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Table of Contents

Data flow methods

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Data flows can be run, monitored, and managed through a rule-based API. Data-Decision-DDFRunOptions is the container class for the API rules and provides the properties required to programmatically configure data flow runs. Additionally, the DataFlow-Execute method allows you to perform a number of operations that depend on the design of the data flow that you invoke.

The following methods support the use of data flows in activities:

  • Running a data flow

    Use the Call instruction with the Data-Decision-DDF-RunOptions.pxStartRun and Data-Decision-DDF-RunOptions.pxRunDDFWithProgressPage activities, or the DataFlow-Execute method to trigger a data flow run.

  • Running a data flow in single mode

    Use the Call instruction with the Data-Decision-DDF-RunOptions.pxRunSingleCaseDDF activity to trigger a data flow run in single mode. Only data flows with an abstract source can be run in this mode.

  • Specializing activities

    Use the Call instruction with the Data-Decision-DDF-RunOptions.pyPreActivity and Call Data-Decision-DDF-RunOptions.pyPostActivity activities to define which activities should be run before and after batch or real-time data flow runs that are not single-case runs. Use the activities to prepare your data flow run and perform certain actions when the run ends. Pre-activities run before assignments are created. Post-activities start at the end of the data flow regardless of whether the run finishes, fails, or stops. Both pre- and post-activities

  • Managing data flows

    You can use the Call instruction with several activities to start, stop, or delete data flow instances that are identified by the runID parameter.

  • Monitoring data flows

    Use the Call instruction with several activities to track the status of data flows that were run in batch mode with the Call Data-Decision-DDF-RunOptions.pxRunDDFWithProgressPage method or submitted on the Data Flows landing page. You can track the number of processed records, and the elapsed or the remaining time of the data flow run.

  • DataFlow-Execute method

    Apply the DataFlow-Execute method to perform data management operations on records from the data flow main input. By using the DataFlow-Execute method, you can automate these operations and perform them programmatically instead of doing them manually. For example, you can configure an activity to start a data flow at a specified time.

  • Types of data flows

    Data flows are scalable data pipelines that you can build to sequence and combine data based on various data sources. Each data flow consists of components that transform data and enrich data processing with business rules.

  • Calling another activity
  • DataFlow-Execute method

    Apply the DataFlow-Execute method to perform data management operations on records from the data flow main input. By using the DataFlow-Execute method, you can automate these operations and perform them programmatically instead of doing them manually. For example, you can configure an activity to start a data flow at a specified time.

  • Decision Management methods

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