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@Mohammad Imran,Independent of support for previous in the graphQL response, could you keep a history of cursors in your client application? This way, you can page or direct navigate using the historical cursors.-Jason
@Peter Arwanitis fyi. I had a call with @Snehal-Jagtap this morning. She’s looking for an example using spaces and has a few other asks. I mentioned that you could assist faster than I can 😀.
@Viswanadha Sai Akhil Pujyam,What type of event are you wanting to launch a function on? In addition to scheduling, you can programatically launch Cognite Functions. That trigger can be in response to an ‘event’.Jason
@Basudeba Mandal ,I can help administer the clientId and secret you need to to access slb-pdf. I’ve reached out on Teams to verify and share with you the correct credentials.Jason
@Sangavi M,I have validated this is an issue and have raised a ticket to fix. I will let you know once remedied. Thank you for sharing. Jason
@Alex Narayanan,As mentioned, nothing out of the box is currently supported. I can imagine a solution using a configuration (CDF File or FDM), for a given set of well-known xls file templates. You can use cell references or named ranges. Your extractor would use the config to pull the data. For this to run on python, something like openpyxl, which would enable you to run as a Cognite function and enable the road to a reasonable reusable extractor Jason
@Neerajkumar Bhatewara Which model is this you are testing with? I presume slb-pdf is your project.
@Ankita Mane I try to highlight several ways you can use the python SDK to retrieve your large number of events. The SDK auto supports paging. If you hit the API directly, you will need to navigate the cursors yourself.Hope this helps,Jasonfrom cognite.client import CogniteClientimport timeclient: CogniteClient = ...# Serial retrievalstart = time.time()events = client.events.list(data_set_ids=[123], limit=None)end = time.time()print(f"Time {(end - start):.2f} seconds")# Parallel retrievalstart = time.time()events = client.events.list(data_set_ids=[123], limit=None, partitions=10)end = time.time()print(f"Partitioned Time {(end - start):.2f} seconds") # Serial chunk retrieval - keep a limited set in memorystart = time.time()for event in client.events(chunk_size=1000, data_set_ids=[123]): pass # Do your work.end = time.time()print(f"Partitioned Chunk Time {(end - start):.2f} seconds") # Parallel chunk retrievalstart = time.time()for event in client.events(chunk_size=1000, data_set_
@Sangavi M , This API has changed. https://docs.cognite.com/api/v1/#tag/Instances/operation/byExternalIdsInstances this is the most recent. Can you have a look and see if this issue still exists for you. If so, tag me and I can have a second look. Jason
@Mohit Shakaly I think we can close this. For now, the team does not require dotnet dll signing as they have identified a workaround. If they require this in the future, we can add it to the shared SLB:Cognite Azure DevOps requirements backlog.
@Sergei Sementchouk I’m not sure if this answers your question. If you want to list all edges in a space, your request to the models/instances/list endpoint could look like:{ "includeTyping": true, "instanceType": "edge", "filter": { "equals": { "property": [ "edge", "space" ], "value": "<ENTER SPACE NAME>" } }}This gets you all instances of edges in a space. If you know the space and id, you can use the model/instances/byids endpoint Jason
@Sangavi M ,Can you kindly provide your API requests and possibly share your model?
@Sonali Vishal Patil , This is related to another issue. Your project has reached the quota limit for number of instances. There is an outstanding support request to remedy. Regards,Jason
@Mohit Shakaly I believe the dlls are now signed. Correct?
Gargi, You may not have the correct permissions to query the projects. You will only see the projects you have permission to see :). Were you using a service principal or your own user principal to execute the query? The service principal will only see one project.Jason
This issue has been resolved.
@Vaibhav Narain TimeSeries datatype is yet to be fully supported. What teams are typically doing is created a surrogate “TimeSeriesRef” type as a placeholder for the time being. You would populate TimeSeriesRef instances with your CDF native time series instances and metadata properties.
@carriechung,I can provide a brief answer. Think of space as storage scoping. You can define your models in one space, but use another space to store instances. This way, you can have one model but use different spaces to partition your instances. Currently, to keep it simple, you can use the same space for data model and the instances. Jason
Xaiofeng, Can you confirm this is resolved?Jason
Snehal,A ticket has been created to address resolution of this issue. We will update you once resolved.Regards,Jason
Hello Niranjan,I created a working sample I hope helps. I created an FDM targeted transformation in Fusion (version as of the date I wrote this) and used the export CLI button in the upper right. This created the following manifest. I updated authentication section with the credentials that are required when the transformation itself is going to run. This auth# Manifest file downloaded from fusionexternalId: tr-BSEEWell-Header-Asset-FDM-cliname: BSEE Well Header Asset - FDM - CLIquery: >- select cast(`API_WELL_NUMBER` as STRING) as externalId, cast(`WELL_NAME` as STRING) as name, cast(`API_WELL_NUMBER` as STRING) as apiNumber from `bsee`.`well_header`;destination: view: space: space-well-model-simple externalId: Well version: "1" instanceSpace: space-well-model-simple type: nodesignoreNullFields: trueshared: trueaction: upsertdataSetExternalId: ds-bsee# this is authentication credentials for Fusion, not the transformation-cliauthentication: clientId: myc
Hello,I presume you have followed the directions here: https://docs.cognite.com/cdf/dashboards/guides/grafana/admin_oidcIf you want user level authentication delegation, your Azure Active Directory (AAD) Administrator will need to provide the appropriate approval. It will be the same person that provided you the Client Id and Client Secret for grafana setup.If you want to use Client Credentials, you can follow instructions here: https://docs.cognite.com/cdf/dashboards/guides/grafana/admin_oidc#set-up-a-client-credentials-grant-flow, but you will still need an client id and secret that has permissions to read from your CDF project. Hope this helps,Jason
Have a look at the sample I shared. The “Direct” relation is not established by creating an Edge. It’s established by setting the property on the Node { "instanceType": "node", "space": "XiaofengTest", "externalId": "externalId:simmodel1", "sources": [ { "source": { "type": "view", "space": "XiaofengTest", "externalId": "SimulationModel", "version": "1" }, "properties": { "modelName": "firstSimulationModelName", "modelId": "xxx-xxx-xxx-xxx-xxx"#DECLARE THE DIRECT RELATION "simulator": { "space": "XiaofengTest", "externalId": "externalId:simulator1"#### } } ] }
Xiaofeng,Looking at XiaofengTestDataModel, I don’t exactly know between which 2 types you are relating (creating edge for). There are 2 types of relations If your model looked something like:type SimulationModel { name: String! simulator: Simulator nodes: [Node]}type Simulator { name: String!}type Node { name: String!}You would need to create a Simulator instance first (I presume you have that). Let’s assume that the id of a Simulator node instance is “simulator-s”A SimulationModel Instance creation would look something like this: { "instanceType": "node", "existingVersion": 1, "space": "your-space", "externalId": "sim-model-id-x", "sources": [ { "source": { "type": "view", "space": "your-space", "externalId": "SimulationModel", "version": "1" }, "properties
Mohit,Can you kindly elaborate? The dotnet SDK is a community SDK. It, and the dotnet extractor utils, are leveraged in cognite dotnet based extractors OSI PI and OPC UA (as examples)Jason
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