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Hi Team, I am facing some issues while using the above pipeline.yaml  file setup which is suggeted by cdf team before, i am getting validation error, even after passing all mandatory fields.Could you please help me doing the devops setup so that i can understand the process.Please set up a call to work on this issue as it is impacting deliverables. Regards,Nidhi N G

I am trying to make a comparison between time series data from CDF and from Pi (accessed with the Seeq Python API). Some questions arise:​​​​​How do I ensure that the DateTimeIndex-s that are returned are identical? Why does CDF return DateTimeIndex with dates before my start value?Examples:Pulling a raw time series from Pi via Seeq looks like this:start = datetime(2021, 1, 1)end = datetime(2021, 1, 2)spy.pull(items, start=start, end=end, grid=None, quiet=True)And the CDF analog looks like this:start = datetime(2021, 1, 1)end = datetime(2021, 1, 2)cognite.datapoints.retrieve_dataframe( external_id=external_id, start=start, end=end, granularity=None)The resulting DateTimeIndex-es are not identical:From Pi via Seeq:DatetimeIndex(['2021-01-01 00:00:00+01:00', '2021-01-01 00:00:05+01:00', '2021-01-01 00:00:10+01:00', '2021-01-01 00:00:15+01:00', '2021-01-01 00:00:20+01:00', '2021-01-01 00:00:25+01:00', '2021-01-01 00:00:30+01:00', '2021

Hi Team, Please help with the current setup or process  of azure devops  to deploy Cognite (CDF) Function(API) to CDF project.

Require More attempts to clear Working with Cognite InField - Assessment

We are currently exploring workflow development on top of CDF python SDK. The client secret is used in the workflow code in order to connect with CDF project instance. This client secret is bound to expire after predefined interval. It will incur production downtime and manual intervention in order to update the secret.Can we have or do we have some concept similar to refresh tokens in CDF Python SDK.

Can we have function chaining feature in Cognite functions where on sucess/failure status of a function we initiate another function.

Hi Team, Could you please provide more attempts on above assessment.

During my training session at Working With CDF: Integrate » Time Series » Working with the IFSDB file I noticed that even though I pointed the Dataset to “FirstNameYearBirth-IFSDB” the data was associated with the other Dataset. The Avevasomething.. how come is that possible? Can someone help me understand what have happened? The transformation showing the correct Dataset.The Data Catalog showing that the time series and events went to the wrong data set. 

Learn Cognite API in java script SDK.

Hi all,what's the best way to write a condition in the transformation query, that checks for presence of certain key in asset metadata?Example asset metadata:"KEY": "VALUE"pseudocode:select * from _cdf.assets A where ‘KEY’ in A.metadata.keys I’ve been provided with following solutiion by Cognite support, with a note to ask here. Is there a better/other solution?select * from _cdf.assets where metadata['KEY'] is not null;

Hi, I see this error in extractor log, I hope even if this happens , it will be retried and there will not be the data loss. Please correct if I am wrong or if there are ways to change any configuration in extractor to avoid this.  2023-03-07 05:42:04.233 UTC [WARNING ] QueryExecutor_3 - Too many concurrent requests in pod | code: 503

It seems I can create an edge with any type. In the code example below, the externalId of the “type” is set to “xxx” when calling POST Add edges, which should not exist. However, the edge was added successfully. Furthermore, I could not see any edges were created in the SimulationModel table, even the “externalId” was set to “SimulatonModelSimulator”.  { "instanceType": "edge", "space": "XiaofengTest", "externalId": "externalId:edge1", "type": { "space": "XiaofengTest", "externalId": "xxx" }, "startNode": { "space": "XiaofengTest", "externalId": "externalId:simulator1" }, "endNode": { "space": "XiaofengTest", "externalId": "externalId:simmodel1" } } 

I’m trying to transform some time-series data (manufacturing pump pressures) into Asset Hierarchy/Numeric Data.The SQL is not writing to the timestamp column and not seeing errors in Preview.I’ve tried MANY different SQL commands to convert the DateTimeStamp string column to timestamp column/datatype and none have worked. CSV files are attached if anyone wants to try it. Added query in attachments. Help is greatly appreciated! Transform setup: Here is some of my data being edited in Excel and saved as CSV then imported into CDF Raw. TagID Tagname Value DateTimeStamp FCE1-HYD-PMP-3 FCE1-HYD-PMP-3 NULL 3/2/2023 3:41 FCE1-HYD-PMP-3 FCE1-HYD-PMP-3 28.54443 3/2/2023 5:51 FCE1-HYD-PMP-3 FCE1-HYD-PMP-3 35.68053 3/2/2023 5:51 FCE1-HYD-PMP-3 FCE1-HYD-PMP-3 42.81664 3/2/2023 5:51 FCE1-HYD-PMP-3 FCE1-HYD-PMP-3 49.95274 3/2/2023 5:51  RAW     

Course - CDF Enablement Bootcamp PreparationLink -Firewall check (cognite.com)Giving Not accessible to connections Attached the screenshot for reference.

