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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.

Hello Experts! I am trying out a POC where I am creating a basic file upload utility in streamlit app that helps users to upload a file in streamlit which gets loaded in CDF Files.I am trying to take use of the following function from the sdk and tried several ways like providing the upload_url as a ‘path’ variable but nothing worked.Can someone suggest any workarounds on this? client.files.upload("/path/to/file", name="my_file") import streamlit as stfrom cognite.client import CogniteClientclient = CogniteClient()st.title("File Uploader")uploaded_file = st.file_uploader( "Upload your file here...")st.write(uploaded_file) 

Hello:Please share some code example in python sdk to link a file to an asset.thanks

What happens to the container or indexes or during query for a field that has @reversedirectrelation.Kindly point to the documentation that explains what actually happens internally when a field has @reversedirectrelation.

Hello, As another user stated, “I am taking the “Working With CDF: Contextualize” . On “Contextualize P&IDs” its asking me to upload a file through the explore data → files tab. However, it is not allowing me to do so. The option appears grey and I cant continue. Please advice how to proceed.”I am experiencing the exact same issue - can I please get some help also?Seems like because there’s 0 files already there, I can’t select that tab to upload to. Also, when I upload to the Data Explorer, it won’t link the uploaded file to the dataset properly. Am I missing a step?Thanks!Bert

When saving and scheduling a calculation from Charts, the enter credentials dialog hangs in the “checking credentials” and keeps trying to verify in a loop. This happens only if you select the Use CDF client ID and Client Secret option at the top. If you do not choose the top radio button and simply enter the creds and click next, it works ok. 

I have solved the BufferGeometry issue was present earlier, apparently the react-app-wired was not the latest which is why the override was not working.import React, { useEffect } from "react"import { Cognite3DViewer } from "@cognite/reveal"import { CogniteClient, CogniteAuthentication } from "@cognite/sdk"import { getToken } from "../../utils/MsGraphApiCall"import "./Models.css"function Models() { const appId = "KPI-Dev" const project = "celanese-dev" const clientId = "my-client-d" const tenantId = "my-tenant-id" const cluster = "az-eastus-1" const modelId = 7575155737800092 const revisionId = 3624517118008353 async function start() { await client.authenticate(clientId, tenantId, cluster) const viewer = new Cognite3DViewer({ sdk: client, domElement: document.querySelector("#your-element-for-viewer"), }) viewer.addModel({ modelId: modelId, revisionId: revisionId }) } const legacyInstance = new CogniteAuthentication({ project, }) // getToken() const

hello:I want to associate files uploaded to CDF type pdf for example to my model, following this scheme:type Documentation { name: String # This is a CDF built in type file: File # this is the INVERSE relationship of the Pump.documentation # Pump.documentation <-> Documentation.relatedPumps relatedPumps: [Pump] @relation( direction: INWARDS, type: { externalId: "Pump.documentation", space: "Space_PabloPalacios" } )}but when I select the uploaded file it only shows me jpg, any ideas?

On behalf of Celanese, I would like to report an issue we encountered with the SDK Data Modeling instances aggregate, where the filter format changed from yesterday, 06/11, to today, 06/12. Until yesterday, the "equals" filter worked, but today it broke all the calls that used it and had to be modified to the "in" format, which did not work correctly until yesterday.Another bug to report in the aggregate call is that when an array of group bys is sent, the return structure has also changed, no longer receiving a structure with externalId and space, but a string concatenating the two in the format: "space:externalId”, and its nomenclature changed from "GroupByName" to "GroupByName.__direct_relation". 

How to PAN the 3D Model left, right, up, down

Hi! I’m trying to create a Power BI Dataflow using CDF timeseries data. The same data is retrieved absolutely fine when using Power BI Desktop and Power Query inside the Power BI Desktop app, but when I try to use exactly the same query as a Dataflow instead, there is a warning about: “The query “Timeseries” contains columns with complex types that cannot be loaded. Some data is retrieved, but it’s incomplete with big parts of it missing. Looks like the CDF connector is not able to retrieve the data correctly when a Dataflow is used instead of a normal Power BI Desktop dataset. Is there a way to make Dataflow also compatible with the CDF connector?  

