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Provide an additional attribute level to filter 3D resource layers, e.g. “Unit” or “Project”. Example:CAD models → Project → Model NamePoint clouds → Unit → Point cloud Name
We recently encountered an issue where we had to delay a task in a workflow to wait for transformation metrics to become accurate. To solve this we put a sleep in a Cognite Function. We can also use external function calls to create a delay, but I was thinking that this might be a feature that would be nice to have built-in to Data Workflows.Considering that there are times when you may want to delay a task for n minutes:I was wondering if there are any plans to add a built-in delay task-type, or a delay field for the existing task-types, into Data Workflows?e.g.# maybe put it in the dependsOn field #############################- externalId: someTask type: ... ... dependsOn: - externalId: transformationTaskId1 delayMinutes: 10# or as a dedicated field for each task ###########################- externalId: someTask type: ... delayMinutes: 10 dependsOn: ...# or as a unique task type ########################################- externalId: '10MinutesAfterTransforms' type: delay minutes: 10 dependsOn: - transformationTaskId1 - transformationTaskId2- externalId: someTask type: ... dependsOn: - externalId: '10MinutesAfterTransforms'And if not:Is this something the Cognite team would consider adding?Currently I think you can build a dedicated delay function by having a Cognite Function forward a delay instruction to an external endpoint using the isAsyncComplete flag, and have some external process tell the workflow to complete the task when the delay is over.But I imagine this is the sort of thing that many teams who use Data Workflows would eventually need to build themselves.You can also sleep inside the Cognite Function but, it’s wasteful since you’ll be paying for the time slept, it will increase the risk of the function timing out, and the function needs to “know” more about timing quirks of the other processes in the workflow.
Hi,Currently, transformations must target a view to populate a container. But if we update the view (e.g. remove an attribute that we no longer want to expose), the transformation will no longer populate that field — even though the container still supports it.As a result, existing users relying on older views that still expose this attribute will see empty data, creating unintentional breaking changes.Suggestion: Enable transformations to write directly to containersThis would:Ensure stable ingestion regardless of view changes, Prevent breaking downstream users, Simplify the data pipeline.
In order to make it easier to use the data registered in CDF, we propose the development of a data linkage function with Excel.From the data registered in the CDF (mainly time series data), for example, when creating a plant operation report,Right now, I have to download the time series data as a CSV, then copy and paste it into the report, which is very time-consuming.If it is possible to acquire data directly into Excel cells by the Excel linkage function, the utilization of data will be promoted.There is still an Odata function, but it would be best if it was in a more user-friendly form like an Excel function.
Create a “next Day/week/month” button in Maintain to easily move from one time period to the next without having to click 6 times to select a new timeframe.
Enable assignment to More than one Grid Zone, some activities such as drain piping can extend through multiple grid zones and therefore need to deconflict large areas.
For a good User Experience, in general, a Cognite Specific Icon should serve the same purpose in all Cognite programs. Navigation and functionality should be similar across modules. Cognite should adopt a consistent philosophy in how you manage this and converge all of your applications for consistency:1) When you search for MBD1070, CDF finds MBD-1070, but Maintain does not find any asset.2) In CDF, when you pan to another asset in the 3D model and single click , you can select the next asset over (MBD-1270) and open the meta data. In Maintain, if you select another asset you highlight the shape only. You do not get any data or even identification of the asset.3) When you select an integrated asset (PW-424-A) in CDF you get a section of pipe and 6 valves. In Maintain, you are able to select and highlight a single valve or shape.4) Maintain has no access to photogrammetry or laser scans as layers in the 3Dmodel.5) You are able to take measurements in both Maintain and CDF modules, but the measuring tools in CDF are much more robust (polylines, polygons, areas, volumes). Maintain has straight line distance only. In CDF you can change the units from metric to English, in Maintain distance is in mm only.6) CDF allows slicing in all three planes. Maintain allows slicing in the vertical plane only.7) In canvas, if you add a 3D view, you cannot use any of the 3Dmodelling tools, such as measurements.8) The icon for adding layers in CDF search changes the marker legend in Maintain9) An icon with a question mark in CDF shows Navigation guidance, while an exclamation point shows the same information in Maintain.
The engineering team will add support to allow a user to load single 3d model in 3D page when there is no location or scenes are configured.
When working with Charts we often start testing it in the “dev” environment where we collect relevant timeseries as a set. In order to then proceed we normally move on to run tests in “qa” and finally our “production” environment. Unfortunately each time we need to recreate the Charts setup from scratch since we could not find a way to export/import or simply copy over a Charts setup to a new environment. Having such a feature would be a great help
Request CDF to be able to auto pre-sort the documents into different groups
Diego, Sofie,Can we please put a direct link to 3D search in the left-hand navigation pane?
