Daily DAX : Day 182 EVALUATEANDLOG
The EVALUATEANDLOG function in Power BI's Data Analysis Expressions (DAX) is a specialized debugging tool designed to help developers understand and trace the intermediate results of DAX expressions during query evaluation. It returns the value of its input expression (scalar or table) while logging detailed information about the evaluation process in a DAX Evaluation Log profiler event, which can be captured and analyzed using external tools. This function is particularly useful for diagnosing performance issues, understanding complex calculations, and verifying the behavior of DAX expressions.
Syntax
DAX
EVALUATEANDLOG(
Expression,
[Label],
[MaxRows]
)
Expression: The DAX expression to evaluate, which can return either a scalar value or a table.
Label (optional): A string to identify the log entry, making it easier to locate specific logs when debugging.
MaxRows (optional): The maximum number of rows to log for table expressions (default is 10). This limits the output size to avoid performance issues.
Key Characteristics
Primary Purpose: Debugging and performance analysis by logging intermediate results and their evaluation context.
Environment Limitation: Fully functional only in Power BI Desktop. In other environments (e.g., Power BI Service), it acts as a passthrough, returning the expression’s result without logging.
Output: Returns the result of the input expression unchanged while generating a JSON-structured log in a DAX Evaluation Log event, capturing:
Expression: The text of the evaluated expression.
Label: The provided label (if specified).
Inputs: Columns in the evaluation context that influence the result.
Outputs: For scalar expressions, a single [Value] column; for table expressions, the output columns.
Data: Input-output mappings (scalar values or table rows).
RowCount: For table expressions, the total number of rows (even if truncated by MaxRows).
Performance Consideration: Since it may disable certain DAX engine optimizations, Microsoft recommends removing EVALUATEANDLOG from production code to avoid performance impacts.
Use Cases
EVALUATEANDLOG is primarily a diagnostic tool, and its use cases revolve around debugging and optimizing DAX calculations. Below are detailed scenarios where it shines:
Debugging Complex DAX Expressions
Scenario: You’re working on a measure or calculated column that produces unexpected results, and you suspect an issue in how intermediate calculations are evaluated.
Use Case: Wrap EVALUATEANDLOG around parts of the expression to log intermediate results. For example, in a measure calculating sales growth, you can log the numerator and denominator separately to verify their values across different filter contexts.
Example:
DAX
DeltaSales =
DIVIDE(
EVALUATEANDLOG([TotalSales], "CurrentSales"),
EVALUATEANDLOG([PreviousYearSales], "PreviousSales")
)
Outcome: The log shows the values of [TotalSales] and [PreviousYearSales] for each evaluation context, helping you pinpoint where calculations deviate.
Understanding Filter Context and Row Context
Scenario: You’re unsure how a DAX expression behaves under different filter contexts (e.g., slicers, row-level calculations) or row contexts (e.g., iterator functions like SUMX).
Use Case: Use EVALUATEANDLOG to log the inputs (columns in the filter context) and outputs, revealing how context affects results.
Example:
DAX
EVALUATE
SUMMARIZECOLUMNS(
'Product'[Color],
"Count", EVALUATEANDLOG(COUNT('Product'[ProductKey]), "ProductCount")
)
Outcome: The log shows the count of products per color and the filter context (e.g., 'Product'[Color] values), clarifying how grouping impacts the calculation.
Diagnosing Performance Issues
Scenario: A report is slow, and you suspect a specific measure or calculation group is causing unnecessary evaluations (e.g., unused branches in a SWITCH statement or calculation group).
Use Case: Insert EVALUATEANDLOG to identify whether the DAX engine evaluates unused logic, which can degrade performance.
Example:
DAX
DynamicMeasure =
SWITCH(
SELECTEDVALUE('MeasureSelector'[Measure]),
"Sales", EVALUATEANDLOG([TotalSales], "SalesLog"),
"Profit", EVALUATEANDLOG([TotalProfit], "ProfitLog"),
BLANK()
)
Outcome: If the log shows events for both “SalesLog” and “ProfitLog” when only “Sales” is selected, it indicates the engine is evaluating unused branches, suggesting a need for optimization (e.g., using calculation groups or restructuring the logic).
