Join the discussions focusing on developing on top of Cognite Data Fusion. Click the + CREATE TOPIC button in the menu bar to start the conversation.
Recently active
Hello, We have around ~10/15 CDF functions. We deploy these functions via cdfToolkit.We notice that deployment of new version of a function takes around ~10min in order for it to be fully available. In the worst case where we modify a common module used by all function, redeploying of all functions can reach ~30-40mins. During this time these functions are not available and results in a failure in the dependent high frequency workflows. We wonder if there is a way to accelerate deployment of new function versions. Thank you!
Hello experts,I’m looking to work with data workflows.I’m looking to trigger on node with a specific attribute (direct relation to another view) empty.I’m trying to work with the UI but I struggle with the Data modeling query validation.I don’t understand why the validation fails and what is the expected format for the query : JSON seems to be the expected format as seen here : But documentation uses YAML : https://docs.cognite.com/cdf/dm/dm_concepts/dm_querying#graph-query-examplesI’m a bit lost and I need your help. And my query : { "with":[ { "ts":{ "nodes":{ "filter":{ "exists":{ "property":[ "nameTranslations" ] } } }, "limit":1000 } } ], "select":[ { "ts":{ "sources":[ { "source":{ "type":"view", "sp
Hi experts, In order to decide whether to use an aggregation strategy (or no aggregation at all), I need to know the number of data points between two timestamps without aggregation (server-side calculation). I’m looking for this code of call :client.time_series.data.count(external_id=<str>, start=<int | datetime>, end=<int | datetime>) -> intI'm trying to avoid having to perform a granularity calculation Thanks !Regards,Pierre
HiI am looking into using the toolkit more actively for deploying resources to CDF. One question that was raised when researching how to use the toolkit is what kind of validations actually happens when doing a dry run for deploying data modeling resources. I do not really have any specific issue I want answered, but rather want to learn more about the tool so prepare for a lot of questions from my notes:)Does it test that the configuration of views and containers work together?Does a successful dry run mean that I can be sure that the deployment will always work?Are there anything I need to consider even after getting a successful dry run?What kind of responses do I get if the dry run finds that something is wrong? Do I get any hints about how to fix an issue?Does it consider what is already deployed into the CDF environment?Will it tell me about any issues that can happen with new breaking changes? Appreciate all kinds of insights and experiences around this topic :)Sebastian
Hello,I am working with the Cognite Data Modeling API to validate edges in a large data set. Our edges do not have a dedicated "edge view" defined in the model. When I attempt to use the instances.query() API to fetch edges filtered by their type, I encounter errors or unexpected behavior indicating that selected properties do not match the view schema.Specifically, filtering or selecting on properties such as "externalId" fails because the queried view does not explicitly contain those properties, as the edges exist only as instances without a separate view.Is there a recommended approach or best practice for querying and validating edges in scenarios where no dedicated edge view is defined? Should we rely exclusively on the instances.list() API with filters, or is there a way to construct valid queries for edges in the current model setup?Any guidance on how to effectively query and validate edges in such cases, especially for large-scale data, would be appreciated.Thank you!
Hello, We are facing an issue using private SSL certificate with Cognite REST extractor, we are receiving this error: While executing request to <URL>: HTTP response error: 400 Bad Request. Body: <html> <head><title>400 No required SSL certificate was sent</title></head> <body> <center><h1>400 Bad Request</h1></center> <center>No required SSL certificate was sent</center> It seems that the extractor does not send the certificate, could you please help? Thanks!
Hi,Context:We currently organize our data in CDF using a per-country partitioning strategy, where each country has its own space.This approach was chosen primarily to restrict data access by country in a fine-grained manner.On top of that, we expose data models grouped by Business Object, such as Well Architecture, Cost Model, etc.Each Business Object model aggregates several data objects under a common business theme, which also allows us to control access by business domain in addition to country-based access.We are now planning to integrate a large amount of historical data, which will likely increase our model size by around 4x.These historical datasets are rarely queried, but we want to make sure their addition does not degrade performance for operational data — both in query latency and data ingestion throughput.We are evaluating two potential strategies: Keep everything in the same spaces, adding an indexed attribute (e.g., is_legacy = true) to distinguish legacy records. Crea
Hi, Data models names are limited to 37 chars today. Is this a hard limit? Is there a way to extend this so we can have more possibilities for internal naming conventions? Thank you!
I am starting the Cognite Data Engineer Learning Path. How to get the access to Cognite Data Fusion platform to practice the learning.
Hi Team, we have data in format like list of externalIds and space as key and value. Like list of Json object in data model. something like [{externalId:well,space:slb},{externalId:well1,space:slb2}]So can we keep a field in model like violatedEntities: [JsonObject]Is it possible to parse all the externalIds and store it like this?Thank you.
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!
