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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:

Problem with truncating Decision Data Store data set

Valid from Pega Version 7.1.9

The Truncate operation for the Decision Data Store data set may cause timeout exceptions. This problem is caused by the Apache Cassandra database that waits until compaction tasks finish before it can truncate the data set.

Recommendation:

Repeat the Truncate operation until it is successful.

The UpdateAdaptiveModels agent causes an exception after Pega 7.2 to 7.2.1 upgrade

Valid from Pega Version 7.2.1

After the Pega 7 Platform is upgraded from version 7.2 to 7.2.1, the log files might show an error that is caused by the UpdateAdaptiveModels agent. This agent is enabled by default and is responsible for updating scoring models in the Pega 7 Platform. If you use adaptive models in your solution, you can avoid this error by configuring the Adaptive Decision Manager service. If you do not use adaptive models, disable the UpdateAdaptiveModels agent.

For more information, see Configuring the Adaptive Decision Manager service and Pega-DecisionEngine agents.

Reconfiguration of the Adaptive Decision Manager service after upgrade to Pega 7.2.1

Valid from Pega Version 7.2.1

After you upgrade the Pega 7 Platform to version 7.2.1, you need to reconfigure the Adaptive Decision Manager service. Beginning with Pega 7.2.1, the Adaptive Decision Management (ADM) service is native to the Pega 7 Platform and is supported by the Decision data node infrastructure.

For more information, see Services landing page.

Interactions in flows are no longer supported by the Run Interaction shape

Valid from Pega Version 7.3.1

The Run Interaction shape in flows has been replaced by the Run Data Flow shape, which supports running a single case data flow with a strategy. Flows that include the Run Interaction shape continue to work; however, you must now use the Utility shape to reference any new interactions that you create.

For more information, see Running a decision strategy from a flow and About Interaction rules.

Extension attributes are not supported in PMML models

Valid from Pega Version 7.3.1

Models in the Predictive Model Markup Language (PMML) format version 4.3 that contain extension attributes with the x- prefix are not valid. These extension attributes are deprecated; you must use extension elements instead. In addition, if the output type of any output field in the model is set to FLOAT, change it to DOUBLE.

For more information, see PMML 4.3 - General Structure in the Data Mining Group documentation.

The Upload responses action is not supported for adaptive models with customized context

Valid from Pega Version 7.3.1

A default instance of the Adaptive Model rule contains five model identifiers (.pyIssue, .pyGroup, .pyName, .pyDirection, .pyChannel) that are used to partition adaptive models. If you add other identifiers in your Adaptive Model rule instance, you cannot upload responses to this instance with the Upload Responses wizard and the following error is displayed: The Flow Action post-processing activity pzUploadCSVFile failed: Cannot parse csv file.You can still train such adaptive models with data flows.

For more information, see Training adaptive models in bulk with data flows, Model context, and Uploading customer responses.

Upgrading Adaptive Decision Manager data mart tables might fail

Valid from Pega Version 7.3.1

Issue: Upgrade from 7.3 to 7.3.1 fails if the data contained in the pxInsName column of the PR_DATA_DM_ADMMART_PRED_FACT table is longer than 128 characters.

Reason: During the Pega Platform™ upgrade from 7.3 to 7.3.1, data in the Adaptive Decision Manager (ADM) data mart tables is migrated from the PR_DATA_DM_ADMMART_PRED_FACT table to the PR_DATA_DM_ADMMART_MDL_FACT table. In Pega 7.3.1, ADM uses only the PR_DATA_DM_ADMMART_MDL_FACT table where the pxInsName property can store values that are 128 characters long. In Pega Platform 7.3, the pxInsName property in the PR_DATA_DM_ADMMART_PRED_FACT table can store values that are 255 characters long. If the pxInsName property contains values that are longer that 128 characters, the upgrade fails.

Resolution: Issue an ALTER TABLE statement to change the pxInsName column size to 255 characters and resume the upgrade. For example:

ALTER TABLE rules.pr_data_dm_admmart_pred ALTER COLUMN pxInsName TYPE varchar(255);

For more information, see Adaptive Decision Manager data model.

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