Release 10.10.0
Cumulocity IoT DataHub Release 10.10 includes the following improvements, limitations, and known issues:
Enhanced support for additional result columns
When setting up an offloading pipeline for a Cumulocity IoT collection, DataHub automatically selects a set of default attributes to offload. Additional top-level attributes in the collection can be included in the offloading by defining so-called additional result columns. DataHub now facilitates the definition of these additional result columns by auto-detecting top-level attributes and guiding the user in the configuration process.
New REST API for querying large batches of data
DataHub provides a REST API to proxy query requests to Dremio. In addition to that API, a new REST API is introduced which is tailor-made for querying large data batches with high performance. The API relies on Arrow Flight for an efficient data transfer with Dremio.
New version of internal query engine
DataHub now uses version 13.3 of Dremio as query engine. The new version comes along with various features and improvements, including up to 25% query performance gain depending on workload and cache performance.
Integration of Software AG icons
The icons used in DataHub are now aligned with the Software AG look and feel, so that it speaks the same visual language.
Limitations
Description |
|---|
| Mixed usage of uppercase and lowercase characters for an attribute name in the documents is not supported as it may corrupt the schema of the offloaded data. |
| If the collection to be offloaded has JSON attributes consisting of more than 32,000 characters, its data cannot be offloaded. One specific case where this limitation applies is Cumulocity IoT’s application builder, which stores its assets in the inventory collection when being used. |
| If the collection to be offloaded has more than 800 JSON attributes, its data cannot be offloaded. This limitation also includes nested JSON content, which will be expanded into columns during offloading. Therefore, measurements documents with more than 800 series/series value fragments are not supported. |
| If an attribute of a collection has varying types associated, the result table will contain a mixed type which may render query writing difficult or lead to problems with subsequent consumer applications. |
| DataHub does not work with Kubernetes version prior to 1.9. |
| Dremio has announced in its Dremio 4.0 release notes to deprecate some functionality on mixed types. In Dremio 13.2, GROUP BY or DISTINCT over mixed type expressions are no longer supported. It is necessary to cast these expressions to a simple type before using them in a GROUP BY or DISTINCT clause. Also mixed type expressions cannot be used in the SELECT clause, when retrieving data over ODBC or JDBC. |
Known issues
Edition |
Description |
|---|---|
| Cloud | Data lake configuration validation is broken in terms of wrong bucket names (AWS S3) and wrong account names (Azure Storage). When saving the settings with an invalid bucket/account name, DataHub fails to quickly detect the problem and will instead run a time-consuming check, which shows up as an ongoing save request in the UI. Eventually the request will fail in the UI with a timeout and the save request in the backend will fail as well. In such a case, please carefully check the bucket/account name and try saving again. |
| Cloud | For older deployments, if the track changes feature of Cumulocity IoT was not enabled, the readings in the Operational Store of Cumulocity IoT do not have a creation timestamp. If more than 4096 of those readings exist, the offloading will fail, even if track changes was enabled afterwards. In that case a Dremio administrator must run a SELECT * query without limit or filter over the collection in order to gather the correct schema, which is required for a successful offloading. |
| Edge | There are no retention policies in place that prevent the data lake contents from exceeding the hard disk limits. |
| Edge | TLS is not supported for ODBC and JDBC. |