Mapping data flow transformation overview
APPLIES TO: Azure Data Factory Azure Synapse Analytics
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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.
Below is a list of the transformations currently supported in mapping data flow. Click on each transformations to learn its configuration details.
Name | Category | Description |
---|---|---|
Aggregate | Schema modifier | Define different types of aggregations such as SUM, MIN, MAX, and COUNT grouped by existing or computed columns. |
Alter row | Row modifier | Set insert, delete, update, and upsert policies on rows. |
Assert | Row modifier | Set assert rules for each row. |
Cast | Schema modifier | Change column data types with type checking. |
Conditional split | Multiple inputs/outputs | Route rows of data to different streams based on matching conditions. |
Derived column | Schema modifier | Generate new columns or modify existing fields using the data flow expression language. |
External call | Schema modifier | Call external endpoints inline row-by-row. |
Exists | Multiple inputs/outputs | Check whether your data exists in another source or stream. |
Filter | Row modifier | Filter a row based upon a condition. |
Flatten | Formatters | Take array values inside hierarchical structures such as JSON and unroll them into individual rows. |
Flowlet | Flowlets | Build and include custom re-usable transformation logic. |
Join | Multiple inputs/outputs | Combine data from two sources or streams. |
Lookup | Multiple inputs/outputs | Reference data from another source. |
New branch | Multiple inputs/outputs | Apply multiple sets of operations and transformations against the same data stream. |
Parse | Formatters | Parse text columns in your data stream that are strings of JSON, delimited text, or XML formatted text. |
Pivot | Schema modifier | An aggregation where one or more grouping columns has its distinct row values transformed into individual columns. |
Rank | Schema modifier | Generate an ordered ranking based upon sort conditions |
Select | Schema modifier | Alias columns and stream names, and drop or reorder columns |
Sink | - | A final destination for your data |
Sort | Row modifier | Sort incoming rows on the current data stream |
Source | - | A data source for the data flow |
Stringify | Formatters | Turn complex types into plain strings |
Surrogate key | Schema modifier | Add an incrementing non-business arbitrary key value |
Union | Multiple inputs/outputs | Combine multiple data streams vertically |
Unpivot | Schema modifier | Pivot columns into row values |
Window | Schema modifier | Define window-based aggregations of columns in your data streams. |