This topic is for data modellers, application designers and system administrators. The pages in this topic explain how to create and run automated tasks in PhixFlow. It also explains strategies for tasks that affect

tables. 

The pages in this topic are:

Overview

When working with data, applications and IT systems, there are routine processes that you need to run. PhixFlow makes it easy for you to set up and manage these processes using tasks and task plans. For example:

• application designers or system administrators can automatically update data in applications
• data

• modellers can run analysis on models or specific

• tables
• administrators can clear old information from the PhixFlow system, by archiving data from:

• • record sets
  • processing logs
  • performance statistics.

Use the task plan properties tab to configure Task Plans. Set the options and add individual Tasks.

If you need to temporarily prevent scheduled task plans from running during system maintenance, see Preventing Task Plans From Running.

Structuring Tasks

When setting up task plans with tasks that affect

tables, you must consider whether the

tables have any dependencies. This affects your options when structuring tasks in task plans.

Multiple tasks each

affecting one

table

If there are dependencies between

tables, configure PhixFlow to have one task per

table and configure each task to be mandatory. 

1. Create a set of tasks.
   • Each task works on a single

1. • table.
   • Set the tasks to be mandatory.
2. Add the set of tasks to the task plan.

PhixFlow processes the tasks, and therefore the

tables, in order. PhixFlow must finish a task successfully before it starts to update the next

table. This is the safest way to set up tasks that affect

tables. Always use this method when there are dependencies between

tables.

Or one task

affecting multiple

tables

If there are no dependencies between

tables, you can add multiple

tables to the task. In this case you have no control over the order in which

tables will be processed. Only use this method if there is you are sure there are no dependencies between the

tables.

1. Create a task
2. Add multiple

1. tables to a task
2. Add the task to the task plan. 

This has the advantage that you only need to configure one task to change multiple

tables.

Mandatory Tasks

The tasks are run in the order they are listed in the the task plan.

You can specify that a task in a task plan is mandatory. This means the task must complete before the next task in the sequence can run. If a mandatory task fails, PhixFlow will not run the following tasks. You must resolve the issue preventing the task from running and then restart the task.

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task-type task-type

Types of Task

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  analysisTask analysisTask

  Analysis Tasks
  Use an analysis task to run analysis on the

• table(s) in the task. 
  
  

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  rollbackTask rollbackTask

  Rollback Tasks
  Use a rollback task to effectively undo run analysis

• on a

• table. 

• When you run a rollback task it rolls back all data in each of the listed

• tables, deleting the

• record-sets. The list of

• record-sets is empty and there are no data records in the

• table. For information about how to rollback

• tables manually, see Rollback

• Recordsets.
  
  

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  configExportTask configExportTask

  Configuration Export Tasks
  Use a configuration export task to export selected applications and packages or a full configuration. The exported file is saved to the download area; see Using the Download Area. 
  
  

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  systemTask systemTask

  System Tasks
  Use a system task to perform system-wide housekeeping activities. These include deleting:
  • managed file entries
  • email entries
  • temporary files created by file exporters to send by email
  • data from incomplete

• • record-sets
  • log messages and optionally archiving them
  • from the PhixFlow database:

• • • table views for which there is

• • • no table

• • • tables for which there is no

• • • table object, when they are older than the period set in System Configuration → Delete Orphaned

• • • Table after Days. 
      

• • • Tables become orphaned when their

• • • table object is deleted or removed by an import process.
    • temporary tables created during publishing, when they are older than the period set in System Configuration → Delete Temp Tables after Days.
      Temporary tables are created by PhixFlow during the publishing process.

  Note
  The system task should be run regularly, for example daily or weekly. When the system task is not run regularly, incomplete

• record-sets can accumulate. If these are large, or many have

• accumulated, this can slow down PhixFlow's performance. Depending on your PhixFlow database, queries that have to exempt many incomplete

• record-sets can reach system limits. This can prevent PhixFlow and its applications from running.

  How long PhixFlow keeps system information, and whether to archive log messages before they are deleted, are controlled by the following parameters in System Configuration:

  • Delete Log Messages After Days
  • Archive Deleted Log Messages To File
  • Delete Statistics After Days
  • Delete Emails After Days

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  archiveTask archiveTask

• Table-Data-Delete Tasks
  Use a

• table-data-delete task to delete data records and

• record-sets that you no longer need in PhixFlow. How long PhixFlow keeps

• table data is configured in

• table properties → Data Retention Settings.
  Running a

• table-data-delete task on a large number of

• tables, or on

• a table with a large data set, can take some time. We recommend scheduling these tasks for times when the system is quiet, for example overnight.
  When

• tables are deleted from the repository, their names are automatically be removed from tasks that refer to them. This means a saved task can become empty.
  

  Note
  Phixflow only runs a

• table-data-delete task on

• tables that have Data Retention Settings specified. If no data retention values are set, PhixFlow never deletes the data.

• table data will accumulate, leading to space and performance issues.

  See also 

• Deleting Old Data. 

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