In the Cognite Data Fusion Fundamentals path, there is a hands on learning course where I need to create a data set; however, it seems like the UI has gone through a couple of iterations since and I don’t see the `create data set` option based on the path provided in the course. These are the instructions that were provided.This is what the UI that I currently see. (It’s possible my account doesn’t have the right access to create the data set) Can someone please help?

Hello team,We are trying to use the data modeling query instances SDK method.client.data_modeling.instances.query(query) our query is:query { "with": { "Min_15_50ts": { "nodes": { "filter": { "and": [ { "hasData": [ { "type": "view", "space": "QA_Test_Space", "externalId": "Min_15_50ts", "version": "3a62f20104e445" } ] }, { "in": { "property": [ "QA_Test_Space", "Min_15_50ts/3a62f20104e445", "entity" ],

Can someone please suggest, how we can add additional python libraries in CDF jupyter notebook?

Hi.I’m getting the following error:ERROR (ToolkitYAMLFormatError): Failed to load 7.<groupname>.writer.Group.yaml with iam.groups(resource_scoped). Error: CogniteAuthError("Don't have correct access rights. Need READ and WRITE on datasetsAcl.").) I’ve noticed that the “actions”-part of my YAML files have varying indentations. Like below, where the READ action is on a higher level than LIST and READ:- extractionPipelinesAcl: actions: - READ scope: datasetScope: ids: - <removed> - <removed>- groupsAcl: actions: - LIST - READ scope:In the YAML-configuration reference, there are examples of both: - dataModelInstancesAcl: actions: - READ scope: spaceIdScope: { spaceIds: [ 'my_space' ] }<...> - rawAcl: actions: - READ - WRITE scope: tableScope: dbsToTables: my_database: tables: []Does indentat

The information I found here is contradictory: Cognite HubSpecifically, I am interested in Aker BioMarine’s tag data on CDF (example shown below). I did not check the documentation, since I prefer to hear it here, “straight from the horse’s mouth”, if you will.Questions:Is the same time zone used for all of our assets, regardless of location of the geographic location of our manufacturing site? Is the time stamp preserved for time series downloaded using, e.g., Python / Jupyter notebook? Anything else I should be aware of?Thank you very much!

I’m currently writing my Master thesis in collaboration with Aize (represented by V. Flovik), where I’m trying to use Generative adversarial Networks (GAN) to generate synthetic time series data. To do this, I’m using data from Cognite OID. I’ve explored the data in the previous semester, and I figured that one of my main challenges is to find longer periods of data that are “Normal”. Meaning periods without to large irregularities and without too many missing data points. Because even when I aggregate the samples over 30 seconds, there are still samples missing in some periods. Some of these periods are hours long and can’t really be filled in without messing up the temporal development of the data. I can’t find any information about the cause of these periods either.The time series I’ve been looking at are:I’m no expert in process engineering, and I only chose these 9 sensors because another master thesis from 2019 had used these sensors in their project. I therefore reach out here t

I am unable to generate client code for the CDF openapi spec at https://api-docs.cognite.com/20230101/ using deepmap/oapi-codegen for Go, seemingly because the spec contains some errors. Do anyone know of a way to generate an api-client in go for the CDF-api spec? Both commands below rely on having openapi spec downloaded to the current directory from https://api-docs.cognite.com/20230101/ Testing the spec for errors with redocly/cli: docker run --rm -it -v $PWD/swagger.json:/swagger.json redocly/cli lint /swagger.jsonFor me this results in “Validation failed with 25 errors and 382 warnings” Generating the client library using deepmap/oapi-codegen: go run github.com/deepmap/oapi-codegen/v2/cmd/oapi-codegen@v2.0.0 --config oapi-codegen-config.yaml swagger.jsonwith the this config file:package: "cdf_api"output: "cdf_api.gen.go"generate: models: true client: truecompatibility: circular-reference-limit: 100For me this results in the message “error generating code: error creating operat

