[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC):2025-09-03。"],[[["\u003cp\u003eData mapping is crucial for integrating data from various sources into a unified model, involving extracting, standardizing, and relating data to target fields.\u003c/p\u003e\n"],["\u003cp\u003eApplication Integration offers two primary tasks for data mapping: the Data Transformer task, which uses Jsonnet and a visual Diagram mode, and the Data Mapping task, a no-code/low-code option with a visual editor.\u003c/p\u003e\n"],["\u003cp\u003eThe Data Transformer task, currently in preview, allows users to create data mapping using Jsonnet templates and features a Diagram mode for visual mapping, while the Script mode allows custom mapping logic using supported functions.\u003c/p\u003e\n"],["\u003cp\u003eThe Data Mapping task provides a user-friendly visual editor, enabling the mapping of single or nested variables and the application of transformation functions to modify data types and formats.\u003c/p\u003e\n"],["\u003cp\u003eBoth Data Transformer and Data Mapping tasks support the use of predefined transformation or mapping functions to manipulate and standardize data, with mappings in the Data Mapping editor executing sequentially from top to bottom.\u003c/p\u003e\n"]]],[],null,["# Data mapping\n\nSee the [supported connectors](/integration-connectors/docs/connector-reference-overview) for Application Integration.\n\nData mapping\n============\n\nEnterprise data might reside in various sources and formats, making it difficult to integrate them into a unified data model or data pipeline. Data mapping is the process of extracting and standardizing data from multiple sources in order to establish a relationship between them and the related target data fields in the destination. Some examples of using data mapping in an integration include the following:\n\n- Extracting fields from a complex data structure such as a JSON.\n- Mapping data source to the target schema.\n- Transforming data by appling transform functions.\n- Generating output values and storing/using them as integration variables.\n\nApplication Integration lets you perform data mapping using the following [tasks](/application-integration/docs/task-overview):\n\n- [Data Transformer task](#data-transformer) ([Preview](/terms/service-terms#1))\n- [Data Mapping task](#datamapper)\n\nData Transformer task\n---------------------\n\n|\n| **Preview\n| --- Data Transformer task**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nThe [Data Transformer](/application-integration/docs/configure-data-transformer-script-task) task is a template engine-based data mapping feature available in Application Integration. It uses Google's [Jsonnet](https://jsonnet.org/) configuration language to create and edit Jsonnet templates that define the mapping relationships for specified source and target integration variables in your integration. The **Data Transformer** task also provides a visual mapping canvas (Diagram mode) to perform data assignments and mappings in your integrations.\n\n\n### Diagram mode\n\nThe *Diagram mode* provides a visual canvas containing the following integration elements:\n\n- **Input**. Displays the input variables of the data transformation. The source can be variables or constants. To assign an input variable, you can either select an existing variable or create a new variable. These variables are mapped with the related output variables by clicking the input element and dragging the line to map with the related output variable.\n- **Output**. Displays the output variables of the data transformation. Target variables can be used for mapping in subsequent input rows. To assign an output variable, you can either select an existing variable or create a new variable.\n- **Canvas**. The canvas is used to visually map the input and output variables.\n\nFor more information about variables in Application Integration, see [Using variables in Application Integration](/application-integration/docs/variables).\nThe following image shows the sample layout of the *Data Transformer diagram mode* :\n\n\n#### Transformation operations\n\n\nYou can use the predefined [transformation operations](/application-integration/docs/data-transformer-functions-reference) to transform and standardize mapping data in your integration. Transformation operations can have one or more input parameters, where each parameter can hold a literal value or a variable. You can use multiple mapping functions for a single input source, forming a mapping transform expression.\n\nThe end data type of an input source is based on the return type of the transform expression defined in the respective data mapping input row.\n\n### Script mode\n\nUsing the **Data Transformer Script editor** and the supported [Data Transformer functions](/application-integration/docs/data-transformer-functions-reference) you can write custom data mapping logic, perform variable assignments, and add or modify integration variables.\nThe following image shows the sample layout of the **Data Transformer Script editor** :\n\n\nFor information about how to add and configure the **Data Transformer** task, see\n[Data Transformer task](/application-integration/docs/configure-data-transformer-script-task).