INC-159216 · Issue 638931
DSS added to create consistent handling of longform datetime
Resolved in Pega Version 8.4.5
After upgrade, a difference in handling related to datetime value was seen. For example, EmailSchedRunEndDate is a date type property holding the value "20201016T000000.000 GMT"; in Pega v7.4, a substring function was used to move the extra characters from the date field ex. EmailSchedRunStartDate = @substring(.EmailSchedRunStartDate,0,8), but in Pega v8.4 and higher the long datetime value ( "20201016T000000.000 GMT") was still being used for the date field. This long value was then truncated to 2020101+ when saving to the database, causing errors in later steps. However, research found that if there is a call @toDate function before this step for any other field, the correct date value was set for EmailSchedRunStartDate. While ClipboardPages separate Dates and DateTimes, internally, in Java, both have a time component. The implementation of DSMClipboardPage made no difference for serialization and appended the time component for pure Date properties. To create consistent handling, an update has been made to optionally set the correct behavior after setting the Dynamic System Setting by way of "Pega-DecisionEngine dsm/clipboard/correctDateFormat -> true". This setting would only take effect after a restart of Pega, and the default is false in order to not disrupt any application inadvertently relying on this behavior.
INC-140160 · Issue 597037
NLP model update reflected on utility nodes
Resolved in Pega Version 8.5.2
After training models on a web node, model updates were not reflected in the email listeners running on the utility nodes. This was traced to the implementation of the model storage using obj-save, which does not propagate the static content on nodes apart from where it was saved. To resolve this, the implementation has been updated to use WBSave which clears static content on all the nodes.
INC-167334 · Issue 639316
GRS support added for Kafka Key password
Resolved in Pega Version 8.4.5
An enhancement has been added to support using GRS to set values for the Kafka Key password dynamically.
INC-186437 · Issue 685015
Updated entity attachment extraction tokenizers
Resolved in Pega Version 8.7
After creating an entity extraction model, it was seen that one of the entities worked when there was a space after the semicolon but the detection was not working if there was no space. This has been resolved by updating the Tokenizers with extra examples to address tokenization when ":" is present between two words without any spaces.
INC-168271 · Issue 640347
ADM performance improvements and duplicate inputs corrected for delayed learning records
Resolved in Pega Version 8.7
Additional work has been done to improve the performance for Adaptive Models used in multi-level decisioning, and an issue with duplicate pxCommonInputs has been resolved.
INC-193986 · Issue 680032
Parameter logic updated for metrics activity counter
Resolved in Pega Version 8.7
An error was causing the PushCDHMetrics agent to fail. This was traced to an undefined parameter in the activity which was used as a counter, and has been resolved by replacing it with a local variable of type integer.
INC-169544 · Issue 649540
Enhancement for MaxEnt modeling data
Resolved in Pega Version 8.4.5
An enhancement has been added to create output for the model coefficients, the term frequency, and the inverse term frequency for use in maximum entropy modeling. For MRM processes, every Maximum Entropy (Maxent) based topic model will contain two additional stats resources. These resources can be used to validate and replicate running of topic model outside of Pega. The resources are: 1) Term Frequency file – A CSV file with all words used for training and their cumulative frequency across training set. File name format – TRAINING_DATA_TERM_FREQUENCY_< RandomNumber >.csv olumns – Word, Count 2) Coefficient file – A CSV file with all features (words, taxonomy matches and category matches) and model learnt weights for each topic across training set. File name format – MAXENT_COEFFICIENT_VALUE.csv Columns – Feature, < TopicName1 >, < TopicName2 > ,…, < TopicNameK >
SR-D26976 · Issue 507217
Filter added to ensure correct context for proposition strategy rules
Resolved in Pega Version 8.2.4
Given two applications (ex App1 and App2) hosted on the same domain where App2 was built on App1, trying to create a strategy rule in App1 and do a test run strategy using the propositional data component which internally uses App2 propositions generated the error: Failed to find a 'RULE-DECISION-DECISIONPARAMETERS' with the name 'GROUP_2'. There were 1 rules with this name in the rulebase, but none matched this request." Investigation showed the strategy was using the PropositionNoCacheUtils and PropositionTools java classes to load the propositions during run time. In these classes, the group classes were browsed from the db irrespective of the application context, causing the strategy run to fail as it was not able to access the decision data rules in other applications which shared the same SR class as the current application. To resolve this, a filter has been added to the PropositionNoCacheUtils and PropositionTools java classes to filter out the groups that are not in the current application context.
INC-169544 · Issue 649541
Enhancement for MaxEnt modeling data
Resolved in Pega Version 8.7
An enhancement has been added to create output for the model coefficients, the term frequency, and the inverse term frequency for use in maximum entropy modeling. For MRM processes, every Maximum Entropy (Maxent) based topic model will contain two additional stats resources. These resources can be used to validate and replicate running of topic model outside of Pega. The resources are: 1) Term Frequency file – A CSV file with all words used for training and their cumulative frequency across training set. File name format – TRAINING_DATA_TERM_FREQUENCY_< RandomNumber >.csv olumns – Word, Count 2) Coefficient file – A CSV file with all features (words, taxonomy matches and category matches) and model learnt weights for each topic across training set. File name format – MAXENT_COEFFICIENT_VALUE.csv Columns – Feature, < TopicName1 >, < TopicName2 > ,…, < TopicNameK >
SR-D12733 · Issue 488666
Code fragment removed to eliminate Fortify false positive
Resolved in Pega Version 8.2.4
A code remnant related to Boolean.getBoolean(..) in Rule-Declare testConsistency was causing a false positive in a Fortify scan. This piece of code is obselete and is not used anywhere, and has been removed.