Solved

Is there currently a best practice for adding a geographical location to an object in a data model?I’ve considered simply using a string property to my model containing wkt-formatted strings, or a GeoSpatial feature external id, but none of them seem ideal. I assume there is a size limit on strings - so that wkt might be a bad choice? We’ve previously discussed this for timeseries, where you mentioned that data model geolocation was on the roadmap. Any update on this? 😊 

In the image above, Target data model in document is mentioned as CDF resource types, and in the image below its Asset Hierarchy.  Same thing for resource type.Can you please check.

Hi,I am using Time zone and Calander granularity function (Release timezone and calendar features in DatapointsAPI (beta) by haakonvt · Pull Request #1779 · cognitedata/cognite-sdk-python · GitHub)I am facing an issue wherein I am passing following datadps_lst = client.time_series.data.retrieve_dataframe_in_tz(   external_id=list,   start=datetime(2023, 6, 24, tzinfo=ZoneInfo("America/New_York")),   end=datetime(2024, 6, 27, tzinfo=ZoneInfo("America/New_York")),   aggregates="average",   granularity="1month") For the End date time is given as 27th June 2024; while I am expecting to get a calculation from 1st June- 27th June; I am receiving an output from 1st June- 30th June. the functionality is not considering “end” date while calculating.  

Hi, we are using Cognite PI Extractor and in PI we have time series where there in some cases are only nano seconds between each datapoint. Since CDF use epoch milliseonds how will the extreactor handle such cases? 

Hello,Is there a way to round timestamps of the incoming OPC UA tags to second within the configuration file? I have gone through the documentation but haven't found anything like that. The problem is that for some tags coming from an OPC UA server I make some simple transformations and these tags are coming to CDF with timestamps at ms, whereas the other tags for which I do not apply any transformation on server side, are coming with timestamp at second. The issue I encounter is when I push the data from CDF to PowerBI and pivot the data and I get 2 rows for the same timestamp which PowerBI is displaying at second, 1 row with values for the tags without transformations and the other with the tags transformed which have timestamp in ms on CDF side. I just don't want to apply another query/transformation step to round the timestamp at second on PowerBI side and on CDF this timestamp rounding should be a scheduled transformation running every minute if not every second. Regards,Raluca

Hi Team,I was looking for any limitations to length or any other limitations for Json data type for properties in the data model but was unable to find it in the documentation.Do we have any limitations? If yes, we would want to know. We are planning to use the json data type in the model to store values for an ongoing project as part of our solution.Thanks,Akash@Aditya Kotiyal 

Hi there,Could you confirm if there is a limit on number of tables allowed within single databaseor is there any limit of tables or database per project ?

Hi,Our project uses Cognite Function scheduling to deploy data to CDF, and we struggle to understand what the “Duration” of a Cognite Function actually represents. I have attached a screenshot showing one of our function calls, printing the duration of various function from our source code. As you see the duration of our source code takes 2+ minutes, but the call of the function itself takes less than 2 minutes (start at 7:40 and end at 7:41). Is there a distinction here between what is actually run in the backend, and overhead in terms of instantiating a call to the Cognite Function? Can anyone explain the apparent deviations? Thanks.  

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="

Is it possible to increase the limit on execution of workflow instances per project or limit on execution workflow instance itself instead of project ? as we require to schedule workflow, on that it depends how much data we get to run workflows instances, so it can be more than 50  

Hello Currently Maintain workorder has been displayed in infield under work order. My understanding is we plan the activities in maintain and the plan get visible in Infield via work order. What is the relationship between activities in maintain as compared to checklist in infield. I am imaging that once we plan activities in maintain, we should be capable to “convert” the activities into checklist in infield?  

Hi,Lately, the “Open in Charts” button in Fusion changed behaviour. It used to open the specific time series in a new chart, while now, the Charts home screen is opened without pointing to the specific time series. Is this intended behaviour? 

I created a process monitoring job several weeks ago and it seems to work as expected showing me the folder I created and alerts were delivered to my inbox. After 2 Recent attempts to create monitoring jobs, the UI stated the job was created but I’m not seeing the new folder nor am I receiving alert emails or seeing indications under the alerts tab in Charts. 

