Power Pivot Principles: The A to Z of DAX Functions – INFO.DETAILROWSDEFINITION

In our long-established Power Pivot Principles articles, we continue our series on the A to Z of Data Analysis eXpression (DAX) functions.  This week, we look at INFO.DETAILROWSDEFINITION.

The INFO.DETAILROWSDEFINITION function

Dynamic Management Views (DMVs) are specialised queries provided by SQL Server Analysis Services (SSAS), Azure Analysis Services (AAS), and Power BI that offer an administrative view into the internal state of these systems.  DMVs are used to retrieve metadata, monitor health and performance, and diagnose problems within the database or data model.  They serve as a powerful tool for administrators and developers to gain insights into the workings of the database engine and the tabular data model, covering aspects like performance metrics, configuration settings and the structure of database objects.

The $System schema DMVs in SQL Server Analysis Services (SSAS), Azure Analysis Services (AAS), and Power BI are categorised into four [4] types, each serving specific purposes:

• DISCOVER: requires admin privileges and provides information about the model, including details on connected sessions and environment configuration
• DMSCHEMA: focused on data mining, offering insights for predictive analytics and pattern recognition, mainly used in SSAS/AAS
• MDSCHEMA: targets multidimensional models, delivering metadata and structure from an MDX perspective, relevant for OLAP cubes and dimensions
• TMSCHEMA: designed for tabular models, it provides detailed metadata about tables, columns, measures, etc., using Tabular Model Scripting Language (TMSL) information, crucial for Power BI and tabular SSAS/AAS models.

In the past, if we wanted to query those $System schema DMVs we used external tools like Tabular Editors or DAX Studio to query them:

The INFO.DETAILROWSDEFINITION function is one of the system functions.  It employs the following syntax:

This function has no parameters.

Based upon the ‘[MS-SSAS-T]: SQL Server Analysis Services Tabular Protocol’ from Microsoft (which you may access here), the DetailRowsDefinition object represents an unnamed table expression in DAX.  It is a child of a Measure or a Table object and requires compatibility level 1400 or higher.

We can write this INFO.DETAILROWSDEFINITION function in DAX query view to get the same information on the TMSCHEMA_DETAIL_ROWS_DEFINITIONS:

It will query the $SYSTEM.TMSCHEMA_DETAIL_ROWS_DEFINITIONS and return an entire table with seven [7] columns:

• ID: this represents a reference to the object
• ObjectID: this is an ID-based reference to a Measure or Table object
• ObjetcType: this is the data type of the object specified by ObjectID.  The possible values are as follows:
• TM_TYPEID_Table (3)
• TM_TYPEID_Measure (8)
• Expression: this represents the DAX detail rows expression for a table type
• ModifiedTime: this is the time that the object was last modified
• State: this is a value that provides information about the state of the parent object or the container object.  The possible values are as follows:
• Ready (1) – the object expression is queryable and the data is in an up-to-date state
• NoData (3) – not applicable
• CalculationNeeded (4) – not applicable
• SemanticError (5) – the object expression has a semantic error
• EvaluationError (6) - not applicable
• DependencyError (7) – a dependency associated with the DetailRowsDefinition object is in an error state (SemanticError, EvaluationError, or DependencyError)
• Incomplete (8) - not applicable
• SyntaxError (9) – the object has a syntax error in its expression.
• ErrorMessage: this is a string that explains the error state that is associated with the DetailRowsDefinition object.  It is set by the engine only when the state of the object is one of these three values:
• SemanticError
• DependencyError
• SyntaxError.

It should be noted that:

• it is used for querying the DMV (Dynamic Management Views) from the $System schema called TMSCHEMA where TM stands for ‘Tabular model’ and TMSCHEMA provides information from the tabular model
• sometimes querying DMVs may fail if we do not have the appropriate permission.

Come back next week for our next post on Power Pivot in the Blog section.  In the meantime, please remember we have training in Power Pivot which you can find out more about here.  If you wish to catch up on past articles in the meantime, you can find all of our Past Power Pivot blogs here.