Visualizing Table Expressions
Scenario: You’re using table functions like FILTER, SUMMARIZE, or ADDCOLUMNS, and you want to inspect the intermediate tables generated during evaluation.
Use Case: Wrap EVALUATEANDLOG around table expressions to log their structure and data, which is otherwise hard to visualize.
Example:
DAX
EVALUATE
EVALUATEANDLOG(
FILTER('Sales', 'Sales'[Quantity] > 100),
"HighQuantitySales",
20
)
Outcome: The log displays up to 20 rows of the filtered table, showing columns like 'Sales'[Quantity], 'Sales'[ProductKey], etc., helping you verify the filter logic.
Learning and Teaching DAX
Scenario: You’re learning DAX or teaching others and want to demonstrate how expressions evaluate step-by-step.
Use Case: Use EVALUATEANDLOG to provide a transparent view of DAX’s inner workings, such as how aggregations or iterators process data.
Example:
DAX
TotalCost =
SUMX(
'Sales',
EVALUATEANDLOG('Sales'[Quantity] * 'Sales'[UnitPrice], "LineCost")
)
Outcome: The log shows the calculated cost for each row before summation, illustrating how SUMX iterates over the table.
How to Access the Logs
Since EVALUATEANDLOG outputs logs to a DAX Evaluation Log profiler event, you need external tools to capture and visualize them:
SQL Server Profiler: Part of SQL Server Management Studio (SSMS), it can connect to Power BI Desktop’s Analysis Services engine to capture trace events. Requires identifying the port number of the Power BI Desktop instance.
DAX Debug Output: A free, user-friendly tool developed by Jeffrey Wang (pbidax) specifically for visualizing EVALUATEANDLOG output in a GUI. Available at GitHub.
DAX Studio: Supports capturing EVALUATEANDLOG trace events when connected to Power BI Desktop, offering a more integrated experience for DAX developers.
Best Practices and Limitations
Remove Before Publishing: Since EVALUATEANDLOG is disabled in Power BI Service and may impact performance by disabling optimizations, remove it from production models. Tools like DAX Debug Output can scan for leftover instances.
Use Labels: Always specify a label to make logs easier to identify, especially in complex models with multiple EVALUATEANDLOG calls.
Limit MaxRows: For table expressions, set an appropriate MaxRows to avoid generating large logs (logs truncate at 1 million characters to maintain JSON validity).
Understand Truncation: If the output is truncated (e.g., due to MaxRows or size limits), the log includes a “notice” property and the total RowCount to indicate missing data.
Optimization Awareness: Be aware that EVALUATEANDLOG may force the DAX engine to use a less optimal execution plan, which can skew performance analysis if overused.
Example in Action
Suppose you’re analyzing sales data and want to debug a measure calculating the average sales amount per region, but the results seem off:
DAX
AvgSalesPerRegion =
AVERAGEX(
VALUES('Geography'[Region]),
EVALUATEANDLOG(
CALCULATE(SUM('Sales'[SalesAmount])),
"SalesPerRegion"
)
)
Execution: Add this measure to a visual in Power BI Desktop, connect DAX Debug Output, and refresh the visual.
Log Output: The JSON log shows:
Expression: CALCULATE(SUM('Sales'[SalesAmount])).
Label: SalesPerRegion.
Inputs: ['Geography'[Region]].
Data: A list of regions and their calculated sales amounts (e.g., {"input": ["North America"], "output": 50000}, {"input": ["Europe"], "output": 30000}).
Analysis: If “Europe” shows an unexpected value, you can investigate the underlying CALCULATE or data for discrepancies.
Conclusion
The EVALUATEANDLOG function is a powerful ally for DAX developers, offering deep insights into how expressions are evaluated. Its primary use cases—debugging, performance tuning, understanding contexts, and visualizing table expressions—make it invaluable for building robust Power BI models. However, its debugging-only nature means it should be used judiciously and removed from production reports. By combining EVALUATEANDLOG with tools like DAX Debug Output or DAX Studio, you can significantly streamline the process of diagnosing and optimizing DAX code.
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