Community Discussions

Hello, We have a very big CDF workflow with many parrallel steps. When a step fails, all the steps fails with “404: Session was not found.” (because the failing step deleted the session) all steps are market as failed. It makes debugging and finding the real failing step very tedious ! Any improvement planned for this? Any workaround? Thanks 

Are there any extractors or connectors to seamlessly integrate Cognite CDF and Aspentech Mtell?If not, have you discussed approaches for that integration, and whether one of them should involve using Aspentech DataSource Interfaces to connect via Aspentech ODBC Datasource, Kafka Datasource, or MQTT Datasource?Please also share any other approaches you may have discussed for seamlessly integrating CDF and Aspentech Mtell.

Lineage doesn’t work. You click on it and it shows for 1 second, before you get this screen. Multiple people gets the same error. 

In Charts, when choosing a core data model as your source, Events are disabled preventing the choosing of core model “CogniteActivity” as “events” to overlay timeseries data from CogniteTimeSeries.Is this functionality on the roadmap and if so, when can we expect?  

Hi community,I’m learning to use the /models/instances/query endpoint (with Open Industrial Data, public project) and experiencing some confusion about how cursors and pagination work.{    "with": {        "cities": {            "nodes": {                "filter": {                    "and": [                        {                            "exists": {                                "property": [                                    "Geography",                                    "City",                                    "name"                                ]                            }                        }                    ]                }            }        },        "continents": {            "nodes": {                "filter": {                    "and": [                        {                            "exists": {                                "property": [                                    "Geography",                                    "Continent",           

We’ve setup an MQTT Hosted Extractor that is recieving a SparkPlug B payload which some times contains a couple of null values, this values cannot be removed from the SparkPlug B payload. We believe that whenever the message contains null values the transformation for the datapoints fails.No more information is provided on the Transform Error, only the “Failed to transform data: Missing required field value”, could the null values just be ignored so the other values be inserted in the time series? We’re getting several empty time series that were created via the hosted extractor.

Is there an alert or notification that can be configured when the MQTT hosted extractor is down? Been having issues with  Request to CDF failed with error Error in middleware: Failed to authenticate request  This error is resolved by creating a new sink, however we don’t get a notification of any kind when the extractor is down. 

I’m working with the PI AF Extractor and facing an issue with Table Lookup attributes.The Table Lookup attribute itself is being extracted correctly into the attributes table, but the value column always comes as “no data”, even though the attribute resolves normally inside PI System Explorer.I would like to know whether there is any supported way to extract the evaluated Table Lookup value using the PI AF Extractor, or if the extractor does not currently resolve Table Lookup references during extraction.Has anyone faced this issue or found a recommended approach to retrieve these values through the extractor?

 We are thrilled to announce the next evolution of your user experience. We’ve unified our ecosystem to help you master your industrial data without the friction.What’s new? One Identity: We’ve merged Cognite Academy and the Community. One login for everything. Unified Search: Find How-to guides, discussions, and courses in a single search. Guided Careers: New role-based learning paths, starting with the Data Engineer path! 👇 Read the full announcement here:  

We are thrilled to announce the next evolution of your user experience. We’ve unified our ecosystem to help you master your industrial data without the friction.What’s new? One Identity: We’ve merged Cognite Academy and the Community. One login for everything. Unified Search: Find How-to guides, discussions, and courses in a single search. Guided Careers: New role-based learning paths, starting with the Data Engineer path! 👇 Read the full announcement here:  

What are the licensing terms and conditions for using Cognite's Open Industrial Data? Could you please provide a link to these terms and conditions?Thank you.

Hi Team,I'm using the Cognite Toolkit to test the CDF download raw functionality. I’ve observed that the download process fails when the staging database name contains a special character such as :.For example, if the database name is state:odbc, the cdf download raw command fails because it attempts to create a temporary folder with the same name as the staging database. Since : is not a valid character for directory names, the folder creation fails.Additionally, when I try to download the raw data from another database (without special characters), three files are created in the temporary directory:.Table.yamlManifest.yamlRawRows.ndjson.gzCould you please confirm if the RawRows.ndjson.gz file is expected, or should the output be in .csv format?

