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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.

Define partitioning of stream data sets

Valid from Pega Version 7.3

You can define partition keys for Data Set rules of type Stream to group similar properties and to process Data Flow rules that contain stream data sets more efficiently across multiple Data flow service nodes. Use this feature only for testing in non-production application environments.

For more information, see Partition keys in Stream Data Set rules.

Create specialized Decision Data rules for text analytics resources

Valid from Pega Version 7.3

You can store various types of resources for text analytics in Decision Data rules that are based on templates. Each resource type (for example, sentiment analysis models, taxonomies, entity extraction rules, and so on) has its own definition class that defines the appearance of the corresponding Decision Data rule form. With this enhancement, system architects can create and maintain various text analytics-related artifacts without having to edit the default Decision Data form fields first.

For more information, see Definition class of text analytics Decision Data rules.

Unable to create text analytics models when Java 2 Security is enabled

Valid from Pega Version 7.3

Security exceptions that prevent you from creating text analytics models are caused by the Java 2 Security feature that is enabled at the JVM level. This feature denies access to the text analytics resources that are required for text parsing functions.

Creating a text analytics model results in a failure because of a number of security-related exceptions, for example:

java.security.AccessControlException: Access denied ("java.lang.RuntimePermission""createSecurityManager")

The suggested approach for avoiding this problem is to use the text analytics models that are provided by default, for example, pySentimentModels, pyTelecomTaxonomy, and so on.

For more information, see Text Analyzer.

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