A fictitious example, but one that reproduces my problem, is the following code: for event_list in client.events(chunk_size = 500_000, data_set_ids = ids_sites):        events = event_list.to_pandas() Error message after just over an hour: CogniteAPIError: Unauthorized | code: 401 | X-Request-ID: 9c8702fc-59bf-9f7a-be47-4876d6b433f3 In fact, if I iterate in another way (for example, filtering by date), I can run code for more than 8 hours (for as long as I want, actually, because I re-authenticate between iterations, preventing the token from expiring). However, I don't want to filter by date because it doesn't provide consistent data volume like iterating by chunks.And apparently, I can't authenticate between iterations in the example I provided here, as it seems the chunk persists the initial authentication, which initially makes sense. Does anyone know how to solve this?   

I am analyzing multiple tags with same Engineering Unit. The charts are getting overlapped even after Stacking feature is ON.   

Hi,I need to use a custom python library from a private repository in Cognite Function  I have referred the following document - https://docs.cognite.com/de/cdf/functions/ In requirements.txt have added --index-url with the basic HTTPS authentication referring private repository URL with credentials.However when I am deploying the functions its not deploying and failing with the following error: Function Id 3485252813249865 Note: I have tested this locally its running fineCould you please help with this?

type Relationship @edge @view(space: "space-name", version: "1_1"){    relationName: String!,    relationType: RelationType,    startTime: Timestamp,    endTime: Timestamp} is there any library developed by cognite which will validate above kind of graphQL syntax also is it possible to check the values provided in graphQL ?

What is the process involved in building the contextualized Industrial Knowledge Graph?  Are we referring to  creation of a  GraphQL schema for a usecase and query data using GraphQL?Is there any training link to lean more about Industrial Knowledge Graph?How can I visualize the GraphQL query output (nodes & edges) as shown in many Cognite documents? 

Hello All, I am curious to know, how does Cognite follows containerization practices. Can we create and use virtual environment in CDF jupyter notebook?I had installed (%pip install) some packages in my notebook and used it for a while. Surprisingly in next session (Notebook restart / kernel restart) it is giving error as ‘package not found’. 

Using the figure from the documentation for my question regarding mapping (below).In the figure, a new view called BasicPump is created by mapping attribute “manufacturer” from Equipment container, and “maxPressure” from Pump container. If the attributes “manufacturer” and “maxPressure” are indexed in their respective containers, does the view BasicPump benefit from these indexes?Ref: https://docs.cognite.com/cdf/dm/dm_concepts/dm_containers_views_datamodels/

Hello team, I am facing constant issue with jupyter notebook in CDF. It often stops working with memory error. Is there any document - how much data can be fetched / analyzed in single attempt with Jupyter notebook? PFA for reference.Also, does Cognite has any ‘compute instance upgrade’ option? Also, being a SAS product, is it having auto scale feature?  

Asset which linked to Timeseries or vice versa filtering option is not available in Data Explorer screen in CDFAnd Also, Asset linked to Event or vice versa event linked to Asset Filtering option is not available in Data Explorer screen in CDF.Also, Files to Events or Events to Files etc.

We are using the MQTT hosted extractor in CDF to retrieve data from an MQTT broker hosted on Microsoft Azure Event Grid.One method for authenticating an MQTT client in Azure Event Grid is through thumbprint matching. In this authentication process, a certificate file (.pem), a key file (.key), and a username are verified by the broker. However, in the Cognie hosted extractor, it's currently not possible to provide the username simultaneously with the certificate and key files.If only the key and certificate files are provided, an Implementation Error is encountered as expected.How can I provide username information along with the key files to the hosted extractor? 

Hello Team, I am trying to list views available in my model, using the functionpdmViewList = client.data_modeling.views.list(space= pdmSpace,all_versions=False, limit=-1)This runs successfully in Jupyter notebook when I test it, but fails in Streamlit app, I am unable to figure out the reason. Can someone help if I am missing out on anything here?Below is my code snippet from my app:import streamlit as stimport pandas as pdfrom streamlit.components.v1 import htmlfrom cognite.client import CogniteClientfrom MyLibrary import get_pdm_facetfrom cognite.client.data_classes.filters import ( Equals, And, In, FilterValueList, Or, Prefix)from cognite.client.data_classes.data_modeling import ( NodeApply, # node constructor ViewId, # view reference DirectRelationReference, SingleHopConnectionDefinition, NodeOrEdgeData, NodeId, InstancesDeleteResult)client = CogniteClient()# PDM Model DetailspdmModelExternalId = "production_domain_model"pdmSpace = "slb-pdm-

HiI am practicing through online help manual through “https://learn.cognite.com/” Where I am successfully logged in to  “cdf-fundamentals” project. Now want to create new data set  as per instruction there is icon on left side to create new data set but I dont find it.Can anyone have idea how to create new data set in “cdf-fundamentals” demo project.