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Published Release Notes

Find release notes for the selected Pega Version and Capability

Browse resolved issues for Platform releases.

This documentation is for non-current versions of Pega Platform. For current release notes, go here.

Cassandra 3.11.3 support for Pega Platform

Valid from Pega Version 8.3

Increase your system's reliability and reduce its memory footprint by upgrading the internal Cassandra database to version 3.11.3.

For on-premises Pega Platform™ users, after you upgrade to Pega 8.3, it is recommended that you manually upgrade to Cassandra 3.11.3. You can upgrade to Cassandra 3.11.3 on all operating systems except IBM AIX. If you do not want to upgrade to Cassandra 3.11.3, you can continue to use Cassandra 2.1.20, which is still supported.

For Pega Cloud Services 2.13 and later versions, Cassandra automatically upgrades to version 3.11.3 after your environment is upgraded to Pega Platform 8.3.

For information on how to manually upgrade to Cassandra 3.11.3, see the Pega Platform 8.3 Upgrade Guide for your server and database at Deploy Pega Platform.

Upgrade impact

After an on-premises Pega Platform upgrade, you still have the older version of Cassandra and must manually upgrade.

What steps are required to update the application to be compatible with this change?

To upgrade Cassandra, you must create a prconfig setting or a dynamic system setting with the new Cassandra version and then do a rolling restart of all the Decision Data Store nodes to upgrade them to the latest version of Cassandra.

 

Text analytics models editing and versioning

Valid from Pega Version 8.3

Pega Platform™ now supports editing and updating training data for text analytics models.

Pega Platform also supports the versioning of text analytics models. When you update the model, Prediction Studio creates an updated model version. You can then switch between the model versions.

Upgrade impact

In versions of Pega Platform earlier than 8.3, the training data for text models was stored in the database. In Pega Platform version 8.3 and later, the training data for text models is stored in Pega Repository. You cannot build new models without setting the repository. After the repository is set, all text models are automatically upgraded and will work normally.

What steps are required to update the application to be compatible with this change?

After a successful upgrade, set the repository in Prediction Studio before building or updating any Natural Language Processing (NLP) models.  In Prediction Studio, click Settings > Text Model Data Repository.

 

For more information, see:

 

Text analytics models migration

Valid from Pega Version 8.3

Pega Platform™ now supports the exporting and importing of text analytics models. For example, you can export a model to a production system so that it can gather feedback data. You can then update the model with the collected feedback data to increase the model's accuracy.

Upgrade impact

In versions of Pega Platform earlier than 8.3, the training data for text models was stored in the database. In Pega Platform version 8.3 and later, the training data for text models is stored in Pega Repository. You cannot build new models without setting the repository. After the repository is set, all text models are automatically upgraded and will work normally.

What steps are required to update the application to be compatible with this change?

After a successful upgrade, set the repository in Prediction Studio before building or updating any Natural Language Processing (NLP) models.  In Prediction Studio, click Settings > Text Model Data Repository.

 

For more information, see:

Decision Data Store data sets can be used only on DNodes

Valid from Pega Version 7.1.8

Data flows that contain Decision Data Store data sets as the primary or secondary source must be created and executed only on DNodes.

Data flows are not restarted automatically after application server restart

Valid from Pega Version 7.1.8

When you restart the application server or the Pega 7 server, you stop the execution of your data flows. The interrupted batch and real-time runs are marked as Failed

Recommendation:

  • Go to the Designer StudioDecisioning > Decisions > Data Flows > Batch processing tab and start the failed batch runs.
  • Go to the Designer StudioDecisioning > Decisions > Data Flows > Real-time processing tab and activate the failed real-time runs.

 

Value list and value group properties are not supported inside data flows

Valid from Pega Version 7.1.8

Value list and value group properties are not supported inside data flows, and you need to instead use other property types.

See the Pega 7 developer help to check all available property types.

Data flow preview size is fixed to 10

Valid from Pega Version 7.1.8

The Preview option for each shape in data flows returns the first 10 records. This value is fixed and currently cannot be changed.

Data Flow transformation shapes cannot be used in combination with the Compose or Merge shapes

Valid from Pega Version 7.1.8

When you reference another data flow from a data flow that contains the Compose or Merge shape, the referenced data flow cannot contain transformation shapes (EventStrategy, Decision strategy, Convert).

Data flow validation does not currently prevent you from designing a data flow that goes against this design pattern. Make sure that your data flows follow this design pattern by checking the referenced and referencing data flows.

 

Data flow destination is resolved at assembly time

Valid from Pega Version 7.1.8

Data flow execution always uses the design-time destination data sets or destination data flows, regardless of the input records at run time.

Example:

You create a data flow and set the destination to a specific data set. In the data flow, you use a strategy that produces some results. Regardless of these results, the execution of your data flow always uses the destination data set that you specified when you designed the data flow.    

The same applies when you set the destination to a data flow.

 

 

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