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Configure an HTTP extraction

Configure an HTTP extraction for extracting data using the REST-API. For an HTTP extraction, you can specify one or more endpoints that provide the data for your extraction. For each endpoint, you must define a data request and specify what the response structure looks like.

Prerequisite

You created an HTTP extraction.

Procedure. Procedure

  1. Open a data set.

  2. Click Extraction in the Data set panel. The Extractions section opens.

  3. Click an HTTP extraction in the extraction list. The configuration view of the HTTP extraction opens.

  4. On the Endpoints tab, click Add endpoint. The endpoint opens and displays the Request.

    You can define one or more endpoints for an extraction. The endpoints are listed on the Endpoints tab.

  5. Configure the endpoint request.

    1. Click Request to display the request options.

    2. Enter an endpoint name in the Name field.

    3. Specify an endpoint URL according to the API of the data source system.

    4. You can define parameters for the query, if required. The parameters are automatically added to the endpoint URL. Query parameters are available only for the selected endpoint.

      Click Query parameters.

      Click + Add parameter.

      Specify a key and a value for each query parameter.

      Example

      <endpoint URL>?parameter(1)=value(1)&parameter(2)=value(2)

  6. Configure the endpoint response.

    1. Click Responds to display the response options.

    2. Click Fetch structure from sample. The JSON structure of the endpoint is determined and displayed in the Response data structure field. The data structure of the first entry of the source table is used to detect the columns of the data source. However, you can also define the response data structure in the input field manually.

      The data source is read and the source table name and the table columns are automatically listed with their namespace and data type next to the field.

      You can reduce the data structure of the data source. When you reduce the data structure of a data source, you are reorganizing it to remove any unstructured data or redundant data to enable a superior, more logical means of storing that data. To do that, click Reduce data in the Response data structure input field.

      Note

      If an HTTP response cannot be parsed into JSON format because the data structure of the response does not correspond to a valid JSON data format, for example due to a syntax error or because the data is in HTML format, the raw data of the endpoint is displayed and a corresponding error message is issued.

    3. Select the element in the JSON structure as the data root element that contains the individual records. You can select the data root from the corresponding drop-down menu. If the response structure has nested tables (arrays in the JSON structure), select a custom root table. Only the tables that are children of that table are then imported. Other data is ignored.

    4. Delete all elements from the JSON structure that are not to be transferred to ARIS Process Mining.

    5. To change the data type of a column, select a data type from the Type drop-down menu in the column list.

      The data format is determined automatically. If the data type cannot be determined (for example, because the value is null), no data type is preselected. You must select the data type for these columns manually. If no data type is selected, the column is ignored.

    6. You can specify the format of date and number (long and double) columns.

      Click the administration icon of a date or number (long and double) column. A corresponding dialog opens.

      Select a format from the drop-down menu.

      Click Done.

    7. You can specify how empty values in the source table should be handled for Date, Long, and Double type. By default, empty values are considered as null.

      Click the administration icon of a column. A corresponding dialog opens.

      Enable or disable the option to allow empty values for the selected Date, Long, or Double data type. If the option is enabled, empty values are considered as null and the corresponding columns of the source table are displayed without values. If the option is disabled the corresponding columns of the source table are ignored and not displayed.

      Click Done.

    8. You can select the columns to be used as key columns in the Key column of the target source table.

      You defined the response data structure.

      The user interface displays toggle options that allow users to specify whether empty values are permitted for different data types. These labels are type-specific rather than using a generic label such as "Allow empty values for numbers." The toggle labels shown in the UI are as follows:

      Date: Allow empty values for date

      Long: Allow empty values for long

      Double: Allow empty values for double

You configured an HTTP extraction.

You can now extract the data from the data source.

Additional settings

You have further options to refine the data extraction.