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APPLIES TO:
Azure Data Factory
Azure Synapse Analytics
Tip
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Data flows are available both in Azure Data Factory and Azure Synapse Pipelines. This article applies to mapping data flows. If you are new to transformations, please refer to the introductory article Transform data using a mapping data flow.
The following articles provide details about metafunctions supported by Azure Data Factory and Azure Synapse Analytics in mapping data flows.
Metafunctions primarily function on metadata in your data flow
Metafunction | Task |
---|---|
byItem | Find a sub item within a structure or array of structure. If there are multiple matches, the first match is returned. If no match it returns a NULL value. The returned value has to be type converted by one of the type conversion actions(? date, ? string ...). Column names known at design time should be addressed just by their name. Computed inputs aren't supported but you can use parameter substitutions |
byOrigin | Selects a column value by name in the origin stream. The second argument is the origin stream name. If there are multiple matches, the first match is returned. If no match it returns a NULL value. The returned value has to be type converted by one of the type conversion functions(TO_DATE, TO_STRING ...). Column names known at design time should be addressed just by their name. Computed inputs aren't supported but you can use parameter substitutions. |
byOrigins | Selects an array of columns by name in the stream. The second argument is the stream where it originated from. If there are multiple matches, the first match is returned. If no match it returns a NULL value. The returned value has to be type converted by one of the type conversion functions(TO_DATE, TO_STRING ...) Column names known at design time should be addressed just by their name. Computed inputs aren't supported but you can use parameter substitutions. |
byName | Selects a column value by name in the stream. You can pass an optional stream name as the second argument. If there are multiple matches, the first match is returned. If no match it returns a NULL value. The returned value has to be type converted by one of the type conversion functions(TO_DATE, TO_STRING ...). Column names known at design time should be addressed just by their name. Computed inputs aren't supported but you can use parameter substitutions. |
byNames | Select an array of columns by name in the stream. You can pass an optional stream name as the second argument. If there are multiple matches, the first match is returned. If there are no matches for a column, the entire output is a NULL value. The returned value requires a type conversion function (toDate, toString, ...). Column names known at design time should be addressed just by their name. Computed inputs aren't supported but you can use parameter substitutions. |
byPath | Finds a hierarchical path by name in the stream. You can pass an optional stream name as the second argument. If no such path is found, it returns null. Column names/paths known at design time should be addressed just by their name or dot notation path. Computed inputs aren't supported but you can use parameter substitutions. |
byPosition | Selects a column value by its relative position(1 based) in the stream. If the position is out of bounds, it returns a NULL value. The returned value has to be type converted by one of the type conversion functions(TO_DATE, TO_STRING ...) Computed inputs aren't supported but you can use parameter substitutions. |
hasPath | Checks if a certain hierarchical path exists by name in the stream. You can pass an optional stream name as the second argument. Column names/paths known at design time should be addressed just by their name or dot notation path. Computed inputs aren't supported but you can use parameter substitutions. |
originColumns | Gets all output columns for an origin stream where columns were created. Must be enclosed in another function. |
hex | Returns a hex string representation of a binary value |
unhex | Unhexes a binary value from its string representation. This can be used with sha2, md5 to convert from string to binary representation |
Events
Mar 31, 11 PM - Apr 2, 11 PM
The biggest Fabric, Power BI, and SQL learning event. March 31 – April 2. Use code FABINSIDER to save $400.
Register todayTraining
Module
Introduction to expressions in Power Automate - Training
Learn how to write expressions in Power Automate.
Certification
Microsoft Certified: Fabric Data Engineer Associate - Certifications
As a Fabric Data Engineer, you should have subject matter expertise with data loading patterns, data architectures, and orchestration processes.
Documentation
Cached lookup functions in the mapping data flow - Azure Data Factory & Azure Synapse
Learn about cached lookup functions in mapping data flow.
Aggregate functions in the mapping data flow - Azure Data Factory & Azure Synapse
Learn about aggregate functions in mapping data flow.
Map functions in the mapping data flow - Azure Data Factory & Azure Synapse
Learn about map functions in mapping data flow.