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I have provided the essential credentials within the config.yml file in the OpcUaExtractor config folder, however when run it get this error. How can I fix this?

Hello Team,I am working on creating POC on PROSPER Connector I checked documentation of Cognite Prosper Connector. Connector is provided by Cognite, but where can I get simulator for POC purpose?Also in connector configuration, where to provide simulator details or simulator name?  

If there are large number of instances in a view, wont that load in the fusion UI? Can’t this be fixed with trimming with some max limit and still display?  

Hi team, I’m working on OPC UA Extractor. I have configured metadata-targets and configured metadata-mapping.I’m not able to see the metadata along with timeseries data.Please find the configuration in attachment and screen shot in CDF how timeseries data looks like. please let me know if any additional configurations need to be done to see the metadata along with timeseries data. 

Hello, is it possible to test the  CogniteAuthError using monkeypatch context manager  ?Regards ,Hakim Arezki 

Does CDF support the direct ingestion of timeseries with non-numeric values ( enums).  If the workaround is to convert enums to integers to ingest, this is unnecessary overhead and a limitation. Also have to remember to convert the values back for visualization. 

I want to create a new time series in CDF based on a calculation on another time series. This can be done by saving the calculation in a schedule. But I would like to run a calculation on the full input signal (which may span multiple years back in time), but it seems like the scheduling limit is 30 days (can anyone verify?). Is it possible to run a single calculation in Charts (spanning the entire period) and save the result to a Time Series object without going by a schedule? Or do I need to use the Python SDK for this purpose?Thanks in advance!Vetle.

I am trying to create a time series subscription and  receiving the error below:"Must have access to WRITE time series subscription.My question is, if the subscription is a listener, why does it need WRITE access?  

Ensuring the security of PI credentials is critical in the Cognite PI extractor.In the context of Azure Vault, the requirement involves implementing robust measures to safeguard PI access credentials. This entails storing sensitive information, such as usernames and passwords, securely in Azure Vault. The system should be configured to read these credentials from the vault when needed, providing a secure and centralized method for managing and accessing PI authentication details. This approach enhances overall data security by minimizing the exposure of sensitive information and adhering to best practices for credential management in cloud environments. we have implemented in other custom extractors. can you share the documentation to implement in Cognite PI extractor

I'm trying to use a graphql query in my python notebook. And I'm using this code snippet given in the sdk docs. from cognite.client import CogniteClient>>> c = CogniteClient()>>> res = c.data_modeling.graphql.query(... id=("mySpace", "myDataModel", "v1"),... query="listThings { items { thingProperty } }",... ) I dont see data_modeling.graphql.query() method available. I see the below error message. AttributeError: 'DataModelingGraphQLAPI' object has no attribute 'query' I'm using sdk version 7.5.1. How do I run my grapghql query?

Are the calculations provided in Charts (originating from `indsl` python library) available for all CDF projects? I’m wondering if it’s possible to contribute with new calculations to Charts that are written in `indsl` but only deployed to the specific CDF project you’re working on (i.e., not accessible for people outside this project)?I want to write new calculations using indsl that SMEs in my team can use in Charts for specific time series analysis, but I think it would be best to keep them isolated within our CDF project to not “overflow” the global Charts with potentially lots of new calculations that may mostly be relevant for my team/company.Any response is appreciated, thanks :)

In Charts you can import your own calculations, but I can’t find any documentation regarding requirements to this end. It seems like the required format is a JSON file, but how should this JSON be set up. If anyone has any examples of imported calculations, sharing them would be very much appreciated.Thank you.

I am trying to configure an OpcUA extractor to push a NodeSet2.xml file to CDF. I have it basically setup and if I run it, there are no obvious errors, but I don’t see any kinds of assets being imported.  Am I expecting too much? Is the functionality in place to import an OpcUA Nodeset as Assets into my CDF project. If anyone has this working I would really appreciate a copy of the config file you are usingThanksAdrian

Hi! We’re aiming to monitor all of our CDF operations in the solution we have for monitoring other systems and data flows (Splunk). This would involve monitoring of extractors/extraction pipelines, cognite functions, and general platform availability. I wonder if any other Cognite customers have done this, and if you would be willing to share your experience / architecture for extracting logs from cognite functions etc. into Splunk or a similar service? Cheers,Kristian 

I am trying to create a synthetic time series query that looks are two other time series and if those values meet a certain condition, is outputs a 1 or 0 as the synthetic time series but I keep getting a syntax error that I can’t solve. Below is a code sample. temp_id_list = [3308928194658464]flow_id_list = [1256034258207391, 3564715377369546]for temperature in temp_id_list:    temp_expression = f"TS{{id:{temperature}}} < 200"    flow_expression = " + ".join([f"(TS{{id:{flowrate}}})" for flowrate in flow_id_list])    final_expression = f"if({temp_expression} and {flow_expression} > 0, 1, 0)"    cv_query = client.time_series.data.synthetic.query(expressions=final_expression, start="1d-ago", end="now")

I am trying to read timeseries data from CDF on my local but facing SSL Error also showing cognite.client.exceptions.CogniteConnectionError.[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate in certificate chain (_ssl.c:997)  

