Release Notes > Version 8.5 Release Notes > Platform Analytics 8.5.0 Release Notes
Platform Analytics 8.5.0 Release Notes
The following sections describe the enhancements, bug fixes, and known issues in Platform Analytics 8.5.0.
Enhancement Description
Reference #
ThingWorx Analytics: security improvements
In this release, security was improved by closing several vulnerabilities.
Property Transform service to retrieve job status
A service called IsPropertyTransformJobRunning has been added to the Property Transform microservice. As the name suggests, the new service can determine whether the Flink job for a given property transform is currently running. For input parameters, the service requires a Thing and a property name. It returns a Boolean value indicating whether or not the job is running.
Bug Fixes
Bug Fix Description
Reference #
Platform Analytics Installer: Encryption of passwords and keys fails when Java 7 is present
During installation, passwords and keys are encrypted automatically. One of the installation prerequisites is JDK 8u141 (or for older versions of Platform Analytics, JDK 8.x). However, if Java 7 is also installed on the same server, errors occur during Platform Analytics installation and the Property Transform and Descriptive Analytics Things are not successfully created in ThingWorx. This issue has been resolved so that Platform Analytics can be installed successfully even when Java 7 is present on the server.
Platform Analytics Installer: RabbitMQ problems during upgrade
During Platform Analytics upgrades, the installer occasionally has one of the following problems with the RabbitMQ application that is necessary for Property Transform functionality:
RabbitMQ fails to stop running
RabbitMQ does not uninstall successfully
The RabbitMQ user is not created
These issues have been resolved as far as possible. If RabbitMQ issues still occur, see the troubleshooting procedures at the appropriate links below:
Known Issues
Known Issue Description
Reference #
ThingWorx Analytics Server: Two-at-a-time Signals request does not return MI for all field combinations
When running a request for Signals, and specifying maxAtATime = 2, Mutual Information (MI), in relation to the goal, is not returned for all field combinations as expected. Instead, individual (one-at-a-time) MI scores are returned for all fields and then are filtered down to the top 25% most relevant fields. Two-at-a-time signals are calculated only for those fields. There is currently no way to modify this filtering behavior.
Analytics Manager: An existing simulation event fails if it is triggered after server restart
Analysis agents must be restarted after a ThingWorx server restart. Without restart of the agent, any new simulation jobs will fail to execute.
Analytics Manager: Time window event does not work for non-time series models
When a non-time series model is uploaded using the Analytics Server Connector, and all of the properties, including the key field are mapped, a time window event does not work.
Analytics Builder: Filtering on list pages does not work as expected
When filtering is applied to a list page with multiple pages (such as the Models list page), the filtered results are not aggregated for display on a single page. Instead, the filtered results remain on their original pages and multiple pages must be clicked through to find all the filtered results.
To improve handling of list page displays, a configurable parameter has been added to set the number of table items that can be displayed per page. A more permanent resolution for the filtering with pagination issue will be provided in a future release.
ThingWorx Analytics Server: Some datasets with a large number of columns fail to upload
There are currently some limitations on the size and number of columns a dataset can contain. These limitations depend on the mix of data types your data includes. For specific information, see the Data section of Prepare Data and Metadata.
When trying to upload a dataset with a large number of columns, if the upload fails and an error message is generated, try the following workarounds:
Where possible, use optimal data types, for example, convert INTEGER data to STRING and use DOUBLE for numeric data.
Reduce the number of columns.
ThingWorx Analytics Server: When dataset or metadata field names begin with a number, server queries fail
When a field that begins with a number is included in a dataset or in metadata, most Analytics Server jobs can run successfully, such as training a model, running or scoring. However, when a server query is executed, such as a BinnedDistribution, the query fails. As a work around, avoid using field names that begin with a number.
This issue will be resolved in a future release so that field names can begin with numbers.
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