Community Discussions

I am currently facing an issue where the dataset data type is set as string = true, whereas it should be false (numeric). As a result, the chart is not displaying any data due to the field being treated as a string.However, when I download the dataset as a CSV file, the data is present. Could you advise if there is a quick fix on your side to convert the data type from string to numeric?  

Is it possible to remove a Flow App from a Cognite cluster after it has already been deployed?

How to get Early adopted for document parsing, i got 3 environments in the request - https: //cognite. zendesk. com/hc/requests/18058. please can someone make it available for us in those 3 environments ?xom-upstream-devxom-upstream-testxom-upstream

May our 3 projects have access to Document Parser as an Ealier adopter ?i have opened this request -  https: //cognite. zendesk. com/hc/requests/18058

Hi,We're using the Cognite DB extractor (version 3.9.2) with a MongoDB database (Azure Cosmos DB via the MongoDB API) and are trying to set up incremental loading.The documentation for mongodb (https://docs.cognite.com/cdf/integration/guides/extraction/configuration/db#databases.mongodb) doesn't mention the use of start_at and incremental_field but after testing them and looking at the debug logs, we can see the extractor sends the {start_at} placeholder literally without substituting the state value. My questions are:    1. Is start_at substitution supported at all for MongoDB JSON queries, or is it SQL-only?    2. If incremental loading is not supported for MongoDB, is there a recommended workaround?Thanks.

what are the typical use cases that Cognite AI can solve Integrated Supply Chain challenges?

I uploaded a PDF maintenance manual into Cognite CDF using:client.files.upload(...)The document is successfully indexed by the Documents Engine.I can confirm that:- client.documents.retrieve_content() works- client.documents.search() returns the document- last_indexed_time is populated- truncated_content contains extracted textExample document metadata:{  "id": 3652062792350259,  "external_id": "HACTL_CSS_Manual",  "name": "HACTL_CSS_Manual",  "title": "Hactl.md",  "mime_type": "application/pdf",  "last_indexed_time": "2026-05-06 14:57:28.531+00:00"}However, Atlas AI still responds with:“I could not find any uploaded maintenance manuals related to wheel carriage troubleshooting in the system.”Questions:1. Does Atlas AI automatically use Documents Search semantic indexing from files uploaded with client.files.upload(), or does it require CogniteFile instances + upload_content()?2. Is Atlas AI document retrieval based on:   - Documents semantic search   - passages/search   - or instanceI

How does asset hierarchy work in CDF?

For metadata on assets (and other object types) in the app UI, the text is capped even though there is a lot of white space. Inconvenient when viewing it on a big screen and expecting to be able to see the whole string.    

Hi, I am struggling trying to find my the description field is empty "-" for my assets (in Data Management > Data explorer > Assets. Looking for the problem I verified the followingsuccessfully imported data into RAW (seen under Data Management > Integrate > Staging)     successfully ran transformations on the RAW table and populated CogniteAssets (seen under Data Management > Data models > Data Management > CogniteAsset)    Any advice would be helpful? 

I follow the Docments for binding files in CDF(client.files.upload_content)After uploading, AtlasAI is indeed able to use the content.However, this file seems to be a chunked TXT document generated from the customer document. I believe this TXT file should follow a certain structure, but I could not find any documentation describing the expected text content structure in the help docs.Is this an industry-standard format, or is the file_content structure arbitrary?It seems that the completeness and quality of the chunk file directly determine the upper limit of AtlasAI’s intelligence and response quality. 

When we’ve tried to update to python sdk v8 we get a 400 validation issue when we try to create a container.We’re currently using v7.92.0, where we have no problems. We’ve tested versions v8.0.7 and v8.2.0.client.config.api_subversion is ‘20230101’ for both 7.92.0 and 8.2.0.Here is an example of a request that fails with: Unexpected field - items[0].properties..constraintState.constraintState seems to be a new property for v8 of the api.ContainerApply( space="Space", external_id="Comp", name="Comp", used_for="node", properties={ "manufacturer_name": ContainerProperty( type=Text(), nullable=True, ) })I notice also that the CDF Jupyter notebook in browser is still on v7.92.0. Is there potentially any other issues preventing an upgrade to v8? Best RegardsDaniel Rasmussen

With Tableau 2026.x introduced the native REST API connector, I wanted to check if anyone has explored using it to connect Cognite Data Fusion (CDF) APIs.Has anyone successfully connected CDF data via the Tableau REST API connector, or evaluated this approach?Any insights, limitations, or best practices would be greatly appreciated. Thanks in advance!

