Forum Discussion
Digital Twins Multiple Timeseries Crossed Up
I created an entity with 2 separate timeseries sources, each coming from a different Lakehouse table.
The source table data is correct, but once I map both time series, the data values get crossed up with both showing data from one of the sources, rather than both. As a result, the State column in the 2nd mapping gets mapped to the Rate data from the 1st mapping.
Any ideas why this is happening? Note the Timeseries ID is the same for both State and Rate, which should not be the case.
Hi druk ,
Yeah, this sounds like a Timeseries ID collision issue. Since both mappings are using the same Timeseries ID (machined), the system is treating them as a single stream, which is why you're seeing the data get crossed up.
To fix this, try assigning distinct Timeseries IDs for each property mapping. Even though both are linked to the same entity, each timeseries (Rate and State) should have its own unique ID so Fabric can track them separately.
You might need to:
- Delete the existing mappings
- Recreate them with different IDs (e.g., machined_rate, machined_state)
Also, make sure the source tables don’t have overlapping timestamps that could confuse the mapping engine when merging the data.
Let me know if that helps or if you're still seeing weird behavior.
If my response resolved your query, kindly mark it as the Accepted Solution to assist others. Additionally, I would be grateful for a 'Kudos' if you found my response helpful.
4 Replies
- burakkaragoz
Super User
Hi druk ,
Yeah, this sounds like a Timeseries ID collision issue. Since both mappings are using the same Timeseries ID (machined), the system is treating them as a single stream, which is why you're seeing the data get crossed up.
To fix this, try assigning distinct Timeseries IDs for each property mapping. Even though both are linked to the same entity, each timeseries (Rate and State) should have its own unique ID so Fabric can track them separately.
You might need to:
- Delete the existing mappings
- Recreate them with different IDs (e.g., machined_rate, machined_state)
Also, make sure the source tables don’t have overlapping timestamps that could confuse the mapping engine when merging the data.
Let me know if that helps or if you're still seeing weird behavior.
If my response resolved your query, kindly mark it as the Accepted Solution to assist others. Additionally, I would be grateful for a 'Kudos' if you found my response helpful.
v-ssriganeshCommunity Support
Hello druk,
Thank you for reaching out to the Microsoft Fabric Forum Community.
The issue you're experiencing, where the "State" and "Rate" timeseries data is getting crossed up and sharing the same Timeseries ID, likely points to a configuration issue in the mapping process. Here are some steps to troubleshoot and resolve this:- Verify that the "Mapped properties" ("Rate, Timestamp" and "State, Timestamp") are correctly linked to their source columns. A mismatch or overlap in the entity properties ("machinerate" and "machinestate") could cause the data crossover.
- Since incremental mapping is enabled for both, it might be overwriting or misapplying data. Try disabling it temporarily, recreate the mappings, and test with a static dataset to isolate the issue.
- As the UI indicates, incremental mappings cannot be modified directly. Delete the existing mappings, recreate them with unique Timeseries IDs, and ensure proper entity linking.
- Confirm that the Lakehouse tables contain distinct "Rate" and "State" data with aligned timestamps to rule out data integrity issues.
Please refer the following Offical Documentation: Mapping data to entities - Microsoft Fabric | Microsoft Learn
If this information is helpful, please “Accept as solution” and give a "kudos" to assist other community members in resolving similar issues more efficiently.
Thank you.- v-ssriganesh
Hello druk,
Just checking in have you been able to resolve this issue? If so, it would be greatly appreciated if you could mark the most helpful reply accordingly. This helps other community members quickly find relevant solutions.
Please don’t forget to “Accept as Solution” and Give “Kudos” if the response was helpful.
Thank you. - v-ssriganesh
Hello druk,
Could you please confirm if your query has been resolved by the provided solution? If so, please mark it as the solution. This will help other community members solve similar problems faster.Thank you.