Solved

Hi Team,We are currently exploring migration of our existing content to use Flexible Data Modeling in CDF, and we are facing some challenges while configuring the OPC UA Extractor.At the moment, we are still pointing the extractor to the traditional Asset-Centric Time Series (dataset-based approach) and then transforming the data into our Data Model types afterward. However, we would like to ingest data directly into a view that implements the CogniteTimeSeries type.We would appreciate your guidance on the following: Do you have any example .yml configuration for the OPC UA Extractor that ingests data directly into a view implementing CogniteTimeSeries? Are there any best practices or recommended approaches for this setup? Is the following documentation the correct reference for this use case?https://docs.cognite.com/cdf/integration/guides/extraction/configuration/opcua#data-models Additionally, we are also evaluating OPC Events ingestion: Should OPC Events be modeled using Cognite

The documentation link takes me to a 404 page: 

Help! 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?  

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?

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.

In the Charts chapter, question 7 and 8 in the quiz asks for some reference values that I cannot understand can be correct. The quiz asks for number of  threshold events and durations within a specific timeframe: From the Data quality use case, how many gaps / events have been detected in Temp in: Gaps detection calculation during the following period: Jun 9, 2022 (9:00) - Jun 10, 2022 (9:00), Type: Between Min & Max of 1? However, none of the alternatives match the resulting dataset I see in Charts. I am a new learner, so perhaps a mistake somewhere, but I have checked multiple times and cannot see any error on my part. Is it only me? Or is there a mismatch in the data? Kind regardsJohannes 

How does asset hierarchy work in CDF?

How are .nwd and .lfa files rendered in Cognite Reveal? Does CDF already convert .nwd and .lfa files in a lossless way, without losing any node or asset metadata? Is is converted to .glb/.gltf file types as conversion output?What happens if we use raw Three.js instead? How can we work with .nwd files in that case? Three.js doesn’t support .nwd files directly, right?Is it necessary to convert them to .fbx or .obj formats? Wouldn’t that result in a lossy conversion, potentially causing loss of metadata, asset hierarchy, or textures? How do we use .nwd and .lfa files for show warnings or overlays? 

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

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. 

Hi,I am trying to install Prosper, GAP and Unisim connectors but the instalation is failing for all of them.It just says that it cannot start the service and that is the only message I gotStart-Service : Failed to start service 'Cognite GAP connector 2.0.0-beta-6 (GapConnector)'.At line:1 char:1+ Start-Service GapConnector+ ~~~~~~~~~~~~~~~~~~~~~~~~~~ + CategoryInfo : OpenError: (System.ServiceProcess.ServiceController:ServiceController) [Start-Service], ServiceCommandException + FullyQualifiedErrorId : StartServiceFailed,Microsoft.PowerShell.Commands.StartServiceCommand 

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 used to run this version to upload simulator connector, model and routines, but it is not working anymorehere is the error I pydantic_core._pydantic_core.ValidationError: 3 validation errors for PagedResponse[GroupResponse]items.324.capabilities.6.acl.scope.scope_nameInput should be 'all' [type=literal_error, input_value='agentExternalIdScope', input_type=str]For further information visit https://errors.pydantic.dev/2.13/v/literal_erroritems.526.capabilities.6.acl.scope.scope_nameInput should be 'all' [type=literal_error, input_value='agentExternalIdScope', input_type=str]For further information visit https://errors.pydantic.dev/2.13/v/literal_erroritems.639.capabilities.6.acl.scope.scope_nameInput should be 'all' [type=literal_error, input_value='agentExternalIdScope', input_type=str]For further information visit https://errors.pydantic.dev/2.13/v/literal_error

I am program manager with one of IT service organization. I want to know, what all the courses i need to complete in order to make sure i have all the information i need in order to manage a program?

Hi All,I just created an Asset in the Cognite Fundamentals workspace, following the guidelines from the course. After following all the steps mentioned I was expecting to find the asset Pranav1992 in the Search under Other Categories after logging into Industrial Tools workspace.However, upon filtering I do not see it there, can someone please help if I missed something?Thanks,Pranav

Hello experts,I have a question about Cognite Functions. I know there’s a limit on the size of the input data, as discussed here : Cognite Hub and documented there : Cloud provider limitations - Cognite Docs But is there a limit on the size of the function’s output? I have one that works perfectly fine but crashes without any explicit error message when handling a large output payload (>500 KB). I’m on Azure provider.Is there any information on this? Thank you,Best regards,Pierre Rambourg edit : the initial error was on my side, but i’m still interested for output limits !

