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I believe we need bring infer_schema_length to db extractor parameter to improve it flexibility.If I understand correctly polars library was used in db extractor.According docs:infer_schema_length: int | None = 100,this means it defines data types by first 100 rows by default. This is not fit for our client data.Currently I extract data from csv and experienced with 2 issues. I think they are related to each other. As I understood: Extractor defined column data type based first n (probably 100) rows: could not parse `"1,616,178"` as dtype `f64` at column '*column_name*' (column number 10) This value on the line 3161 could not parse `"2.15"` as dtype `i64` at column '*column_name*' (column number 15) This value on the line 118 - all previous values equal “0”after error in terminal I see suggestion:You might want to try:- increasing `infer_schema_length` (e.g. `infer_schema_length=10000`),- specifying correct dtype with the `schema_overrides` argument- setting `ignore_errors` to `True`,- adding `"1,616,178"` to the `null_values` list.
I had an observation where after cancelling the CDF Data Workflow, the transformation it triggered were not stopped/terminated immediately.SCENARIO:- A Data Workflow is triggered.- Transformation step started.- Transformation failed in first run/attempt.- While second run starts (due to retry policy) click on Cancel Run in workflow interface.- Workflow successfully cancelled , but the triggered transformation keeps on running till it failed again.I was assuming the transformation would stop with the Data Workflow execution getting cancelled, but later realized the transformations kept running and eventually failed.
when contexualized engineering documents, some annotations added wrongly and it's innevitable.we want data tidying-up functions such as dragging and selecting multiple annotaions and delete at once, or deleting annotations by right-clicking. And more,we think deleting annotations available in edit screen would be better.Now, we have to select one by one, and click the right-upper botton(in a distance) 2times to delete single annotaion.
On the Checklist Lists, users currently after check a Checklist, needs to scroll up, click on the three dots and change the checklist to done. It should have a simple way to change with less click and more easier to the users.
I would like to set time range in grafana custom query using grafana variables. I see we can use:granularity='GRANULARITY', alignment=ALIGNMENT in query and wonder if there is any parameter for range?
Building upon the recent enhancements of waypoints and ghosting, the ability to walk a user to a location from their current location or a selected start point is a use case for our contractors during daily maintenance or Turnaround activities. Often contractors have never been onsite and navigation to the work area or a specific asset would be helpful. Think google maps walking feature or a line that connects scan points in the 3d model to guide the user to the location.
Here are some of the things I cannot do with the call logsSee all logs (only four pages) Filter based on status Filter based on schedule Filter based on time ranges Sort calls based on run times Automatically locate the “first failed” call (which is often relevant in debugging) See logs in monospaced font to preserve formatting (see other feature request) Get call logs into Power BI (I need to deploy a separate Cognite Function that fetches call logs and writes to a Sequence, which can then be loaded into Power BI for simple monitoring)At least we should be able to see all logs from our calls, with additional functionality to filter in relevant dimensions.
Hi Team!Right now graphql support for fetching FDM Data doesn't offer any filters for type "TimeSeries". Since Timeseries type usually has a lot of datapoints associated with it in any given model, fetching data through graphql api from it without any filter is extremely time consuming , especaially when you dont need all datapoints/timeseries from it. For example, right now when we want to fetch information only for non string timeseries, there is no way other than fetching all Timeseries associated and remove the ones that has "isString" property as false which slows down some parts of our appplication.So if we can get graphql filter support for timeseries type, we will be able to optimise things in our side.Thanks & Regards,Sangavi M
We should build an extractor that connects to an InfluxDB 2.x (most common) locally and will push up Time Series data much like it does with Pi.
We have some people who already have Tableau. Is it possible to use Tableau to visualize data from Cognite Data Fusion? If so, any guidance on setting up the connection?
