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How can we get access to work hands-on with the learning path athttps://cognite-learn.fusion.cognite.com/cdf-fundamentals/data-models?cluster=api.cognitedata.com&workspace=data-management?If not, how can we practice hands-on with Cognite Learn?

Hello everyone,I observe a difference in behavior that I cannot explain.My input data, few datapoints, and before the value is 0, timeseries.is_step = TrueInput datapointsWith client.time_series.data.retrieve, behavior is as expected :And with every granularity results are okay as expected.Nevertheless, with client.time_series.data.synthetic.query it’s… different.that’s okthat’s okNot ok, why the result is not 2 groups : from 46 to 49 then 49 to 52 ? another wrong exampleWhy the start timestamp is 48 and not at 46 ? Again, the timeseries endoint is good : I have lost hope.If anyone has anything to try or an explanation, i’ll be grateful.Thanks in advance,Pierre 

 Hi everyone! 👋 Join us tomorrow to see the results of our "Hack for Impact" challenge. We are hosting Tridiagonal.ai (presented by ​@Dinesh Makked ) and SLB (presented by ​@Aditya Kotiyal) to present the winning concepts they developed for "Smart Operations" and "Cognite Vision."This is a fantastic opportunity for the community to: Celebrate the creativity and hard work of your fellow community members. See the specific approach these teams took to build their solutions. Hear the story behind the project directly from the creators. Hope to see you there! 🗓️ Thu, Jan 15 @ 3:00 PM CEST 👉 Register Here

Hi All,I have a large production records data set which i am utilizing to create reports using GraphQL queries.I want to perform DESC sort to fetch the latest records for which i am using default ‘StartTime’ property(This property is derived from Schedulable Container). But system is generating this warning : "The sort is not backed by a cursorable index, which means query time sorting is necessary, which in turn means a lot more data must be read. Consider whether a cursorable index is a good fit."What’s the best way to approach this so that i can fetch large data sets with improved performance?Should i make a custom DateTime field as cursorable ? What are the impact of this ?

Description / Problem StatementWe are using the Cognite 3D File Extractor to migrate 3D model files from an on-premises Windows VM to Cognite Data Fusion (CDF).The majority of 3D files are ingested successfully with multiple sizes mostly > 10 GB. However, four specific files consistently fail ingestion, even after multiple retries.Key observations:All failing files are close to 5 GB in size Example sizes (as shown in Windows Explorer): 4.99 GB 4.94 GB 4.91 GB When checked via terminal/command line, these same files report a larger actual size (~5.3 GB) It appears that based on the Windows VM file size, the 3D extractor determines it should use a single-part upload. However, when it attempts to upload the actual file, the process fails because the size exceeds 5 GB      

Hi community,I’m learning to use the /models/instances/query endpoint (with Open Industrial Data, public project) and experiencing some confusion about how cursors and pagination work.{    "with": {        "cities": {            "nodes": {                "filter": {                    "and": [                        {                            "exists": {                                "property": [                                    "Geography",                                    "City",                                    "name"                                ]                            }                        }                    ]                }            }        },        "continents": {            "nodes": {                "filter": {                    "and": [                        {                            "exists": {                                "property": [                                    "Geography",                                    "Continent",           

We’ve setup an MQTT Hosted Extractor that is recieving a SparkPlug B payload which some times contains a couple of null values, this values cannot be removed from the SparkPlug B payload. We believe that whenever the message contains null values the transformation for the datapoints fails.No more information is provided on the Transform Error, only the “Failed to transform data: Missing required field value”, could the null values just be ignored so the other values be inserted in the time series? We’re getting several empty time series that were created via the hosted extractor.

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I’m working with the PI AF Extractor and facing an issue with Table Lookup attributes.The Table Lookup attribute itself is being extracted correctly into the attributes table, but the value column always comes as “no data”, even though the attribute resolves normally inside PI System Explorer.I would like to know whether there is any supported way to extract the evaluated Table Lookup value using the PI AF Extractor, or if the extractor does not currently resolve Table Lookup references during extraction.Has anyone faced this issue or found a recommended approach to retrieve these values through the extractor?

Is there an alert or notification that can be configured when the MQTT hosted extractor is down? Been having issues with  Request to CDF failed with error Error in middleware: Failed to authenticate request  This error is resolved by creating a new sink, however we don’t get a notification of any kind when the extractor is down. 

I’m using the CogniteSDK. I have seen the following behavior several times: assets = client.assets.list()the variable assets can contain deleted assets if they have been recetly deleted. If I find the external_ids of these assets, the client.assets.retrieve_multiple(external_ids=deleted_xids) correcly do not return the assets. The assets cannot be found in fusion either. I suspect that client.assets.list() is using cached values. This also applies with arguments, f.ex LabelFilter. I have seen the issue many times, but now it really got painfull, so therefore I’m writing here. It returns assets that were deleted several days ago.  What to do? 

Hello, Although “unitless” is an alias of the dimensionless:unitless unit, try_get_unit(“unitless”) returns null.ref: https://github.com/cognitedata/units-catalog/blob/main/versions/v1/units.json#L1699 Could you please have a look? Thanks!

What capabilities are required to run a transformation using client credentials? I have a client_id and client_secret that when I add to the transformation and hit ‘Test credentials’ it says ‘Credentials verified’. However when I run with client credentials I get an error: Transformation job could not be created. Error code: 403 API error: Invalid source/destination credentials: Token did not provide access to project kuraray-america. Request ID: eb5136ee-594d-971f-b27a-7be0d1a60b15these credentials are a part of a group that that has read and write capabilities to:transformations sessions datamodelinstances (that is what this particular trasformation is creating)Additionally I am part of the same groups as this client_id, and I am able to run the transformation using ‘run as current user’ successfully

With the Java-SDK, I don’t see an option to supply the client-name during initialization of the client.  https://statics.teams.cdn.office.net/evergreen-assets/safelinks/2/atp-safelinks.htmlIs there anyway we can do that? We need the client-name for logging purpose. 

