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We have an OPCUA Server (Server) that sends an array (Array) of length 500 every second. We need an OPCUA Client (Client) to stream this array to cloud.First, we use UaExpert an open-source software as Client. Here we can see a node for Array which has values of Array[0], Array[1], Array[2], Array[3], … Array[499] Next, we use Cognite OpcUaExtractor as Client to stream data to cloud. But we result in only Array[0] being sent in each instant (second). I have tried to adjust different parameters in config file with no success.

In a hypothetical scenario where we need to extract asset hierarchy directly from PDF-based P&ID documents, does Cognite provide a built-in library to support this? Or would we need to rely on external libraries like PyMuPDF or pdfplumber for data extraction—or even tools like Pytesseract in cases involving scanned images?Thank you for any guidance on best practices or integrations for this use case!

We are looking to add Events into our CDF solution via an existing OPC UA Extractor. The OPC UA Extractor is currently pulling data from KEPServer and pushing into time-series end-points.We want to add some of the binary & string references in the PLC (which are now exposed in KEPServer) as Events so that we can utilize the Charts over-lay function.Is there a worked method for updating the OPC UA Extractor file for this purpose? Does it require KEPServer Alarms & Events plugin to be used? We have used this link already: Configuration settings | Cognite Documentation

Hello everyone in the community,I have a question:I have a project created with CDF and the assets are already contextualized with the P&IDs. I received new revisions of plans.My question is, do I have to contextualize everything again and what has already been contextualized is lost? Is there a way to only upload the new plans in the new revisions and have it done automatically?

I am looking at 127 time series linked to one asset and I want to download the list of these time series as shown in the screenshot below, but this doesn’t appear to be straight forward.The download button circled in blue saves a JSON file linked only to the asset “11. QHP”. Is there a way to spare the user the effort of manually selecting and downloading each of the 127 timeseries and later reassemble them into one table like the one shown in the browser?  It is not possible to select and display more than 20 columns in the browser … due to performance issues. This is not critical at this time, but still dissatisfying. I want to download everything wholesale and pick what I need from the list locally. Is there a way around this restriction? Solving issue #1 would remedy also #2, as I’d be able to join the tables locally again. Thanks

Search option is not working in non-pdf document at CDF for Documentum.Steps to reproduce the issue: Login to CDF Click on Data Explorer tab in CDF menu bar. Click on Files tab in right side of the panel. Set Data set as ‘src:006:documentum:b60:ds’ under Common filters in left side of the screen. Enter the file name ‘ELECTRICAL SAFETY RULES.docx’ in search bar. Click to open the file. Expected results: User should be able to see the preview of file and search the any word inside the document.Actual results: Search option is not working in preview of file and displaying message ‘this document is not searchable.’

Hello Cognite Community,I am working on a workflow that involves receiving a daily email with a consistent title in Outlook. Each email contains an attachment that I need to extract and process. I'm looking for a way to automate this extraction process using Jupyter Notebook.Has anyone implemented a similar solution or could guide me on how to approach this? Specifically, I’d like to:Identify emails by their subject line Download the attachment(s) automatically Work with these files within a Jupyter Notebook environment for further analysisAny suggestions, code samples, or libraries that could help with this integration would be greatly appreciated!Thank you in advance for your insights

 Hello,  We are unable to select version of workflow from the UI. for instance here we are at version 0.0.39 and in the UI the workflow is at version 0.0.1.I think this might be an UI issue. Thanks

Hi.I’ve set up a data model with 26 containers. How come only the first 10 of them (in alphabetical order) show up in the Fusion UI? I successfully return all 26 containers using the python SDK:client.data_modeling.containers.list(space="sp_kra_enterprise_model", limit=None) 

Hi.I’ve got an enterprise data model set up, and built a test solution model with a subset of the enterprise model, and also expanding one of the views. Somehow my solution model does not show in the UI - only a spinning wheel is shown. Does anyone know where I can start to troubleshoot this?  I’m able to populate the model with transformations, and I can retrieve the resulting nodes using the Python SDK, so the model seems to be working. Can this be only a UI issue?

