Improved diagnostics and logging for Decision Data Store nodes
Valid from Pega Version 7.3
On the Decision Data Store tab, you can view additional metrics from the Decision Data Store nodes that help with diagnosing Cassandra database problems. You can also set the logging level to control interactions from and to Decision Data Store nodes.
For more information, see Decision Data Service node status information and Configuring the Decision Data Store service.
Tracing Cassandra queries in a Decision Data Store data set
Valid from Pega Version 7.3
You can now enable the Trace option for every operation in the Decision Data Store data set to collect information about how the Decision Data Store queries are executed in Cassandra. You can view this information in the clipboard and use it to troubleshoot and optimize performance of the Decision Data Store data sets and Decision Data Store nodes. All the queries and related events are collected on the DDSTraces page on the same Pega thread.
For more information, see Tracing Decision Data Store operations.
Record Editor and data import enhancements
Valid from Pega Version 7.3
The Record Editor and Import wizard for data types have been enhanced to make the import process faster and easier to use. You can now perform the following tasks.
- Configure the Record Editor to use full-text search, which makes searching faster.
- Configure the location of the data import error file. For example, you can set the location to a shared location so that users can access the file from any node in a multinode system.
- Pass the keys of the records that were added, updated, or matched directly to custom postprocessing without additional database I/O.
- Search and filter records and export only the results instead of all records.
- Stop an import that is in progress.
Enhanced functionality of the Decision Manager portal
Valid from Pega Version 7.3
The Decision Manager portal now provides more revision management options. The Decision Analytics work area for development of predictive, adaptive, and text analytics models is now part of the Decision Manager portal. PegaUnit testing of rules is more convenient from a new Automated Testing landing page. Revision managers can reassign change requests back to strategy designers or other users of the Decision Manager portal without losing changes that were already made.
For more information, see Enhancements to the Decision Manager portal.
New Java API improves JSON serialization
Valid from Pega Version 7.3
By using a Java API, you can serialize a Page or Property clipboard object to a JSON string for faster JSON serialization. You can also create a map between API responses and an application's internal data model that improves integration performance and maintainability.
For more information, see Using the mapping API for high-performance JSON serialization and Using the mapping API for high-performance JSON deserialization.
Use Kafka data sets in Pega Decision Strategy Manager
Valid from Pega Version 7.3
You can create Kafka data set rules to connect to an external Apache Kafka server cluster and use this data set in decision management for processing real-time streaming data. Integrating Kafka data sets into complex event processing (CEP) as part of Event Strategy rules provides a fault-tolerant and scalable solution for processing real-time data feeds.
For more information, see Kafka data sets in decision management.
Use definition classes to create Decision Data rules that contain text analytics records
Valid from Pega Version 7.3
Use the dedicated definition classes to create Decision Data rules that contain all the types of records that are used in text analytics, such as taxonomies, lexicon, entity extraction rules, and so on. By using these definition classes, you can quickly create, update, and manage the text analytics records in your application.
For more information, see Definition class of text analytics Decision Data rules.
Create resilient data flow runs
Valid from Pega Version 7.3
The resilience of data flow runs has been improved. If Data Flow service nodes fail, active data flow runs continue on the remaining functional nodes. Depending on the type of primary data source and the selected run failure policy, data partitions on the failed nodes can be reprocessed on another functional node or the data flow run is marked as failed for further investigation. You can also add or remove nodes from the Data Flow service while data flow runs are in progress. The runs are automatically rescaled.
For more information, see Data flow run updates.
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.
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.