Bug Report - Unable to use INFO() DAX functions with ExecuteQueries REST API

[TMJForrester]

Per the following thread: Re: DAX Info Functions Against Published Datasets - Microsoft Fabric Community

It seems that we're unable to execute any of the INFO() DAX functions when using the ExecuteQueries REST API on a published semantic model. I have a few pipelines that require extracting metadata from the semantic model, and everything was working fine until this morning when I started getting an Analysis Services error code of "3239575574" (below is the full JSON of the error message).

{
"error": {
"code": "DatasetExecuteQueriesError",
"pbi.error": {
"code": "DatasetExecuteQueriesError",
"parameters": {},
"details": [
{
"code": "DetailsMessage",
"detail": {
"type": 1,
"value": "Failed to execute the DAX query."
}
},
{
"code": "AnalysisServicesErrorCode",
"detail": {
"type": 1,
"value": "3239575574"
}
}
]
}
}
}

[Sayantan]

I am facing the same kind of issue : using postman, i am doing - POST https://api.powerbi.com/v1.0/myorg/datasets/bc96b10d-8222-4630-8af3-37cefdf77a49/executeQueries Req body : { "queries" : [ { "query" : "EVALUATE INFO.TABLES();" } ] } in response : { "error": { "code": "DatasetExecuteQueriesError", "pbi.error": { "code": "DatasetExecuteQueriesError", "parameters": {}, "details": [ { "code": "DetailsMessage", "detail": { "type": 1, "value": "Failed to execute the DAX query." } }, { "code": "AnalysisServicesErrorCode", "detail": { "type": 1, "value": "3239575574" } } ] } } } what is the solution ?

[Dantezin]

Bumping this thread to receive updates on the status of this issue. Are there any other known ways of achieving this information in an automatic fashion?

[StevanLopes]

Hi guys. Any update about this topic?

[TheDataBrick]

@StevanLopes, @Dantezin, @Sayantan I have been able to automate the usage of INFO.* functions through a Fabric Notebook scheduled and run by a Fabric . Leveraging the Semantic-Link library I was able to post DAX queries to the different semantic models in the company tenant.

The piece of code is fairly simple:

import sempy.fabric as fabric

# Set variables

ws = workspace_name

ds = semantic_model_name

ds_table = 'data_source_table'

relative_path = 'root/path'

# Evaluate Dax

annotations = fabric.evaluate_dax(dataset=ds,workspace=ws,dax_string="""EVALUATE INFO.ANNOTATIONS()""")

measures = fabric.evaluate_dax(dataset=ds,workspace=ws,dax_string="""EVALUATE INFO.MEASURES()""")

# Save output as spark dataframes

spark_df_annot = spark.createDataFrame(annotations)

spark_df_meas = spark.createDataFrame(measures) #

# Save to ADLS as Parquet

spark_df_annot.write.mode("overwrite").parquet(f"{relative_path}/{ws}_{ds}_annotations")

spark_df_meas.write.mode("overwrite").parquet(f"{relative_path}/{ws}_{ds}_measures")

Unfortunately, this lib is only available through Fabric and not databricks, self-hosted jupyter notebooks nor ADF notebooks. Therefore, I had to use Fabric.