Intermittent Internal server is seen while reading RAW table. It is happening in different functions that may not be part of some workflows. It is blocking workflow to run as we use these staging tables to get information for other functions. Is there is any check that needs to implemented ?  

I’m using cognite/reveal and cognite/sdk for a project developed in react (18.x).While connecting cognite/reveal with react application I’m encountering this error:e.BufferGeometry is not a constructorTypeError: e.BufferGeometry is not a constructor I would like to know what is causing this error. code attached below:-   A help to figure out the issue would be helpful.Thank you, Regards,Hariharan B P 

Hi Community,I would like to know if anyone have information on how the Cognite Streamlit Reveal python package full feature & capability documentation? Second, can the "cognite-streamlit-reveal” have the zoom in / zoom out event trigger? This is because we want to develop a use case where user able to zoom in into the oil rig plaform 3D and once the zoom stop, it able to send and event to show what are the bounding box of that area so that we can load data related to that specific area during zoom in and zoom out interaction. Thanks

Hello!I'm trying to develop a PowerBI dashboard but encontered some situations where it's impossible to not expand new columns or lists from the nodes (foreign key from dimension table is inside the node) and I understand this drops the performance considerably (sometimes even turns impossible to load the table) of the model in the dashboard.Is there a way to query the data straight from the connector? I know there's the possibility of making simple filter queries but I wasn't able to use other type of OData queries that exists. We need a solution that simplifies this since currently it's impossible to load more complex data models into PowerBI without expanding the nodes.Please understand that I want to keep this situation as low code as possible, so an API or SDK solution is not an option.Thanks!

Hi,I am working on one of the project where I am using MQTT extractor to inject data into CDF. Kindly advise best optimized stepwise solution to integrate and transform data into CDF.Note that it is Sparkplug B-formatted MQTT data.Kindly advise.Regards,Amol S Pawar

Hi Team,I'm excited to be registered for the Data Engineer Basics course, specifically the “Learn to Use the Cognite Python SDK” section!While working through the “List, Search, Retrieve” portion, I came across an issue. The documentation states that the general pattern for search operations is `client.<cdf_resource_type>.search()`, where `<cdf_resource_type>` could be `data_sets`, `asset`, `time_series`, `events`, `files`, `labels`, and so on.Following this, I tried the code:```pythonc.data_sets.search()```However, it resulted in the following error:```AttributeError: 'DataSetsAPI' object has no attribute 'search'```I double-checked the Python SDK documentation but couldn't locate a `search()` function for `data_sets`. Could you please let me know if I missed something? And if the `search` function for `data_sets` is indeed unavailable, perhaps it could be noted in the documentation to prevent future confusion?Thank you for your help and for the informative course! Best re

Hi!I have a question regarding how quickly the metadata for a FunctionCall is updated after a successful call. The reason I ask is the following case:I have deployed a set of Cognite Functions that run on a schedule every minute. In production this will be every 10 minutes, but for testing and debugging I want to speed it up to see how it works.One of the functions perform this job:1. Determine the time range for the data fetch based on response value of previous call (if first call we use pd.Timestamp.now())2. Fetch Events in time range and process the data3. Write processed events to a Sequence resource in CDF4. Return a dict {"status": "success", "start_time": start_time}The start_time of call N becomes the end_time for call N+1. The function is a “historic backfiller” that traverses back in time to a pre-defined date and fetches Events along the way.The issue:I have run into the scenario that in call N+1, when I get the response of call N, the status of call N is still Running. So

Is there currently, or is it planned on the Cognite roadmap, a Job UI for real-time tracking of job statuses, including runtime, failure reasons, and retry counts? Additionally, will it provide a step-by-step view of each job’s progress to help easily identify and troubleshoot issues?