I have cloned the following in my local DEV folder.using-cognite-python-sdk.gitI have also installed the dependencies that are defined in the pyproject.toml in the repo.To run the code in jupyter notebooks. (Note: Change the "Kernel" to use the virtual environment created by poetry.) and add new libraries as needed. How do I change the Kernel in jupyter notebook to the one created by poetry? When I open the jupyter notebook from the repo folder, it shows the general python3 (ipykernel) but this was present even before I installed poetry. So how do I change the kernel in my notebook. Please advise. 

It seems the link to download the demo data is not working in https://docs.cognite.com/cdf/data_modeling/upload_raw_dm. Once clicked the “the demo data” link, got an error message “This site can’t be reached”. Seems the dropbox link is broken. https://www.dropbox.com/s/o5o9eaewb9j57kt/FDM_Movie_data.zip?dl=1 Could you help have a check?

As part of bootcamp-prework training, pre-configured ubuntu VM, We are unable to download pre-configured Ubuntu VM image zip file (it is around 10GB) and it got stuck-up. training link : https://learn.cognite.com/bootcamp-pre-work/1441023

I have a transformation that is to write to a new dataset as seen here:SELECTconcat('CWS:',loc) as externalId,IF(parent_loc='' OR parent_loc IS NULL, '', concat('CWS:',parent_loc)) AS parentExternalId,CAST(lastUpdatedTime AS STRING) AS name,to_metadata(*) AS metadata,description AS description,7089382776719091 AS dataSetId FROM `CWS-Assets-DB`.`CWS-Assets-Tbl` The Preview seems to work fine.When RUN: I get following error:Request with id 96f4a082-9dde-9b41-8065-0b3cf0923197 to https://az-eastus-1.cognitedata.com/api/v1/projects/ra-istc-sandbox/assets/byids failed with status 403: Resource not found. This may also be due to insufficient access rights..The permissions on the dataset for my user group is raw:readraw:writeraw:listdatamodels:readdatamodels:writedatamodelinstances:readdatamodelinstances:writedatasets:readdatasets:writedatasets:ownertimeseries:readtimeseries:writefiles:readfiles:writeevents:readevents:writesequences:readsequences:write3d:read3d:create3d:update3d:deletetransfo

Tried to create an Asset Hierarchy transformation and waited for over 5 minutes. It did not work. Tried twice. This is an urgent matter for me to complete this training.  Help is appreciated!  

If  publishing a datamodel with TimeSeries attributes defined(like below)in the UI, it will fail with an error message:type Property {  modelName: String  value: TimeSeries} 

I am able to login with clientID and client Secret to our test project using cdf cli. Also the “cdf dm create” is working. However, when publishing a graphql using “cdf dm publish” there was always a validation error even using the demo GraphQL data model. Below is the error message:$ cdf dm publish --file=./test.graphql --external-id="testgraphql1" --space="testgraphql1" --version 1 --verbose2023-02-28T13:24:31.576Z cdf:middleware:auth Fetching auth token from CDF...2023-02-28T13:24:31.577Z cdf Getting token via Client Secret2023-02-28T13:24:31.578Z cdf:auth:client-secret Starting to aquire client credential token2023-02-28T13:24:32.032Z cdf:middleware:auth Finished fetching auth token from CDF2023-02-28T13:24:32.038Z cdf:data-models:publish dataModelVersionsHandler initialized2023-02-28T13:24:32.038Z cdf:data-models:publish Reading graphql file ./test.graphql2023-02-28T13:24:32.039Z cdf:data-models:publish Schema contents 'type Actor {\r\n' + '  name: String!\r\n' + '  age: Int\r\n'

In Charts, we have been using the “Shift Time Series” function (for creating a new Calculation time series) to assess data more effectively, but have now noticed a limitation where the calculation is limited to the data from the source time series already displayed.  If you look at the first image below (just a 10-min shift), you can see in the green calculation that there is a gap on the left where the calculation doesn’t exist due to the source data being “off the page”.  If we go to a more extreme scenario (2nd image below), now of the data shows since we are attempting a 2+ day shift in a time series.  Is there a solution where this limitation can be removed?  For our scenario specifically, we are looking closely at (and comparing) three separate incidents that lasted about 1 minute each, but were spread out over the course of a week, so we are super zoomed in to look at the behavior signatures.  Thanks for the input!Kind regards,Richard10-minute shift​​​​​ Multiple-day shift 

I have asset hierarchy table and time series table imported, but I want to link asset to timeseries or vice-versa. asset hierarchy table looks like:level 1, level 2.e1, entity 1;level 1, level 2.e1, entity 2;level 1, level 2.e2, entity 3;time series table looks like:t1, entity 1, x1, y1t2, entity 1, x2, y2when I click asset entity 1 in Explore view, it shows time series data count but the name and description of the time series are empty; when click time series, the count of linked Assets is 0. I do not know how to fix the issue.  

I am taking the course called Cognite Data Fusion Fundamentals. At the module called ‘Work With CDF: Integrate’ I could not find the raw files for events,  time series nor Data points. Wierd because I found the raw ones for assets and 3D Models. Could someone helpe me please? Am I missing something? Have I skiped any other mandatory module? Thanks. Marcio.

I might need to create 100,000s - 1,000,000 of individual timeseries. I would like to understand if the number of timeseries impacts the API performance. e.g. retrieving data points for 1 of the timeseries. Would the API response be similar if I had 100 or 1 million timeseries?Also is there a maximum number of timeseries that can be created per CDF project?