Daily DAX : Day 196 INFO.SEGMENTMAPSTORAGES

 The INFO.SEGMENTMAPSTORAGES DAX function in Power BI is part of the INFO family of functions, which provide metadata about the semantic model. Specifically, INFO.SEGMENTMAPSTORAGES returns a table containing detailed information about the segment map storages in the current Power BI model. It corresponds to the TMSCHEMA_SEGMENT_MAP_STORAGES Dynamic Management View (DMV) in Analysis Services, adapted as a DAX function for use in Power BI. This function is primarily used for advanced model introspection and optimization, requiring semantic model admin permissions to execute.

Syntax

DAX

INFO.SEGMENTMAPSTORAGES ( [<RestrictionName> [, [<RestrictionValue>] [, <RestrictionName> [, [<RestrictionValue>] [, … ] ] ] ] )

    RestrictionName: (Optional) The name of a column in the segment map storages schema to filter the results.

    RestrictionValue: (Optional) The value to filter the specified column.

    Multiple restriction pairs can be provided to refine the output.

Return Value

The function returns a table with columns that match the schema of segment map storages, providing metadata about how data segments are stored in the model. The exact columns are not fully detailed in public documentation, as the function is considered undocumented or unsupported by Microsoft, but they typically include attributes like segment IDs, storage details, and related metadata.

Key Characteristics

    Output: A table containing segment map storage details.

    Context: Cannot be used in calculated columns or calculated tables due to its metadata-focused nature.

    Compatibility: Compatible with DirectQuery mode, but limitations may apply based on the data source.

    Permissions: Requires semantic model admin permissions, and some scenarios may need workspace admin permissions.

    Context Transition: Performs a context transition if called in a row context.

Use Case

The INFO.SEGMENTMAPSTORAGES function is primarily used by advanced Power BI developers or administrators for model optimization and debugging. Here are specific use cases:

    Model Performance Analysis:

        Segment map storages relate to how data is partitioned and stored in the Tabular engine (VertiPaq). By analyzing the output of INFO.SEGMENTMAPSTORAGES, developers can gain insights into the storage structure, such as how data segments are organized.

        This can help identify inefficiencies, such as excessive segmentation or suboptimal compression, which may impact query performance.

    Memory Usage Optimization:

        The function provides metadata that can be used to assess memory consumption at the segment level. For large models, understanding segment storage can guide decisions on data partitioning, column cardinality reduction, or adjusting refresh strategies to optimize memory usage.

    Troubleshooting Data Refresh Issues:

        During data refreshes, issues like memory bottlenecks or refresh failures may occur. By examining segment map storages, administrators can diagnose whether the storage structure is contributing to these issues, such as excessive fragmentation or storage overhead.

    Model Documentation:

        The function can be used to extract metadata for documentation purposes, helping teams understand the internal structure of the model. For example, combining INFO.SEGMENTMAPSTORAGES with other DAX functions like SELECTCOLUMNS or ADDCOLUMNS can create a report on storage characteristics.

    Advanced Development and Research:

        For developers working on custom tools or extensions for Power BI, this function provides low-level access to model internals, enabling the creation of diagnostic tools or performance dashboards.

Example

Below is a sample DAX query to retrieve segment map storage details:

DAX

EVALUATE

INFO.SEGMENTMAPSTORAGES()

This query returns a table listing all segment map storages in the model. To filter results, you could add restrictions, though specific column names for restrictions are not well-documented and may require experimentation or access to internal model metadata.

To make the output more usable, you can combine it with other DAX functions:

DAX

EVALUATE

SELECTCOLUMNS(

    INFO.SEGMENTMAPSTORAGES(),

    "SegmentID", [SegmentID],  // Hypothetical column name

    "StorageSize", [StorageSize]  // Hypothetical column name

)

This query selects specific columns (e.g., SegmentID and StorageSize) for analysis, assuming those columns exist in the output schema.

Practical Considerations

    Undocumented Nature: Since Microsoft does not provide official documentation for INFO.SEGMENTMAPSTORAGES, its use requires caution. The schema or behavior may change in future Power BI updates, potentially breaking queries.

    Advanced Tooling: Tools like DAX Studio or VertiPaq Analyzer are often used alongside this function to interpret the output, as they provide additional context about the model's storage engine.

    Performance Impact: Running metadata queries like this on large models may consume resources, so use them judiciously in production environments.

    Permissions: Ensure you have the necessary admin permissions, as unauthorized access will result in errors.

Alternative Approaches

If INFO.SEGMENTMAPSTORAGES is too low-level or inaccessible, consider these alternatives:

    Use VertiPaq Analyzer in DAX Studio to analyze model storage and memory usage without directly querying segment map storages.

    Leverage other INFO functions, such as INFO.TABLES or INFO.MEASURES, for higher-level metadata.

    Use Power BI's Performance Analyzer to identify query bottlenecks without diving into storage details.

Conclusion

The INFO.SEGMENTMAPSTORAGES DAX function is a niche, advanced tool for inspecting the storage structure of a Power BI semantic model. Its primary use cases revolve around performance optimization, memory analysis, and troubleshooting, making it valuable for experienced developers and administrators. However, due to its undocumented status and the1540 requirement for admin permissions, users should approach it with caution and consider supplementary tools like DAX Studio for comprehensive model analysis.