Hello everyone ! Since this morning (3AM Paris time ) we encounter serious problem with our MQTT hosted extractor. Setup- CDF region: West Europe 1- 1 Source (Azure Event Grid MQTT broker, port 8883, TLS cert auth) controlled externally- 1 Destination (single sink, single CDF session)- 2 Jobs (topic filters), both using the same source and same destination:  - xxxx/OUT/xxxxxxx/AA/#  - xxxx/OUT/xxxxxxx/BB/# ProblemSince this morning (~03:00 UTC+1), both topic filters are stuck in connection_error with the following error looping in the event log:Could not establish connection: Mqtt state: Server sent disconnect with reason 'None' and code 'SessionTakenOver'Both jobs were running fine until today. No configuration changes were made on our side. What we tried1. Paused one job to isolate — the other still fails alone2. Paused both, waited 10 minutes, resumed — connects briefly then gets kicked again3. Deleted 10 legacy/unused sinks and 1 old paused job (cleanup) — no change4. Checked Azure

Hello,I am running a function ‘dq_validate_model_integrity’ and ‘dq_validate_broken_references’ which give a 403 unauthorized error for a timeseries intermittently. There has been no change in access or data yet its failing sometimes with a 403 error.Could you please let us know why this issue is coming up frequently?PS: I have attached the screenshots of the passed and failed statuses of both functions with the timestamp as well as the logs of both failed functions. Do let me know if there’s any more information required from my end. Thanks alot :)

Hello,  Is it planned to support RAW querying via CDF Grafana Datasource ?  Thanks ! 

When hovering over the dropdown, the legends are lingering making it hard to find and click on correct time series. Happens when creating calculations in Charts. 

Hello, In our project, we need to use TIMESTAMP_LTZ data type for our timestamps. This data type is only available in Spark starting from 3.4 version. Is it possible to upgrade your version (which is 3.3 I believe) to 3.4 at least please? Thank you

Team, I am trying to schedule math functions, specifically addition of 4 tags and averaging of 4 tags.These need to run specifically at 10:05am as these are totals that are reported once a day, at approximately 10am EST.How can this be done and make these values available for use in Grafana? Thanks for helping!

I am new to extending CogniteCore data model to further extend. How to Import CogniteCore datamodel to further extend in a new datamodel space. 

Hello,  Since function deployment using cdf tk is asynchronous, function can fail without any error feedback and stay in failing state until next deployment..Any recommendation to avoid this?Thanks  

KepServerEx 6.10 OPC UA Configuration Manager : KepServerEx 6.10 OPC UA Node ID :config.yml :source:    endpoint-url: opc.tcp://127.0.0.1:49320      #This is your OPC UA server url    auto-accept: true    queue-length: 10    username:     password:     browse-chunk: 1000    attributes-chunk: 1000    x509-certificate:            browse-throttling:        max-node-parallelism: 10   extraction:    id-prefix:     # Delay in ms between each push of data points to targets    # Alternatively, use N[timeunit] where timeunit is w, d, h, m, s or ms.    data-push-delay: 5000        # Source node in the OPC-UA server. Leave empty to use the top level Objects node.    # If root-nodes is set, this is added to the list of root nodes.    root-node:        # Full name of the namespace of the root node.        namespace-uri: "Simulation"        # Id of the root node, on the form "i=123" or "s=stringid" etc.        node-id: "s=Simulation"            # List of proto-node-ids similar to root-node.    # The

Hello, Currently using cdf-tk version 0.5.111. The bySpace param on btree indexes is not yet supported in this version.We are trying to migrate to version 0.7.220. Although, this version sets correctly the bySpace param on indexes it does not seem to resolve correctly the view dependencies in our data model.Error trace:  Deploying 375 views to CDF...WARNING [MEDIUM]: Found a strongly interdependent set of 75 views: sp_dm_dap_knowledge_graph:BHAComponent(version=4.3), sp_dm_dap_knowledge_graph:BHARun(version=4.3), (...)sp_dm_dap_knowledge_graph:WellPath(version=4.3), sp_dm_dap_knowledge_graph:Wellbore(version=4.3) and sp_dm_dap_knowledge_graph:WellboreSection(version=4.3). This might indicate a data model design issue, and the deployment might fail due to API batch size limits.Traceback (most recent call last):  File "pypoetry/virtualenvs/drillx-dwdap-cdf-toolkit-fxS2v_xU-py3.13/bin/cdf-tk", line 8, in <module>    sys.exit(app())             ~~~^^  File "pypoetry/virtualenvs/drill

cdf version is 0.7.236.i cannot find the same quickstart mentioned in the training material. below is the screenshot from my environment.   the instruction mentions two times about “would you like to make changes to the selection”. the action is inconsistent.  The second question should be updated to be the real one.  

We have requirement to update capabilities in existing groups in CDF using Python SDK/API, we can add capabilities while creating group using python SDK, but if we want to updated that created group no provision for that. we tried client.iam.groups.create(group) but it creates new group with same name, in this case how we can update capabilities in group?