\n\nData Mapping task\n-----------------\n\nThe **Data Mapping** task is a no-code low-code feature in Application Integration that provides a visual mapping canvas--[Data Mapping editor](#editor)--to perform data assignments and mappings in your integrations. In addition, you can also use the supported [mapping functions](#functions) to further transform your data into meaningful variables/formats to make them accessible to the other tasks or triggers in\nyour integration.\n\nWith the **Data Mapping** task, you can:\n\n- Use the [Data Mapping editor](#editor) to visualize and define variable mapping for single or nested variables.\n- Transform variables from one data type to another data type. The **Data Mapping** task lets you apply multiple mapping functions (including nested functions) to transform the variable data.\n\nFor information about how to add and configure the **Data Mapping** task, see [Data Mapping task](/application-integration/docs/configure-data-mapping-task).\n\n### Data Mapping editor and layout\n\nThe **Data Mapping editor** provides a visual canvas containing the following integration elements:\n\n- **Variables** pane: Displays the different types of variables that are available to the integration:\n - **Inputs**. Input variables of the integration.\n - **Outputs**. Output variables of the integration.\n - **Local Variables**. Variables that exist within the scope of the integration.\n\n If no variables are listed, click **Add +** to configure a new variable.\n Click chevron_right **(Expand)** to expand each variable and view the available subfields of that variable. To search for any variable or its subfield from the available variable list, click search **(Search variables)** .\n\n\n For more information about variables in Application Integration, see [Variables](/application-integration/docs/variables).\n- **Input** column: Displays input mapping rows containing the source of the data mapping input. Source can be a literal value, a base function, or an input variable, with [mapping functions](#mapping-functions). Click **Variable or Value** in an input mapping row to add a source. **Tip:** To add an input variable,you can directly drag and drop a variable from the **Variables** column to the **Input** column.\n- **Output** column: Displays the output mapping rows containing the related target variables for the respective input mapping row. Target variables can be used for mapping in subsequent input rows. To assign an output variable, you can either create a new variable or directly drag and drop an existing output variable from the **Variables** column.\n\nThe following image shows the sample layout of the **Data Mapping editor** :\n\n\n### Mapping functions\n\n\nThe **Data Mapping** task provides various predefined [mapping functions](/application-integration/docs/data-mapping-functions-reference) to transform and standardize the mapping data in your integration. A mapping function can have one or more input parameters, wherein each parameter can further hold a literal value, a variable, or a base function with mapping functions applied. You can use multiple mapping functions for a single input source, forming a mapping [transform expression](#transform).\n\nThe end data type of an input source is based on the return type of the transform expression defined in the respective data mapping input row. The **Data Mapping editor** displays a validation error error under the respective data mapping input row if the return type of the input source doesn't match the return type of the corresponding output mapping target variable.\n\n### Transform expression\n\n\nA transform expression is a combination of several [mapping functions](/application-integration/docs/data-mapping-functions-reference) that are either chained together in-series or in a nested structure. Using the **Data Mapping editor** , you can easily insert, modify, or remove a function or a function parameter in a defined transform expression. If the defined transform expression is invalid, the **Data Mapping editor** displays a validation error error next to the respective function or function parameter that is causing the error in the expression. To view the complete error message, hold the pointer over the validation error error icon.\nThe following image shows a sample mapping with validation errors in the **Data Mapping editor** :\n\n\nFor more information about how to configure a mapping in a **Data Mapping** task, see [Add a mapping](/application-integration/docs/configure-data-mapping-task#add-map).\n\n\nFor information about the supported pre-defined mapping functions in Application Integration, see [Supported data types and mapping functions](/application-integration/docs/data-mapping-functions-reference).\n\n### Mapping order\n\nMappings specified in the **Data Mapping editor** are run in sequence from top to bottom. For example, in the preceding image, `Num1` is mapped to `Num1ToInt` in the first row, making `Num1ToInt` available for mapping in the subsequent rows.\n\nQuotas and limits\n-----------------\n\nFor information about quotas and limits, see [Quotas and limits](/application-integration/docs/quotas).\n\nWhat's next\n-----------\n\n- Add and configure a [Data Transformer task](/application-integration/docs/configure-data-transformer-script-task) ([Preview](/terms/service-terms#1))\n- Learn about [Data Transformer functions](/application-integration/docs/data-transformer-functions-reference) ([Preview](/terms/service-terms#1))\n- Add and configure a [Data Mapping task](/application-integration/docs/data-mapping-task)"]]