Community Discussions

Hi When testing some new functionality in a Cognite Function I got this error message: “The size of the data field is too large.”The data input was from the output of another function ran previously in a workflow.I am looking through the documentation to find what the limits are, but can not find anything.For my use case I can decrease the input size and run more batches, but it would be good to know what the size limits are for input data into Cognite Functions. Also, are there any other size limits I should be aware of?Thank you!Sebastian

“I’m using cognite/opcua-extractor-net as container.Is there a docker image version for linux/arm64 platform available ? (not present on docker hub)”

hi guys,  can you please tell me the reason of the error below while API testing in Postman:any help is very much appreciated 

Hello,I am using OPC UA extractor to bring in sensor data in my cdf project. I want to limit the number of tags I am bring in from the source. I observed that in the PI extractor there is capability to include or exclude tags. Is there a similar filtering capability in OPC UA Extractor?

If I want to establish a relationship between a specific data model (not the core or enterprise model) and assets like a "function location," Do I  necessarily need to bring all the views from the core or enterprise models into your domain data model?The goal is not to extend the core model but to create a reference from my domain data model to the asset, possibly using node_reference.For instance, if I have an inventory and want to relate materials to a local storage (which is represented as an asset in the enterprise data model), could I define a property in my domain model that references the enterprise asset.Example:graphqltype StorageLocation { location: String plant: CogniteAsset # Reference to the asset in the enterprise model } In this case, I am just creating a link between my domain model and the asset without needing to extend the enterprise model or bring its full view into my domain model , works? 

Hi all,I am building a solution model on top of  a domain model we already have in place for a project.The domain model contains all the instances we have in the project, but this consumer is only interested in a subset and would like some filters in place to ensure that they are only getting the subset of interest. One of the requirements is that a certain property is according to their project standards and has a minimum length for a property. I see that there is a Range filter to check if a numeric property’s value is within a specified range, but is there any way I can add functionality to get the values length for this property?

I have the following question regarding Containers,  Spaces and Instances. Let's say I have a Container named Well in the space A and all its instances are created in space B. When I delete container Well in space A and recreate it (because I want to change a column name for example): Does instance in space B are deleted as well? If they are not deleted, If I rerun the transformation to populate the new container again in space B with the new schema (same external_id) what state should I expect my instances to be in ? A merge of old and new schema? What is the best practice ? To delete container in its space and its instances in all spaces also? Thank you!  

This might be a basic question, but I often find myself uncertain about when to use CogniteDescribable in data modeling within Cognite Data Fusion.For example, let's say we have domain tables in our data model, such as MaterialType, which contains data from SAP and defines the types of materials we work with (e.g., code and description). In this case, would it be appropriate to implement CogniteDescribable to reuse common properties like name and description?What are the advantages of doing so? Does using CogniteDescribable provide any specific benefits—such as improved performance through indexing or partitioning—when used it containers?In summary, should I always use CogniteDescribable in these types of scenarios, or are there cases where it's better not to?

 I have created 1 workflow , in which I am creating dynamic tasks depending on input, it creates batch of ids and create tasks out of it. Below is workflow definitionWorkflowVersionUpsert(   workflow_external_id="test_dynamic-0729",   version="1",   workflow_definition=WorkflowDefinitionUpsert(       description="This workflow has two steps",       tasks=[           WorkflowTask(                external_id="test_sub_tasks",                parameters=FunctionTaskParameters(                    external_id="test_sub_tasks",                    data="${workflow.input}"                ),                retries=1,                timeout=3600,                depends_on=[],                on_failure = "abortWorkflow",            ),           WorkflowTask(                external_id="test_create_sub",                parameters=DynamicTaskParameters(                    tasks="${test_sub_tasks.output.response.tasks}"                ),                name="Dynamic Task",                description=

I’m using n8n AI agent builder to query CDF via an http request. The body of the request is:The request URL is https://westeurope-1.cognitedata.com/api/v1/projects/essc-sandbox-44/events{ "filter": { "startTime": { "min": 1751070336000, "max": 1751588736000 }, "dataSetIds": [7726848970162689] }, "limit": 1000}CDF seems to recognize the datasetid filter but not other filters like starttime as shown or others like Types. The result set returned is all events in that datasetid.I’ve also tried minstarttime and maxstarttime.ideas?  

Hi All,We are encountering an issue after uploading E57 point cloud files into Cognite Data Fusion (CDF). The rendering quality of the images is quite poor, and we're unsure if we're making a mistake during the upload process.Has anyone else experienced similar issues? If so, do you have any solutions or recommendations to improve the image quality for point cloud in CDF?Please feel free to share your insights and suggestions.Thank you!

hello guys, I wonder how do you populate data model directly from the dataset? so i have ingested all my timeseries data into my dataset and then i want to run transformations using this dataset as a source but how do i get the actual values from the data points and can you filter just to extract certain timeseries data? this is the query i am running at the moment: select  cast(`externalId` as STRING) as externalId,  cast(`name` as STRING) as name,  cast(`description` as STRING) as descriptionfrom  `_cdf`.`timeseries`; what i want really is to import all my timeseries data from my dataset into my data model and then continue building. 

I have a question about contextualization.In my setup, I have a functional location with a machine, and under the machine, there's a sub-station. When I contextualize a document related to the sub-station, why isn't it directly linked to the machine level and the functional location? I understand that I manually contextualize it to the specific station, but since the station is part of the machine and the functional location, it should appear there too.I think there's a missing link in my data modeling between the functional location, machine, and sub-station. What methods can I use to ensure that when I contextualize a document, it shows up at all levels of the hierarchy linked to that machine?

i want to take export of one table to another table but facing this datatype error .also tried with multiple datatype (like string , float and Bigint ) still same issue is coming.  