I’m getting results from several topics using the # function at the end of my topic path-tree.e.g. ‘~/Installations/Location/Vessel/Seapath/#’where ‘~/Installations/Location/Vessel/Seapath/acceleration_x’ is an example pathThe problem now is that: when I get “context.topic” I get the full path (~/Installations/Location/Vessel/Seapath/acceleration_x) instead of the last path (acceleration_x) and I can’t seem to find a way to extract only the last path as there is barely any functionality in Functions | Cognite Documentation.Is there a way to get past this?sample data: {"timestamp":1700740159863,"values":[-0.013358482159674168]}here is my transformation:{  "externalId": concat("installation.vessel.seapath.", context.topic_last_part), # where I can e.g. do split, substring, slice, regexp_extract or any string manipulation on context.topic  "timestamp": input.timestamp,  "value": input.values[0],  "type": "datapoint"}sample output;{    "externalId": "installation.vessel.seapath.acceleratio

Hi,From my MQTT topic I receive sensor data as a timestamp and 25 values, where each value should gets transformed as a datapoint for its own timeseries. However, there is a limit on 2000 char for the transformation code AND a constraint that does not allow you to set up duplicate streams on the same topic: meaning you can only do one transformation per topic, but this function is limited to 2000 chars. I run into a problem now where, for this sample data:“{"timestamp":1701093489556,"values":[-0.035999998450279236,-0.10400000214576721,-0.09099999815225601,-0.08299999684095383,-0.09399999678134918,-0.10999999940395355,-0.10700000077486038,-0.10499999672174454,-0.11299999803304672,-0.12099999934434891,-0.13899999856948853,-0.1340000033378601,-0.14399999380111694,-0.1340000033378601,-0.15000000596046448,-0.15000000596046448,-0.17000000178813934,-0.16699999570846558,-0.15399999916553497,-0.16500000655651093,-0.15000000596046448,-0.10199999809265137,-0.11100000143051147,-0.1469999998807907,

Hello,In DB Extractor, I see a parameter that could be configured to specify how to treat the timezone parameter.  Is there something similar for OPC-UA Extractor as well ?If not how can the different timezone data could be handled or atleast Local timezone data ?

While testing the hosted MQTT extractor and the pre-release front end I have noted a couple of things you might be interested in, but I’m also guessing some of these are quite obvious to you and already in the pipeline. Front end should support creating a new destination with specified dataset. Viewing and editing a stream transformation without deleting and creating a new one would be nice. A way of listing existing transformation mappings and create or draft new ones without setting up an extractor instance for it would be helpful. Transform error-messages might not point at correct line and character in the message it returns. I don't have an example of this right now, I will post one if I see it again. Transformation Mappings entity could have a description-attribute that lets users describe the scenario it is written created for. The endpoint listed in beta docs for creating destinations did not work, I ended up using the same endpoint as the front-end where "hostedextractors" is

Within custom transformations, is there a way of updating ongoing events in cases where the MQTT messages does not contain an UUID or enough information to build an event-externalId?In the example messages below I would ideally like to create an event based off the first message, and then update it when the second message is received. Is it possible to do so without an UUID that is contained within both messages? Events start message:{    "alarm": {        "data": {            "Name": "logic_cond",            "Source": "logic",        },        "id": "logic",        "message": "TOOL UNCLAMPED",        "state": "active",        "timestamp": "2023-11-08T14:16:41.626645Z"    },    "source": {        "applicationType": "mtc",        "clientID": "asset5",        "ownerID": ""    }}Event end message:{    "alarm": {        "data": {            "Name": "logic_cond",            "Source": "logic",        },        "id": "logic",        "message": "TOOL UNCLAMPED",        "state": "dismissed",  

Trying to download the openapi spec over at https://api-docs.cognite.com/20230101/ by using the URL in the “download” link fails with 404 when trying to use the URL with wget/curl and “ADD” in a dockerfile. It seems like the link is generated behind the scenes during pageload by javascript. Is there a way to download the openapi spec in scripts e.g for use in CI pipelines and similar?

Hi Team,Is there any sample code available for retrieving a list of instance objects from FDM? I've reviewed the documentation's sample code, but I need additional clarification on where to provide Space, Object Type, Version, and Data Model.  Sample code available for Instance List. instance_list = c.data_modeling.instances.list(limit=5) I have also followed the steps outlined in the document URL below.. advancedListInstance queryContent searchInstances Thanks,Karguvel K

Hello, I am going through Cognite Data Fusion Fundamentals and am having an issue that I cant figure out. After multiple attempts I am loading 1 row of data to try and figure out my issue.I make it to the “Preview the Transformation” step:  The next step is to “Run the Transformation” step and this is where I am running into an issue. I get the below error message and theres no suggestion on what to do to correct my apparent error. Any idea what to do or how to progress? I just want to finish this course. -George

Hi I have an application to read data from and I have two options either to use ODBC or OPC UA directlyWhat are the benchmarks or limitations when it comes to aboveI have 30,000 data points to read with sample time of 1s and 5s and 10s