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How can I execute two or more different queries extracting the data from the source and inserting the data in the same CDF RAW table?Currently only the last query available in the config.yaml file gets executed. 

Do Cognite OData APIs also offer have cursor implementation like cursor capabilities on REST endpoints?

Hi! I would like to check if a time series stays within a region for more than a certain amount of time. Is this possible? This would be the equivalent of inverting the “Upper lower threshold” function. Also I would need a time limit for that. Perhaps it would be a simple yet powerful addition to the existing functionality: To be able to invert the monitoring task? Some of the monitoring tasks have a time aspect, and some do not.. perhaps all should have it?  Regards  

Has anyone configured the extractor to use Visual Studio Code? I need a step by step guide.

Is it possible to configure in Cognite tools (like CDF & Cognite Infield) to send an email with the information on the user (to designate admin(s)), when a user trying to access the tools is restricted access to those tools, for not being part of the right security groups? Question posted on behalf of Celanese user access administrator.

We are fetching quite a lot of data from CDF, both raw and aggregated, and we have experienced error messages from Postman and Java requests when the aggregated number of datapoints are exceeding the limit (10.000), but we have yet to experience this for the Cognite Python SDK for raw data (limit 100.000). Is there an error message implemented for this intention? From the code in the SDK in GitHub it appears that if the data is exceeding the limit then it would return an empty list, which is a very dangerous return setting. Best regardsOliver

It has been observed that while transforming data from CDF datapoints table, if the datapoint has a timestamp value with year below or equal 1970, the timestamp value is shown as null. How do we deal with this issue?

I am attempting to run the python file associated with the Data Modeling hands-on lab (https://colab.research.google.com/drive/11NdrGUzFhbwsOlKqXVfYRqu9s1DzAw4b?usp=sharing). I am receiving the same error every time the ‘plot’ function is called: “TypeError: Cannot interpret '<attribute 'dtype' of 'numpy.generic' objects>' as a data type”. After some debugging, the data seems to be in a dataframe data type. I suspect there is some version discrepancy between numpy and pandas, has anyone else seen this error? Thank you, Adam

Once we have created the Timeseries, is it possible to change the isString value to be True?

Hi, In my endeavor to make a percentwise threshold in Charts: I.e. how many percent of the last week was a time series above a certain value, I stumbled on what I think is a bug.I need to divide the time the timeseries is above a threshold by the total duration of the time window. I therefore tried the “constant value”-function, and set it to one. The default granularity is then at 7 days. I can change the granularity to 1 day as in the screenshot below:  However, when I change the granularity below this. Eg. 1 hour, I get the following warning: Ideally I want it to 1m or something like that, so that I have sufficient granularity to measure percentage above threshold over  the course of a day.Any suggestions as to how I can fix this, or an alternative way to reach my goal?Thank you

Hands on with Data Science > Data Processing and Exploratory Data Analysis > Google Colab notebook called Data processing and analysis for IDA course.ipynb has issues in the Setup code block.  Here is partial output log:...Installing collected packages: PyJWT, protobuf, cryptography, msal, cognite-sdk Attempting uninstall: protobuf Found existing installation: protobuf 3.19.6 Uninstalling protobuf-3.19.6: Successfully uninstalled protobuf-3.19.6 ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. tensorflow 2.9.2 requires protobuf<3.20,>=3.9.2, but you have protobuf 4.21.12 which is incompatible. tensorflow-metadata 1.12.0 requires protobuf<4,>=3.13, but you have protobuf 4.21.12 which is incompatible. tensorboard 2.9.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 4.21.12 which is incompatible. Successfully installed PyJWT-2.6.0 cog

Hello @Kristoffer Knudsen @ibrahim.alsyed  would like to know if Cognite InField would work ok for demo purposes on a giant smartphone (android  55’’)Celanese is planning to demo this to 100 people using something like this https://www.giantitab.com/ cc: @MortenNesvik @Kriti Dhaubhadel @Philippe Bettler @piya dey @Ajo 

We may have many clients with small userbase. What is the suggested deployment model for these clients from below options:As all the CDF projects are isolated, should we as a single Cognite tenant create different projects for different clients. We should provision separate Cognite tenant for each client keeping future creation of multiple CDF projects over time. 