When creating a Cognite Function you specify the dataset it belongs to, as an example lets say D2 LCI, then the files of the function is stored as files in that dataset. However, as D2 LCI is a dataset for file storage for engineering documents these function files cause noise, not much but still. If you were to list out all files for the dataset these “internal” CDF files would simply show as regular files and would have to be filtered out.Now, as we (AkerBP) are moving away from the asset-centric and over to data modelling this might not be an issue given how data models and spaces are. But in the future when datasets are a thing of the past, how will function and the like work, where will those files be stored. Storing the file used for compute with the data they compute might be a simple implementation, but not ideal as it does cause some noise. Note: this does not only apply to Cognite Functions, but to all CDF features where “internal” files are stored alongside the regular data.
I’m trying to update the is_string value of Time Series from false to true using CDF python class ognite.client.data_classes.time_series.TimeSeriesUpdate. But I’m unable to update it. The value in CDF remains false even though I updated it. Is this an expected behavior of Time Series Update?
Hi Team,Our observation while storing duplicate entries in Cognite Streams:Mutable Streams - It discards the duplicate entries consistently.Immutable Streams - It sometimes allow exact duplicate entries (externalId and other fields) and sometimes it doesn’t.Even when we checked in the Cognite AI, it says it usually doesn’t allow duplicate entries but in some rare scenarios, it allows.Could you please let us know the behavior. If it allows in rare scenarios, please let us know the exact scenarios.Thanks,Rahul
I am new to extending CogniteCore data model to further extend. How to Import CogniteCore datamodel to further extend in a new datamodel space.
Hello,I am testing streams and records in one of our projects, but I am getting “The user does not have any ILA streams capabilities.” error.I am also not able to add the capabilities for Streams and Records to my user group as I cannot see them in the capability type list
We’re using the client.documents.previews.download_page_as_png_bytes() function in the Python SDK to retrieve png previews of P&IDs in order to display them in a webapp (Streamlit).For some P&IDs, the dimensions of the returned png are distorted. The image is in the correct orientation but squashed to fit within a portrait envelope. The affected P&IDs are displayed correctly in both CDF Data Management and when downloaded and opened in a pdf viewer.Has anyone had this issue before and, if so, did you find a way to handle it?
Hello, We recently migrating the way of deployment of Streamlit App in our cdf toolkit project. Before we used to deploy our streamlit app by creating a file in a dedicated dataset. Now we use out of box way of deploying Streamlit Apps provided by cdf toolkit (this was not available before). When changing to this way, we notice that the app is only deployed using “--include streamlit” option.i.e: when not using the “--include streamlit” cdf toolkit the deploy summary is the following: however, we notice it is a previous version that has been deployed! when using “--include streamlit”: summary is the following And the App latest version is deployed as expected. Toolkit Version used is '0.6.20'. Are we missing something? Could you please take a look at this? Thanks!
This might be a basic question, but I often find myself uncertain about when to use CogniteDescribable in data modeling within Cognite Data Fusion.For example, let's say we have domain tables in our data model, such as MaterialType, which contains data from SAP and defines the types of materials we work with (e.g., code and description). In this case, would it be appropriate to implement CogniteDescribable to reuse common properties like name and description?What are the advantages of doing so? Does using CogniteDescribable provide any specific benefits—such as improved performance through indexing or partitioning—when used it containers?In summary, should I always use CogniteDescribable in these types of scenarios, or are there cases where it's better not to?
I am facing issue of jupyter notebook getting crashed frequently. Sharing the image for reference.
When we’ve tried to update to python sdk v8 we get a 400 validation issue when we try to create a container.We’re currently using v7.92.0, where we have no problems. We’ve tested versions v8.0.7 and v8.2.0.client.config.api_subversion is ‘20230101’ for both 7.92.0 and 8.2.0.Here is an example of a request that fails with: Unexpected field - items[0].properties..constraintState.constraintState seems to be a new property for v8 of the api.ContainerApply( space="Space", external_id="Comp", name="Comp", used_for="node", properties={ "manufacturer_name": ContainerProperty( type=Text(), nullable=True, ) })I notice also that the CDF Jupyter notebook in browser is still on v7.92.0. Is there potentially any other issues preventing an upgrade to v8? Best RegardsDaniel Rasmussen
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 ?
I need some help with the SDK (Python). I'm trying to list active sessions in Cognite using the following resource: client.iam.sessions.list(status="ACTIVE" However, I notice that even my client_id doesn't return in the listing (I'm logged in via browser with my user). Am I misunderstanding this feature?
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 want to take export of one table to another table but facing this datatype error .also tried with multiple datatype (like string , float and Bigint ) still same issue is coming.
Check the
documentation
Ask the
Community
Take a look
at
Academy
Cognite
Status
Page
Contact
Cognite Support