Hello!We currently have a multi-tenant application (multiple companies data can be stored within same DB with a tenant Identifier to segment data). Our business performs services work for these companies, so we have internal employees that are granted access to several of these companies. We are in the process of migrating some of our functionality over to being backed by CDF. During this transition, we will have internal employees demoing to customers in both our product and the CDF UI. For Data Sets, we plan to externalId them prefixed with Company/Tenant Identifier combined with the data source, so that the externalId may be something like “abc-inc-app-that-does-stuff” where “abc-inc” would be the tenant identifier. When our internal employees are demoing results using both our product and CDF to Company A, the internal employee does not want other companies (Company B) data to be visible. In our app, a user with access to multiple companies is able to switch between Companies accommodate this, but I don’t know the best way to do this in CDF.I would like to be able to group data sets into a “Data Set Group” (or Company or Tenant if we want to be more specific/rigid about the meaning). Then I would like to be able to select a “Data Set Group” in CDF and have only Data Sets within that “Data Set Group” be visible when navigating between types of data. Initially, I thought I would be able to use different CDF Projects for this purpose, but according to Torgrim Aas we will need to store multiple Companies data within a single shared Production Project we are being provided with as a part of our partnership. This is why this feature request is critical for us to move forward. Thank you for your help.
Hi, When we do manual annotations we would the option to filter what we search for. For example in this search I am looking to the tag “21L3201” but I’m only interested in the one from the IAA facility. And when I am in a document from IAA I am only interested in IAA tags, searching through the SKA facility is just noise.In addition we have different representations of this tag in different datasets, the tag “IAA-21L3201” is technically a match but it is from a dataset that for this use case is nothing but noise.When we do manual annotations we know what space/dataset the tag is located in within CDF and we always know which physical facility it belongs to. Searching through all of CDF is a neat feature in theory, but in practice it is noise.There should be a way to filter on dataset/metadata to make it easier to find the tags/assets that are actually relevant. Regards,Markus PettersenAker BP - CDF Data Delivery - Tech Lead
Hi Team,Currently, when we make any changes to a data model from the UI, there is no change log that is shown to the user before publishing.Ideally, user should be shown the changes that are going to get commit before publishing a model from the UI so that they do not inadvertently make any mistakes.Change log would be something similar we are shown before git commit and push (like additions, deletions, etc)This will improve user experience for anyone using the data modeling service from the UI.Thanks@Aditya Kotiyal
Our TA and Projects team is evaluating the 3D tool inside Cognite to be the backbone of how work is planned. I would like to get a few enhancement requests that will be helpful to make the planning process in 3D value added. One is the ability to add and move around 3D objects to a scene so planners can understand what equipment is needed or if equipment can fit in a working area. Cranes, people, scaffolding, etc. Specifically for cranes, it would be valuable to add different sizes and ability to understand the reach of the crane so they can understand what work could be done without moving it. Can see how this might pair with capability already in Maintain to see workorder in 3D.
Hi team, We’d like to suggest an improvement for the Transformations feature.Currently, in Transformations, we only have access to staging tables and not to the instances of the data model that have already been created. This leads to some redundancy and inefficiencies in transformation logic. Use case:Let’s say I load Well objects in a first transformation, applying a set of filters (e.g., valid wells, correct country, etc.). Then, in a second transformation, I want to load Wellbore objects. However, to ensure consistency, I want to join with only the wells that were already loaded into the data model — not reapply the same filtering logic I used earlier.Currently, since I can’t access the already loaded Well instances in the data model, I have to duplicate the filtering logic or rely on external references, which is error-prone and inefficient. Suggestion:Allow read access to instances of the data model from within transformations, so we can:Reference already created objects (e.g., Well) directly when creating new ones (e.g., Wellbore). Avoid duplication of logic. Ensure better consistency across related business objects.Let me know if this is technically feasible or already planned.Thanks a lot!