I am going through the course Match entity python sdk ,  there one notebook in section “How to succeeded with this task ” .But the link is not accessible . Please can some one guide in it. https://cc.sj-cdn.net/instructor/hhi6o3bc6ve-cognite-academy/assets/1688105749/Entity_matching_notebook_copy.ipynb?response-content-disposition=attachment&Expires=1763969235&Signature=dX1a9jxYTvcqFQ7jWIhNing8AxVk9r~60Tm4ZFWuvUK232AuM7mIg4StnYkk~MwaarbraKyfxE0O4BFm8VQbKFsEzgjeIDufqRvP5XEDH4X9aTC0XY5YR1l8iJeNmU2ebqWArryM8296eFNOVtPsNdIPOGWIaDz2xdqQ2rkncm4Zo-awiI7u~VFf~83tTN10ZiLuoTBqa2hurinAD5W3Igo4HlRQG109N9PVBkL7fO2ZeyjHhbRqBtxXrU8um0u6l4fcHJRb1CL9sWHEjouuK55CTf4iIK~057XQM9yx6ylK8FWD9EuT3ayDmgdwXx~FPhKPNpdBaxWIcKj3VrEERw__&Key-Pair-Id=APKAI3B7HFD2VYJQK4MQ

 Issue SummaryCreating `CogniteFile` instances in Data Modeling Service (DMS) automatically creates unwanted "ghost files" - duplicate file resources that are incomplete and have no external_id, no dataset_id, and no content. This causes the Diagram Parser UI to display incorrect file IDs and show "Files not uploaded" errors.  Environment- Project: tridcognite-sanbox- Cluster: aw-was-gp-001.cognitedata.com- Dataset ID: 1242342447467142- Space: diagram_parser_space_1- Data Model: diagram_parser_data_model_1 (version 1)- Python SDK Version: 7.78.0---Methods Used:Method 1: SQL TransformationINSERT INTO cdf_cdm.CogniteFile(v1)SELECT   CAST(externalId AS STRING) as externalId,  CAST(name AS STRING) as name,  CAST('application/pdf' AS STRING) as mimeType,  CAST(TRUE AS BOOLEAN) as isUploadedFROM `Diag_Parser_Cement`.`parser_files_staging`WHERE externalId = 'cement-parser-file-crusher-pid' Transformation Configuration:- Destination: Instances- Space: diagram_parser_space_1- View: cdf_cdm.Cogn

Hello,When testing the new Diagram Parser tool on Vector PDFs, I found that it successfully finds some Assets ingested in the DMS and Symbols from a selected library. However, the Assets only show up as annotations even when verifying them. How can I get the suggested Assets to link to the Diagram in the DMS (i.e. open the diagram and see Assets directly linked to the diagram)? Thanks,Gabriel

During the calculation of adding two time series, if one of them has no value, will the calculated timesseries give me some interpolated value?In the example below, the ‘Error Intern’ series has a value of 2252, but in ‘Total Down Time’ I’m getting 2756.64, which is incorrect—it should also be 2252.Why is it still giving me a linear interpolation value even though I selected the interpolation type as ‘step’?  

Why are we making this change?The CDF CLI was originally designed to streamline application development on top of CDF, specifically focusing on Data Modeling workflows and the generation of type-safe SDKs.However, to ensure we are delivering the highest value to our developer ecosystem, we are refining our product strategy and priorities. The CDF CLI (beta) has not been under active development for some time, and maintaining it to our quality standards no longer aligns with our current roadmap. By discontinuing this tool, we can refocus our resources on the core tools and SDKs that best support your integration with Cognite Data Fusion.If your current CI/CD pipelines or local development environments rely on installing this package, you must take action before February 18th, 2026 to avoid build failures.Timeline of Events February 18th, 2026: The @cognite/cdf-cli package will be unpublished from NPM. You will no longer be able to install it via npm install or yarn add. What do you need

I’m using the CogniteSDK. I have seen the following behavior several times: assets = client.assets.list()the variable assets can contain deleted assets if they have been recetly deleted. If I find the external_ids of these assets, the client.assets.retrieve_multiple(external_ids=deleted_xids) correcly do not return the assets. The assets cannot be found in fusion either. I suspect that client.assets.list() is using cached values. This also applies with arguments, f.ex LabelFilter. I have seen the issue many times, but now it really got painfull, so therefore I’m writing here. It returns assets that were deleted several days ago.  What to do? 