Hi,In the course “match entities with python sdk ” https://learn.cognite.com/match-entities-with-python-sdk, when running the notebook, I can modify it to connect to Cognite using the same credentials as in the “Learn to Use the Cognite Python SDK” course. When I get to cell 5, I get this error:“””TypeError: DataSet.__init__() missing 5 required positional arguments: 'id', 'created_time', 'last_updated_time', 'description', and 'metadata'“””This is what is in cell 5:# Create datasetstry: bra_dataset = client.data_sets.create(DataSet(external_id="BRA_TestData", name='TestDataset', write_protected=True))except CogniteDuplicatedError as e: print("BRA_TestData already exists, you can continue") bra_dataset = client.data_sets.retrieve(external_id="BRA_TestData")try: nor_dataset = client.data_sets.create(DataSet(external_id="NOR_TestData", name='TestDataset', write_protected=True))except CogniteDuplicatedError as e: print("NOR_TestData already exists, you can continue") nor

Hi Cognite Team,We are currently defining an integration pattern for a partner who will provide data from an OPC UA source into Cognite Data Fusion.Our preference is to use a managed MQTT broker in CDF and avoid deploying any self-hosted MQTT broker or additional bridge components on-prem.Based on the documentation, we understand that the OPC UA Extractor supports an mqtt: output mode, but it also references a requirement for the MQTT-CDF Bridge and a configured broker host/port.To ensure we define the correct and supported architecture, could you please clarify: Is it supported to configure the OPC UA Extractor to publish directly to the Cognite-hosted MQTT broker in CDF? If using the Cognite-managed MQTT broker, is the MQTT-CDF Bridge still required? Is a self-hosted MQTT broker mandatory when using the mqtt: configuration in the OPC UA Extractor? What is the recommended architecture today for a partner delivering OPC UA data into CDF using MQTT? Our intended target architectur

Hello Experts,I’m trying to use advanced filter on timeseries through SDK. I can do what I want except in the following situation: the asset_id property is null. Can anyone help me?I tried :from cognite.client.data_classes.time_series import TimeSeriesPropertyf = filters.And( filters.Equals("data_set_id", 123456), filters.Equals("name", "foobar"), filters.Equals(TimeSeriesProperty.asset_id, ""))[advancedFilter.[2].equals.value A string is not a valid value for the property "assetId"]from cognite.client.data_classes.time_series import TimeSeriesPropertyf = filters.And( filters.Equals("data_set_id", 123456), filters.Not(filters.Exists(TimeSeriesProperty.asset_id)),)-> 0I’m sure there is timeseries where timeseries.asset_id is None.Thanks experts !Regards,Pierre Rambourg

I'd like to inquire about the current status of the monitoring functionality in the workflow orchestration. Specifically, I'm interested in the setup for notification emails. It would be helpful to know if we are able to receive notifications in the event of a workflow failure. Could you please provide an update on this?

Hello experts,I’m looking to work with data workflows.I’m looking to trigger on node with a specific attribute (direct relation to another view) empty.I’m trying to work with the UI but I struggle with the Data modeling query validation.I don’t understand why the validation fails and what is the expected format for the query : JSON seems to be the expected format as seen here : But documentation uses YAML : https://docs.cognite.com/cdf/dm/dm_concepts/dm_querying#graph-query-examplesI’m a bit lost and I need your help. And my query : { "with":[ { "ts":{ "nodes":{ "filter":{ "exists":{ "property":[ "nameTranslations" ] } } }, "limit":1000 } } ], "select":[ { "ts":{ "sources":[ { "source":{ "type":"view", "sp

Hello Team,I am going through the using-cognate-python-sdk-data-modeling course and noticed that the notebook is not returning any datamodelingInstancesList.instances.When I checked the UI, I noticed that I don’t have enough permission to see the Data ModelsPlease advise…….  

Hi, i was asked to bump the toolkit version to 0.7.137 or higher, so we can enable some config for agents tools.When i tested i got some errors,Last run worked fine, on toolkit version 0.7.69 (last friday), for both pipelines below. I have tried both version 0.7.137 and 0.7.139, getting the same error on both Error (on dry run step) - synergi pipeline: Pipelines - Run 20260302.2 logs ^^^^^^^^^^^^^^^^^^^^^^^^File "/home/vsts/.local/lib/python3.12/site-packages/cognite_toolkit/_cdf_tk/apps/_core_app.py", line 367, in <lambda>….^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "/home/vsts/.local/lib/python3.12/site-packages/cognite_toolkit/_cdf_tk/client/api/functions.py", line 62, in retrievereturn self._request_item_response(^^^^^^^^^^^^^^^^^^^^^^^^^^^^File "/home/vsts/.local/lib/python3.12/site-packages/cognite_toolkit/_cdf_tk/client/cdf_client/api.py", line 115, in _request_item_responseresponse_items.extend(self._validate_page_response(response).items)