Hey everyone! 👋 I've been diving into the world of CDF data modeling for the past couple of weeks, and I thought I'd share what I've learned so far in a way that's easy to understand. First off, let's talk about the term "Data Modeling." It's everywhere in CDF - in API endpoints, UI, docs - but its meaning can vary depending on where you look. After some digging, I've figured out what it means specifically in CDF. Essentially, it's about organizing, storing, and working with data in a way that's perfect for handling complex industrial scenarios. Think of it as the foundation for unleashing the power of Cognite Data Fusion on your industrial data. So, what exactly makes up a Data Model in CDF? Let's break it down: Space: Think of it like a folder where everything in a Data Model hangs out. Containers, views, instances - they all belong to a Space and have their own unique ID. Containers: These are like the storage units for properties. They live within a space and hold sets of proper

SUMMARY Committed to elevating our service and support standards, we continually evaluate and refine our processes to improve the exchange of information between end-users and the Cognite support team. We have identified that including additional information upfront in the support tickets raised can greatly streamline our response process, allowing for quicker and more efficient issue resolution. To facilitate this, we have pinpointed essential details that, when provided in tickets, can significantly accelerate resolution times.We are dedicated to continuous improvement in these areas and greatly value your feedback.  There is basic information that will be helpful for troubleshooting Have you encountered this issue before, or is this the first time you have experienced it? To better understand the impact, please let us know the number of affected users. What is the project name? The following questions will be added based on the product: SUMMARY Charts Questions  Functions Questions

Hello,  We are using: Toolkit Version '0.5.20' We are having a file schedules.Function.yaml: - name: Run every 10 minutes to do some work functionExternalId: fn_name description: Run every 10 minutes to do some work cronExpression: "*/10 * * * *" data: extractionPipeline: "test"When deploying we have this error trace: Traceback (most recent call last): File "venv/bin/cdf-tk", line 8, in <module> sys.exit(app()) File "venv/lib/python3.10/site-packages/cognite_toolkit/_cdf.py", line 116, in app _app() File "venv/lib/python3.10/site-packages/typer/main.py", line 340, in __call__ raise e File "venv/lib/python3.10/site-packages/typer/main.py", line 323, in __call__ return get_command(self)(*args, **kwargs) File "venv/lib/python3.10/site-packages/click/core.py", line 1161, in __call__ return self.main(*args, **kwargs) File "venv/lib/python3.10/site-packages/typer/core.py", line 740, in main return _main( File "venv/lib/python3.10/site-packages/typer/core

Hi,I would like to update data to the EDR. The EDR has a build in tool to upload data, but I would like to use the API. As I understand it is not officially supported, but we would like to give it a try as we have hunderds of files we would like to upload.Before I asked my questions by e-mail, but I am directed to this hub to ask my questions, so there we go: File upload:I'm using the client.files.upload() function [1]. It seems to work when only the file path is provided, but I'm unsure whether this is sufficient or if I should be populating more of the optional arguments. Here's what I'm looking at: path external_id name source mime_type metadata directory asset_ids source_created_time source_modified_time data_set_id labels geo_location security_categories recursive overwrite  name: It appears this is automatically assigned based on the filename, is that okay?directory: This seems to default to the dataset ID, but I’ve run into an error when using 968ca

Whose idea was it to hide the dropdown behind the filters? 

Does it make the data available for optimal maintenance scheduling, or does it automatically generate maintenance plans based on that data? Does it predict failures?

Hi,We have uploaded a 3D .nwd model using the Fusion UI and noticed that the underlying processed 3D files (e.g., .glb, .reveal, .zip) are stored as file resources and are visible in the Data Explorer under the Files resource type.I couldn’t find any documentation or guideline on how to assign security categories to hide or restrict access to these files for end users. I also tried using dataset-based access control, but I’m looking for a better or recommended way to handle this.Appreciate your guidance or suggestions.

The python extractor utils requires the config to be stored as a local file there is not way to pass it directly as a string/yaml object. This makes it quite cumbersome to use as not all our deployments have access to local file storage for config files.Is there a way to add support for the config to be passed as an environment variable? Reading config from env example:  

  The countdown is on! Cognite Hub has officially launched the Impact Challenge 2025 -a no-code hackathon inviting all our community members to roll up your sleeves and solve real-world challenges using Cognite Data Fusion. Unlocking Value Through Community InnovationAt its core, this community-driven initiative is about unlocking value - from accelerating CDF adoption to creating user-friendly solutions, breaking down silos, and driving measurable business impact. And it’s all happening without writing a single line of code. Let’s turn ideas into Impact!Expert Support and MentorshipParticipants will be supported by a panel of Cognite experts and community leaders who will mentor and guide top ideas as they evolve. After an initial round of social voting, the top 10 concepts will receive dedicated mentorship to help bring their visions to life.Recognition and RewardsAnd the reward? The best ideas will step into the spotlight at the Impact Conference in Houston, gaining visibility, reco

Good news, innovators!We've heard your requests and have extended the deadline for registration, team formation, and idea submission for the Impact Challenge 2025. You now have until this Friday, June 13th, at the end of the day (US time) to get your ideas in.Don't miss this opportunity to solve real-world challenges with Cognite Data Fusion®, win amazing prizes, and present your solution at the Impact Conference in Houston.No coding required!👉 Join the Challenge Now: https://hub.cognite.com/p/hack-for-impactLet's turn your ideas into impact!

I am getting following error when ingesting files from SharePoint site to CDF. send_request_body.failed exception=LocalProtocolError('Too much data for declared Content-Length')Anything I need to specify in .yaml file to allow content-length? Also how do I trace which file is causing the problem. I changed Logger to DEBUG level but still don’t see the file name info.Thanks,Zuber