Hi Developers! :)I have a use case where I need to retrieve a large number of Time Series data points from CDF. We are a final DataFrame with a shape of approximately (1000, 400000).  So a total of 4 billion data points + the index. I also want the data retrieve to be fast…. :)  So instead of retrieving everything in a single call to `client.time_series.data.retrieve_dataframe`, I thought to use multithreading to start the retrieves in an approximately parallel fashion, and then concatenate the resulting dataframaes at huge runtime gains! However, I observe that the results from multithreading do not equal the results from the single call. :( Specifically:I split the data retrieval on Time Series IDs, and concatenate along axis=1. I observe that data from the “first two” threads have a lot of missing data, while data from the last two threads are 100% correct. I have also tried to split the DatetimeIndex and multithread along this dimension, but I see exactly the same result in that so

I would like to know if Cognite visualization has the same features as the one found in Power BI and Tableau.The reason is simply because we need to have Decision Support and Visualization module as part of our overall setup.

Hello,I’m trying to pull energy usage data from a Rockwell power monitor that supports OPC-DA but not OPC-UA. I configured the OPC-DA server (rslinx classic in this case) and I’m able to see the live data using an OPC-DA client (Kepserver). Next I try running the extractor, and it sees the project structure and creates assets, but never creates any time series data. I’m seeing very little in the logs. I did notice that “contious: False” shows up, but I don’t see any way to change that via configuration. I will get a keep alive message as you can see in the second image, but no data. Any suggestions would be greatly appreciated! Thank you.  

Hello everyone,I have a problem viewing 3D. It tells me that I don't have any scenes created, but I do have some. I understand that the error message is because I have to configure the location in the scenes. How do I do that? I don't see the option to add the location.  

Hi Cognite Team,I'm curious about the specific rules you follow for versioning views, particularly with the versioning format like "@view(version: 'v4')". I’ve noticed that the last number is the only one that changes, and I wanted to understand the rationale behind this.In my experience, I typically use the X.Y.Z format, where:Major versions indicate significant changes or potential backward-incompatible updates. Minor versions introduce new features or enhancements. Patch versions address bug fixes or minor improvements.While I understand that tools like DVC are more suited for tracking actual data changes, we are focusing on versioning the views and models. Is this approach aligned with your guidelines?If there aren’t any formal rules, that’s perfectly fine; we’re just trying to establish our own conventions and best practices. Versioning is an important aspect for us, and any insights you could share would be greatly appreciated.

In a hypothetical scenario where your company has more than 100 sites across different countries, each containing multiple units, it's important to organize data in a way that ensures scalability, flexibility, and ease of maintenance.We have our own perspective on the matter, but we would like to hear from other specialists, especially those experienced in data modeling approaches, like yourself. Example 01: Managing Employee Information Inside CogniteQuestion: Should we separate SPACEs for each site? Example Structure in Cognite Data Fusion:You can structure the SPACEs for your company’s sites and units as follows: Top Level: Country Create a SPACE for each country to organize data regionally.Example: US, BR, IN (for the United States, Brazil, and India). Mid Level: Site For each country, create separate SPACEs for each site within that country.Example: US_COR, BR_SAO, IN_BOM (COR for Corpus Christi, SAO for São Paulo, BOM for Mumbai). Low Level: Unit Inside each site’s SPACE, cre

Hi.I would like to experiment with using more of the advanced functionality in data modeling. For instance, everything related to importing views and mapping properties between data models. However, I feel like the documentation (https://docs.cognite.com/cdf/dm/dm_graphql/dm_data_modeling_language#specification-of-directives) is a bit lacking of examples of how to use the functionality. Are there any end-to-end (both basic and advanced) examples or other training material of how to reference data in other data models using all the different directives specified. For example examples of best practices when referencing between a source model and a domain model, and when referencing between a domain model and a solution model.Thank you!Sebastian