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Resolved Issues

View the resolved issues for a specific Platform release.

Go to download resolved issues by patch release.

Browse release notes for a selected Pega Version.

NOTE: Enter just the Case ID number (SR or INC) in order to find the associated Support Request.

Please note: beginning with the Pega Platform 8.7.4 Patch, the Resolved Issues have moved to the Support Center.

INC-143121 · Issue 610732

Timeout for loading predictors made configurable

Resolved in Pega Version 8.3.6

When using an extremely large number of predictors, the Report definition pzADMPredictorsFilter was suffering timeouts due to the time for loading predictors from the database exceeding the time threshold allowed. This has been resolved by marking the rule as editable to allow custom setting of the threshold according to need.

INC-148899 · Issue 615702

Adaptive models update correctly

Resolved in Pega Version 8.3.6

Some models had the recorded responses column updated, but the models (number of Positive, Negative and Processed Responses) were not updated. Investigation showed that deleting the modelRuleConfiguration through the stateManager/client did not delete modelFactories related to the configuration. If a new configuration came in with a different algorithm, the update issue occurred. This has been resolved by reseting the configuration according to its factory in that specific case.

INC-155822 · Issue 618267

Locking added to avoid null pointer error for auto-populate property

Resolved in Pega Version 8.3.6

After configuring the auto populate property "OrgProduct" which referred to a data page, the system experiencing heavy load led to the property not getting properly initialized. This resulted in a WrongModeException and NullPointerException. To resolve this, the system has been updated to lock the requestor when Queue Processors execute their activity. This will prevent race conditions and concurrent modifications if other threads are accessing the same requestor.

INC-157629 · Issue 626633

Duplicate key exception resolved for adaptive model

Resolved in Pega Version 8.3.6

During the model snapshot update, a DuplicateKeyException was generated while trying to insert a record in to the predictor table. This did not affect the model's learning, but did appear ion the model monitoring report. This was traced to a local scenario of having the same outcome values defined on the model with different cases (Accept and accept). All predictors used in an Adaptive model are inserted into the model monitoring tables as a part of the monitoring job: because the monitoring tables are not case sensitive, this lead to a unique constraint exception since there were multiple IH predictors with the same name. To resolve this, validation has been added which will skip adding duplicates from new responses.

INC-160331 · Issue 628710

ML model continue tag error changed to debug logging

Resolved in Pega Version 8.3.6

Log entries were seen indicating "The continue tag is found without a start tag for window Line1 1234567890 in text". This appeared to be coming from the MLCommand java class. Investigation showed this occurred when the ML model believed a portion of the text (token) was a continuation of the entity because it has not found the starting part of the entity. This situation is not currently treated as a valid output, so an update has been made to change the logging level from error to debug for this case.

SR-69015 · Issue 619995

Unescaping characters implemented for expressions

Resolved in Pega Version 8.3.6, Resolved in Pega Version 8.4.4, Resolved in Pega Version 8.5.3, Resolved in Pega Version 8.6

An issue where expression builder statements were evaluated differently at runtime than at testing has been resolved. Pega Platform expressions with String literals(that is, sequences of characters enclosed in quotation marks) now unescape characters in strategy shapes such as Set Property or Filter.

INC-202111 · Issue 710105

Logging extended for PRPCPropertyInfoProvider

Resolved in Pega Version 8.6.5

In order to assist with diagnosing issues with Kafka and JSON, additional logging has been added for PRPCPropertyInfoProvider.

INC-208976 · Issue 719166

Enhanced SSA metrics made available

Resolved in Pega Version 8.6.5

In order to better diagnose delays related to the time when a Campaign is scheduled to start and the time when the Dataflow actually starts to run, an update has been made which will generate detailed metrics to cover some of the strategy execution key performance intensive areas. Additional lower level internal metrics related to SSA engine execution have also been made available by way of a DSS to collect more runtime insight for diagnosis. To enable the collection of these Level 2 SSA internal metrics, set the dataflow/shape/strategy/detailed_metrics/level2 DSS in the Pega-DecisionEngine rule set to 'true'. A comprehensive set of enhanced metrics will be available in Pega 8.8.

INC-213217 · Issue 714194

Updated context handling for executing data transforms in dataflows

Resolved in Pega Version 8.6.5

When performing a sort operation in a data transform on a page list and invoking the Data transform through a Data flow, a java.lang.UnsupportedOperationException was generated on the sort step even though the data was correct. Investigation showed that the dataflows were using a different execution context than the context used for regular activity execution. An update has been made to ensure the correct context is being used while executing data transforms in dataflows.

INC-215601 · Issue 721524

Explicit Kerberos renewal added for HDFS

Resolved in Pega Version 8.6.5

When using WebSphere/IBM with Hadoop connectivity, the Kerberos credentials were expiring after 7 days and causing connectivity failures. Investigation showed the Apache Hadoop HDFS Client was not renewing the ticket even when there were operation calls every few hours. To resolve this, an enhancement has been added to the Pega HDFS client which will explicitly tell Hadoop authentication layer to check for Kerberos ticket renewal instead of relying on Hadoop built-in logic.

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