Define graph axis for time series data in Industrial Canvas. In this example below, date range and UOM are needed to understand the graph effectively. Submitted at the request of the Cognite project team
By default, filters in Cognite seem to be set to “AND,” meaning that to get a successful return, if you have slected two criteria, the target bust have both properties. There are times when the user wants to cast a wider net, and use “OR,” meaning that the filter will return results if either criteria is met in the filter. For example, if the user wants results from two different platforms, but not all platforms. Or, in some cases, the filter will not allow the user to select the filter element because of this property. Suggest standardizing how filters work and allow user to select either “AND’ and “OR”
When a CDF transformation fails the error message could be more details pertaining to which record instance (external id) caused it to fail. Currently the CDF transformation provides the error why it failed but no information on which record caused the failure.If the transformations are triggered using python SDK, the returned object contains detailed info on which instances caused the transformation to fail. Some similar details would help with expediting the debugging and resolution process.
Is it possible to add support to combine name and SourceID as the external ID.From a Data management point of view the best solution might be to use PointID. But from a consumer point of view it might be more convenient to use name. However with name we have the possibility to overwrite if there is created a new timeseries with similar name. But how about a combination? external-id-prefix string Enter the external ID prefix to identify the time series in CDF. Leave empty for no prefix. The external ID in CDF will be this prefix followed by either the PI Point name or PI Point ID. external-id-source either Name or SourceId Enter the source of the external ID. Name means that the PI Point name is used, while SourceID means that the PI Point ID is used. Default value is Name.
Currently, there is no checkall button in Data Model → Data Management. If I have a long list of data that I would like to export/download to CSV file, I have to tick the data row by row.
Instead of writing lot of yaml configuration files in the CDF tool kit better to generate those using trained Chatgpt models to generate. Nowadays Kubernetes deployment yamls are getting generated instead of configuring it manually.We can make use of this github repo to get some idea about generating yaml files. https://github.com/Luxadevi/yaml-generator-Litellm
I believe we need bring infer_schema_length to db extractor parameter to improve it flexibility.If I understand correctly polars library was used in db extractor.According docs:infer_schema_length: int | None = 100,this means it defines data types by first 100 rows by default. This is not fit for our client data.Currently I extract data from csv and experienced with 2 issues. I think they are related to each other. As I understood: Extractor defined column data type based first n (probably 100) rows: could not parse `"1,616,178"` as dtype `f64` at column '*column_name*' (column number 10) This value on the line 3161 could not parse `"2.15"` as dtype `i64` at column '*column_name*' (column number 15) This value on the line 118 - all previous values equal “0”after error in terminal I see suggestion:You might want to try:- increasing `infer_schema_length` (e.g. `infer_schema_length=10000`),- specifying correct dtype with the `schema_overrides` argument- setting `ignore_errors` to `True`,- adding `"1,616,178"` to the `null_values` list.
I had an observation where after cancelling the CDF Data Workflow, the transformation it triggered were not stopped/terminated immediately.SCENARIO:- A Data Workflow is triggered.- Transformation step started.- Transformation failed in first run/attempt.- While second run starts (due to retry policy) click on Cancel Run in workflow interface.- Workflow successfully cancelled , but the triggered transformation keeps on running till it failed again.I was assuming the transformation would stop with the Data Workflow execution getting cancelled, but later realized the transformations kept running and eventually failed.
when contexualized engineering documents, some annotations added wrongly and it's innevitable.we want data tidying-up functions such as dragging and selecting multiple annotaions and delete at once, or deleting annotations by right-clicking. And more,we think deleting annotations available in edit screen would be better.Now, we have to select one by one, and click the right-upper botton(in a distance) 2times to delete single annotaion.
On the Checklist Lists, users currently after check a Checklist, needs to scroll up, click on the three dots and change the checklist to done. It should have a simple way to change with less click and more easier to the users.
I would like to set time range in grafana custom query using grafana variables. I see we can use:granularity='GRANULARITY', alignment=ALIGNMENT in query and wonder if there is any parameter for range?
Building upon the recent enhancements of waypoints and ghosting, the ability to walk a user to a location from their current location or a selected start point is a use case for our contractors during daily maintenance or Turnaround activities. Often contractors have never been onsite and navigation to the work area or a specific asset would be helpful. Think google maps walking feature or a line that connects scan points in the 3d model to guide the user to the location.
Here are some of the things I cannot do with the call logsSee all logs (only four pages) Filter based on status Filter based on schedule Filter based on time ranges Sort calls based on run times Automatically locate the “first failed” call (which is often relevant in debugging) See logs in monospaced font to preserve formatting (see other feature request) Get call logs into Power BI (I need to deploy a separate Cognite Function that fetches call logs and writes to a Sequence, which can then be loaded into Power BI for simple monitoring)At least we should be able to see all logs from our calls, with additional functionality to filter in relevant dimensions.
Hi Team!Right now graphql support for fetching FDM Data doesn't offer any filters for type "TimeSeries". Since Timeseries type usually has a lot of datapoints associated with it in any given model, fetching data through graphql api from it without any filter is extremely time consuming , especaially when you dont need all datapoints/timeseries from it. For example, right now when we want to fetch information only for non string timeseries, there is no way other than fetching all Timeseries associated and remove the ones that has "isString" property as false which slows down some parts of our appplication.So if we can get graphql filter support for timeseries type, we will be able to optimise things in our side.Thanks & Regards,Sangavi M
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