Hello, Although “unitless” is an alias of the dimensionless:unitless unit, try_get_unit(“unitless”) returns null.ref: https://github.com/cognitedata/units-catalog/blob/main/versions/v1/units.json#L1699 Could you please have a look? Thanks!

There are some signals that in the names or the description have the words: alarm, warning, or fault. E.G. There is this alarm signal, (in red ) that I’m comparing with one of the vibration signals.  And the alarm seems to be on when the vibrations are close to 0 and the Compressor is off. I’m plotting the label as a combination of the name and the description, but the externalId of the alarm is: pi:160268In most cases that alarm is on when the compressor is off, except in this case, Where I do not see any problem with the vibration signal: There are these other two alarms, from the plots: one is on when the compressor is off and the other one when it is starting up. But I do not see any strange behavior in the signal when they occur. Besides the alarms, I’ve also looked into some of the fault signals but those seem to be on for very long times: Is there another way to use the alarm and fault signals to label anomalies or failures? I don’t know if using the vibration signals is the bes

I’m searching for a specific document using Search. The doument ID is hidden in a metadata tag.If I search for this document ID in the search bar, the file is not discovered (obviously it doesn’t search in metadata)Plan B is to use the filter (which is inconvenient since it forces me to know that particular metadata key)The metadata key is document:abp_document_number, but it doesn’t show up when I search in the filters  If I use the Data explorer under Data management, it discovers the metadata key, allowing me to filter on it  But there is an even better way of doing this in Data explorer. There I can edit the search settings and instruct it to look in the metadata. Then it discovers it immediately. This allows me to find the document without having to know to filter on this very cryptic key. For classic data model, where a lot of info is dumped in metadata, with poor governance on the keys, the ability to search in metadata is VERY useful   

Can we visualize Visio files with.vsd extension in Industrial canvas?

What capabilities are required to run a transformation using client credentials? I have a client_id and client_secret that when I add to the transformation and hit ‘Test credentials’ it says ‘Credentials verified’. However when I run with client credentials I get an error: Transformation job could not be created. Error code: 403 API error: Invalid source/destination credentials: Token did not provide access to project kuraray-america. Request ID: eb5136ee-594d-971f-b27a-7be0d1a60b15these credentials are a part of a group that that has read and write capabilities to:transformations sessions datamodelinstances (that is what this particular trasformation is creating)Additionally I am part of the same groups as this client_id, and I am able to run the transformation using ‘run as current user’ successfully

Hi everyone,I have a question: Can we use data from Data Models in Canvas?Is there any way to visualize that data available in Data models into Canvas?In our case, we are using Cognite Charts with time series data coming directly from machines (e.g., good parts, bad parts). However, the time series does not include product or batch information, which we do have in our Data Model.Is there any possibility to link both sets of information together for analysis?My initial thought is: if I can bring the required data from Data Models into Canvas and then create charts there, it would make the analysis much easier.But I’m not sure if this is possible—or if there’s another approach you would recommend.Any suggestions or best practices would be greatly appreciated!

Hi, I have defined a Data Model with a Source View having a DirectRelation to a Target View as a simplified version below, which Pygen created an SDK successfully.  But when I added a ReverseDirectRelationApply to the Target View, Pygen returned the captioned error.  Please help.source_container = ContainerApply(       space =”myspace”,       external_id=”sourceContainer”,       properties={            “sourceName”: ContainerProperty(type=Text, name=”sourceName”),            “target”: ContainerProperty(type=DirectRelation(is_list=False, container=ContainerId(space=”myspace”, external_id=”targetcontainer”) } target_container = ContainerApply(       space =”myspace”,       external_id=”targetContainer”,       properties={            “targetName”: ContainerProperty(type=Text, name=”targetName”)} source_view = ViewApply(     space = “myspace”,     external_id = “souceView”,     version = “1.0”,     properties = {           “sourceName”: MappedPropertyApply(container=ContainerId(“myspace”,