As a Cognite tenant we can have multiple CDF projects. Some CDF projects may have large user base in comparison to others. Do we need to worry about Cognite WebAPI request handling capacity.

Can we get usage cost per CDF project.

Is there any difference between Cognite WebAPI vs Cognite Python SDK in terms of response time and data transfer limit.

In bootcamp documentation there were some guiding principles:https://docs-bootcamp.app.cogniteapp.com/content/chapter_0/#the-ice-cream-factory-dataOne of them was for Cognite functions:Cognite Functions for running and scheduling simple and short workloads in Python (< 10 min. execution time)Can we use Cognite functions for long running and scheduling workloads typically of duration 10-12 hours.  

Do we have option available to deploy CDF on private cloud.

I was trying to complete learning exercise in contextualization. I’m nit able to find dataset ‘saurabh1985-IFSDB’ created by me in initial exercise. Please check image below. Can you please help me with issue ? thanks,Saurabh Lale 

@Eric Stein-Beldring - is there a way to lock the y-axis when you have a chart in stacked mode? We have a good example that our team has been using where we’ve created a calculated column that we need to zoom in on to see the short term trends, but the moment we move the mouse over the chart the y-axis automatically re-adjusts not allowing us to use the stacked feature. If we could toggle y-axis auto adjustment, that would be very valuable!Not zoomed burgundy line vsZoomed burgundy line 

Would like to know in detail about the fact extraction from drilling reports. Is there any capability in CDF to do such fact extraction and relevant methods to process drilling reports?

We are interested in retrieving data from cdf through the odata service. We would do this not from Power BI, but from another Power Platform component, namely Dataverse. (the purpose would be to create "virtual tables" there which we could query, and in that way we could control access to the data more granularly then we are able to thorough the Cognite API) The documentation we find only mentions the OData connector in relation to Power BI (e.g. Cognite Power BI connector | Cognite documentation (cogniteapp.com) and Tips and best practices | Cognite Documentation). Is Cognite's OData service specifically tailored for Power BI, or is it a full implementation according to the OData standard? Is anyone able to recommend for or against attempting the proposed approach?In case the service implements the standard, does anyone know which version of the standard is it?

Hello,I have a Python project that uses publicdata project of Open Industrial Data. I am trying to refactor the authentication step to use Python-SDK with OAuth since the API keys are (being) deprecated.To do so, I need the parameters token_url, client_id, client_secret, scopes.I am setting the parameters as such:cognite_tenant_id = "48d5043c-cf70-4c49-881c-c638f5796997"token_url=f"https://login.microsoftonline.com/{cognite_tenant_id}/oauth2/v2.0/authorize"client_id=???client_secret=<client secret generated from Open Industrial Data https://hub.cognite.com/open-industrial-data-211>scopes=["https://api.cognitedata.com/user_impersonation"]I would like to know if we can use the already defined Cognite tenant in AAD with Tenant Id “48d5043c-cf70-4c49-881c-c638f5796997” ? Are you providing the client id for that then? Similar to the ones publicly provided for Postman and JS-SDK? Please also note that I cannot use interactive login since it is not a one-off script.Moreover, I cannot re

I have ingested RAW data into CDF for a bunch of equipment (16) and also applied transformations on those to setup Assets, Timeseries, Datapoints and Events. I have a P&ID diagram (PDF) which has 4 Equipments shown in the Diagram with P&ID#. I would like to know the process of ingesting this file as a resource type for this equipment setup and where do I upload the file?  When the user selects any of the above Equipment in CDF, the system should display the enclosed P&ID diagram.

Data set is not available in the below path for the practice, kindly request your support to resolve this ASAP.   Regards,Naveen