Hi everyone,I have a question: Can we use data from Data Models in Canvas?Is there any way to visualize that data available in Data models into Canvas?In our case, we are using Cognite Charts with time series data coming directly from machines (e.g., good parts, bad parts). However, the time series does not include product or batch information, which we do have in our Data Model.Is there any possibility to link both sets of information together for analysis?My initial thought is: if I can bring the required data from Data Models into Canvas and then create charts there, it would make the analysis much easier.But I’m not sure if this is possible—or if there’s another approach you would recommend.Any suggestions or best practices would be greatly appreciated!

Hi, I have defined a Data Model with a Source View having a DirectRelation to a Target View as a simplified version below, which Pygen created an SDK successfully.  But when I added a ReverseDirectRelationApply to the Target View, Pygen returned the captioned error.  Please help.source_container = ContainerApply(       space =”myspace”,       external_id=”sourceContainer”,       properties={            “sourceName”: ContainerProperty(type=Text, name=”sourceName”),            “target”: ContainerProperty(type=DirectRelation(is_list=False, container=ContainerId(space=”myspace”, external_id=”targetcontainer”) } target_container = ContainerApply(       space =”myspace”,       external_id=”targetContainer”,       properties={            “targetName”: ContainerProperty(type=Text, name=”targetName”)} source_view = ViewApply(     space = “myspace”,     external_id = “souceView”,     version = “1.0”,     properties = {           “sourceName”: MappedPropertyApply(container=ContainerId(“myspace”,

Hi,We are looking into contextualizing our data models with 3D info, based on the relevant concepts/types from the Cognite Core Model. However, we ran into a limitation that as far as we can see severely limits the usability of the functionality as is.The CogniteCADNode has a direct relation to a Cognite3DObject, that can be made up of multiple CogniteCADNodes, reflecting that an asset may correspond to multiple nodes in the 3D model. That makes sense. However since the link from CogniteCADNode to Cognite3DObject is a single direct relation, the current model does not allow a CogniteCADNode to be part of more than one Cognite3DObject, which typically is meant to correspond to an asset. That is unfortunately in direct contrast to reality. One CAD node belonging to many different assets/objects is not an edge case, rather, it is the norm, at least for Aker Solutions.Have we correctly understood the current functionality? If so, are there any plans to amend this limitation? Do you have a

Hi Everyone,Previously, I was able to bring my Cognite chart into Canvas, and it displayed correctly without showing the calculation area at the bottom. However, starting today, I can still add the chart to Canvas, but nothing appears—it’s completely blank. We tested this across multiple profiles, and the issue occurs for all of them. Is anyone else experiencing this problem? Could the Cognite team help us resolve it?Thanks in advance!

Hi everyone,As we prepare for the General Availability release of Records in CDF on December 2nd, 2025, we're implementing important changes based on learnings from the Private Beta program.Timeline: These changes will be rolled out progressively between today and December 2nd, 2025. We'll update this post as specific changes go live.What's changing:Record-specific containers We are introducing a new type of container dedicated to records, which has higher limits for number of properties, and will allow evolution of the records specific container as more features are made available in records. This container is defined by the usedFor field set to "record". It will be possible to ingest records only into containers with usedFor set to "record" Any records already ingested into non-record containers will remain queryable, but new ingestion attempts to these containers will fail This separation enables better schema management, clearer data organization, and simpler logic for clients q

Hi Everyone,Is there a way to create an alert directly on a calculated series in Cognite Charts?From what I’ve found, to create an alert for a calculation, I first need to schedule the calculation and then run the alert on that scheduled result. However, scheduling doesn’t seem to work well in my case.For example, if I receive machine data every hour, I also need to schedule the calculation every hour. Sometime scheduling stops by itself. It would be much easier if we could create alerts directly on the calculation without scheduling.Secondly, I’m not finding clear documentation or videos on how to schedule calculations properly and what best practices to follow. If anyone has experience with this or can share guidance, please let me know.Thanks!   

Hello, When I’m connecting to the virtual machine Ubuntu, I’m facing a pop-up “connection failed”. It seems that my internet connection is not set up, do you have any idea to do so ? I’m not able to do rest of the training without connection. Thanks 

In the process of initializing a new CDF tenant for one of our customers I am getting the following error when adding Assets Read/Write capabilities: 1 invalid capabilitie(s) are present: {"assetsAcl":{"actions":["READ","WRITE"],"scope":{"all":{}}}} (invalid capability - write access to the legacy Assets API is restricted) | code: 400 | Are core assets now restricted?

Hi Everyone!I need to manage streamlit applications (read / update files) using the Cognite SDK or with the API.I was able to publish streamlit applications using the cognite toolkit, but I also need to read them.Tried searching the api-docs and cognite-sdk docs with no luck. Thank you!

Hello, I have two questions:When using cdf_nodes in transformation, does query optimizer take advantage of the container indexes? What we notice is it is not the case.  How can we run broadcast joins in transformation. Hints does seem to be working: https://spark.apache.org/docs/latest/sql-ref-syntax-qry-select-hints.htmlThank you!

 I am facing issue of jupyter notebook getting crashed frequently. Sharing the image for reference.