated Sets Functions Different reporting scenarios
  3. 3.  MDX is a language used for querying and manipulating data stored in OLAP Cubes (or say multi-dimensional databases) Concept is same as “SQL is a querying language”. ◦ SQL  Relational Database ◦ MDX  Multidimensional Database MDX return multidimensional cell-sets that contain the cubes data
  4. 4. OLAP Cube Result (multidimensional Cube-Sets) MDX Reporting Services (SSRS, SAP TM1, Oracle Essbase, Microstrategy, Tableau, Cognos etc.)
  5. 5. Syntax: [ WITH <SELECT WITH clause> [ , <SELECT WITH clause> ... ] ] SELECT [ * | ( <SELECT query axis clause> [ , <SELECT query axis clause> ... ] ) ] FROM <SELECT subcube clause> [ <SELECT slicer axis clause> ] [ <SELECT cell property list clause> ]Simplest Syntax: SELECT {set} ON AXIS(0) , {set} ON AXIS(1) FROM [Cube] WHERE <<data is sliced by some coordinates>>
  6. 6. Before getting into details, you should be familiar with basics of Cubeterminology. This include Cube, Measures, Attribute Hierarchy,Members, Level etc.For revision please refer the link below:
  7. 7. a. Axisb. Member Referencec. Tupled. Partial Tuplee. Setsf. Calculated Membersg. Calculated Sets
  8. 8.  Axes in MDX defines representation plane for data of result set. Sometimes we put one dimension representing one axis. For e.g. in 3-D space x,y,z are three axes (figure below) In SELECT statement we specify what data on which axes of result-set, is required SELECT statement support 128 axes (i.e. 0 to 127) Important axes in MDX are listed below (most used are 0 and 1): Formal Name Short Name Alias Axis(0) 0 COLUMNS Axis(1) 1 ROWS Axis(2) 2 PAGES Axis(3) 3 SECTIONS Axis(4) 4 CHAPTERS
  9. 9.  Fully qualified name for each member in Cube Multiple ways to give member reference: [Dimension].[Attribute Hierarchy].[Attribute].[Member] Without user hierarchy (Attribute Hierarchy is Attribute itself) E.g. ◦ [Time].[Year].[Year].[2001] ◦ [Time].[Year].[Year].&[2001] ◦ [Time].[Year].[Year].&[1] With user hierarchy E.g. ◦ [Time].[Fiscal].[Year].[2001] ◦ [Time].[Calendar].[Year].&[2001] ◦ [Time].[Fiscal].[Year].&[1] We need not Attribute name sometimes E.g. ◦ [Time].[Year].[2001] ◦ [Time].[Calendar].[Year].[2001]
  10. 10.  Ordered list of members from each dimensions of cube  Represent a point in the Cube space  A cell can be representation of a tuple  For e.g. ◦ In 3-D space (x1, y1, z1) is a tuple ◦ In a cube with 3 dimensions (2 dimensions and 1 for measures) ([Time].[Year].[Year].[2001], [Product].[Category].[Category].[Bikes], [Measures].[Sales Amount]) is a tuple• In 3-D space, a tuple represent list of one member from each axis. So an ordered members list says (x1, y1, z1) . <In Red>• In Cube a tuple is ordered list of member from each dimension (more specifically each attribute of cube). In this example we believe there are 2 Dimension only and 1 member from Measures Dimension is necessary. <In Blue>
  11. 11.  Part of the tuple with less member reference, where rest of the member reference are taken care with Analysis Services to understand That is, no need to list for all the members from each dimension Default member from dimension is used in place of Omitted members For e.g. ◦ In 3-D space, if we want to omit an axis tuple will be (0, y1, z1) i.e. with zero ◦ In Cube space, if we omit Time dimension tuple will be ([Product].[Category].[Category].[Bikes], [Measures].[Sales Amount])
  12. 12.  Ordered collection of tuples with the same dimensionality, or hierarchality E.g. Sets with tuple having single member: {[Time].[Year].[2001], [Time].[Year].[2007], [Time].[Year].[2009]} Sets with tuple having multiple members: { (Time.[Year].[Year].[2001], [Product].[Category].[Category].[Bikes]), (Time.[Year].[Year].[2002], [Product].[Category].[Category].[Clothing]) } Sets with hierarchy involved: { (Time.[Fiscal].[Year].[2001], [Product].[Category].[Category].[Bikes]), (Time.[Fiscal].[Year].[2002], [Product].[Category].[Category].[Clothing]) }
  13. 13.  MDX provide way to create and query calculated members in result set Use WITH MEMBER clause before SELECT statement Create a member in any dimensional attribute and Measures dimension as well. E.g. Dimensional Member: WITH MEMBER [Product].[Category].[Popular] AS [Product].[Category].[Category].[Bikes]+[Product].[Category].[Category].[Clothing ] E.g. Measures member (new calculated measure): WITH MEMBER [Total Sales] AS ([Measures].[Reseller Sales Amount]+ [Measures].[Internet Sales Amount])
  14. 14.  Same as Named Sets in Cube, we can create Calculated Sets in MDX while querying Sets are always collection of Tuples, so is a calculated set Use WITH SET clause before SELECT statement E.g. Calculated set for two members of Product Category: WITH SET [Best Products] AS {[Product].[Category].[Category].[Bikes],[Product].[Category].[Cat egory].[Clothing]}
  15. 15.  About 12-13 categories and more than 50 Functions Functions eases the calculations and provide desired results Need to understand function with examples and their uses Broad categories are : ◦ Set Functions ◦ Navigation Functions ◦ Metadata Functions ◦ Time Functions ◦ String Functions ◦ UI Functions
  16. 16.  Different reporting requirements needs different MDX query manipulation For example: ◦ We list all or selected members of one attribute to fill filter values of report ◦ We CROSSJOIN different attributes to get multiple columns or fields required in report ◦ We use NON EMPTY to filter unnecessary rows from results ◦ We use STRTOSET, STRTOMEMBER to manipulate string as cube members ◦ We create calculated members and sets when desired fields are not available in cube ◦ We use SUBCUBE functions and queries in MDX to avoid unwanted totalsThere are many different scenarios coming across reporting needs.But I am sure little hands on experience with MDX, can help youfind solution for all. That’s the beauty of MDX, its flexible and vast.
  17. 17.  Please add all your queries and doubt here or my blog: For further details on functions and MDX please comment on the blog posts.