Hi team,This is what I am trying to achieve:I have written a function to create a new time series (in case it is not already created) and insert data points into it.The newly created timeseries needs to be added to a solution data model I have created.type ESPInputs @view(space: "workflow-sdm-spc", version: "1_0") {    well:Well    pump: ESP,    operatingFrequency: TimeSeries,    voltage: TimeSeries,    pumpIntakePress: TimeSeries,    pumpDischargePress: TimeSeries,    motorWindingTemp: TimeSeries,    current: TimeSeries,    vibration: TimeSeries,    torque: TimeSeries,    pmm: TimeSeries,    operatingFrequencyPmm: TimeSeries}The instances under this view are already present. The newly created time series need to be references to the property pmm that are filtered via well property (I have well external Id and pmm time series external id available with me in the function).I think I need to update the instance in the apply instance as per the documentation, but I am unable to find an up

I type in a comment in the comments pane and there is no way to submit the comment. I press enter and nothing happens. There is no button to submit. When I close the comments pane and reopen, the comment text has been deleted. Am I missing something?

Hyperlink in CDF is not navigate to right screen for the provided hyperlink. User will navigate to CDF by default screen not the intended hyper linke.g: https://oq.fusion.cognite.com/oq-test/explore/search/timeSeries?cluster=westeurope-1.cognitedata.com&env=westeurope-1&journey=timeSeries-114626196540160&q=separator  

The number of assets shown as linked to the file is not correct. The system is wrongly showing the number of assets linked in the file.And also Linked Asset to an asset count is wrong and same issue for linked files, linked time series, Linked events. These linked is different than directly linked items. (A) Linked (Files): this count means all decedent children of a given asset. (B) Directly linked (files): this count is the number of files that are connected directly to the asset. (C) The file count on top: This count may vary since there might be duplicated IDs amongst the different types - the total number is a distinct value. The linked assets are not relevant to the Asset which user try to refer and these Linked assets will not linked to the Asset.Directly linked assets are linked to the assets which user try to refer.User don't want to see linked asset tab in CDF because its doesn't have a meaningful assets linked to it, however Directly linked asset have meaningful tab and same

Hi, I’m doing the data science modules, I’m on Notebook 2 (List/Search/Retrieve) and I note that when I use the LabelFilter on the assets, I find a number of assets with a label called ‘COLD’.  However, when I do c.labels.list               (limit=None), I get only 4 labels and none of them match the ‘COLD’ label. Are labels for assets different from labels that are found using c.labels.list?

Is the following use case a good fit for Data Workflows?Cognite Function that is reading data from Time Series and writing "event-like" data into Data Modeling continuous processing for metric type A ideally an execution every minute, but more importantly no overlapping executions (i.e., if execution takes longer than a minute) passing state from one to another function execution hourly processing for metrics type B Idea:2 Data workflows:Hourly execution of trigger Cognite Function to calculate metric B Daily execution of a workflow that triggers Cognite Function that recursively outputs a dynamic task, which calculates metric A. The Function outputs information for the next execution run (i.e., timestamp for next execution, state, and other info). At the end of the day the dynamic task would not output a timestamp for the next execution and workflow would complete. The execution trigger could also be daily.

Hello, When I tried to run the DBExtractor, I get the following error: “polars\_cpu_check.py:232: RuntimeWarning: Missing required CPU features.The following required CPU features were not detected:    avx, avx2, fmaContinuing to use this version of Polars on this processor will likely result in a crash.Install the `polars-lts-cpu` package instead of `polars` to run Polars with better compatibility.Hint: If you are on an Apple ARM machine (e.g. M1) this is likely due to running Python under Rosetta.It is recommended to install a native version of Python that does not run under Rosetta x86-64 emulation.If you believe this warning to be a false positive, you can set the `POLARS_SKIP_CPU_CHECK` environment variable to bypass this check.”After doing some googling, I was able to install the polars-lts-cpu package referenced using python, but I got the same error. I’m not sure how to make the extractor reference the polars-lts-cpu package when it runs. See attached screenshot.The extractor i