Hello, We are defining description of every attribute of our data objects in cdf toolkit. However these does not show anywhere. We want to be able to see these description in the Industrial tools Search UI when we expend properties of an object.Could you transform this into a feature request please? Thanks
I have created this Feature Request to track the request raised here and to monitor its progress on behalf of the customers.IssueThe current limit of 100 in datapoint retrieveLatest API is causing performance issues when serving Angular dashboards due to multiple network calls.Solution proposedIncrease max number of time series returned in datapoint retrieveLatest API to 1000. Requester: priyanka.perera@cognite.comOrganization: Schlumberger
Hello, Today the CDF Snowflake extractor only support OAuth or User/password authentification schemas: https://docs.cognite.com/cdf/integration/guides/extraction/configuration/db/#-snowflakeWe would like to be able to authenticate using private key: https://docs.snowflake.com/en/user-guide/key-pair-authIs this part of your Snowflake extractor road map?Thank you
Currently the data models page shows all data models (system - added by default by Cognite and custom). Add a filtering capability to show only the models created by users.Currently, there is only a search button but having a filter out default data models will enhance user experience as data models by Cognite have increase by a large number.Thanks
When browsing data using the Data Catalog view there’s a “Governance Status” presented on datasets: We have Datasets created with users’ having write-access to be able to facilitate uploads from Canvas. What has been identified however is that these files become searchable in the Add Data view of Canvas. When searching for data, a mechanism to prevent searching un-governed datasets would overcome concerns of people potentially adding ungoverned data to perspectives that could lead to incorrect decision making.
Summary: Get aggregates, specifically the maximum and minimum value for a given timeframe of a time series, without needing to specify the granularity.Suppose I want to get the maximum value of a time series between time A and B and the difference between A and B is 3 hours. To achieve this, I would need to specify a granularity of, say, 120 seconds and then find the maximum of the returned data points again. This additional computation can be avoided if the API allowed the user to just specify the start and stop time and get the single maximum/minimum data point in the interval.
We are using Pygen to generate Python SDK for our Data Model. Pygen has given us good set of classes and methods which are really helpful. However, descriptions added in this generated SDK are very generic and not that useful. I think the only way to add descriptions and examples are manually doing changes to each classes and methods.We are planning to use Pygen to create SDK and may generate SDK multiple times based on data model versions. If we put our own descriptions and examples manually then each time new SDK will generated we will loose the descriptions and examples.Here, descriptions should be applied to all classes, methods, arguments etc.I believe there should be way to create SDK with relevant descriptions and examples.Please suggest what needs to be done.If no approach available then please consider it as a new product idea
Under the "Add Data" button in the Charts, the user suggest renaming the field from "Add timeseries" to "Add events or timeseries" to better reflect the available options.Additionally, in the Category dropdown, options like Assets, Files, Functional Locations, and Equipment should either be removed or grayed out, as these data types cannot be added to a chart. This will help reduce confusion and make the interface more intuitive for users. Requested by: mark_wrzyszczynski@oxy.com
Hi team,We would like to request a feature that enables unit conversion directly on Sequences, similar to what is available today for Time Series. Here’s a more detailed description of the idea:Each column in a Sequence would have an associated unit (e.g., 'psi', 'm', 'kg'). When querying a Sequence, the user can specify the unit they want for each column — if omitted, the original unit is returned. Alternatively, the user can define a default unit system (e.g., SI or field units), and Cognite would automatically convert all columns to match this system.Why this would be helpful:It reduces the burden on end users to manage unit conversions manually after retrieving data. It aligns with the behavior already available in Time Series, making the API more consistent and user-friendly across data types.Let me know if this is on the roadmap or if more details are needed.Thanks!
Hi team, We’d like to have a real-time mechanism to consume new row-level data from Sequences as soon as it's ingested.Use case:Sequences are often populated continuously (e.g., depth logs data), and we need to react with low delay to new rows. Right now, the only option is polling, which isn’t efficient. Suggestion:Introduce a Change Data Capture (CDC) or subscription mechanism at the row level for Sequences to:Detect new data as it arrives. Stream updates to external systems or trigger real-time logic.Thanks for considering this enhancement!
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