DP-600 · Question #13
You have a Fabric tenant that contains a machine learning model registered in a Fabric workspace. You need to use the model to generate predictions by using the PREDICT function in a Fabric…
The correct answer is C. Spark SQL D. PySpark. In Microsoft Fabric notebooks, ML model scoring via the PREDICT function is supported through SynapseML and MLflow integrations in two languages: Spark SQL (C), which allows SQL-style syntax such as SELECT PREDICT(model, *) FROM table, and PySpark (D), which allows Python…
Question
You have a Fabric tenant that contains a machine learning model registered in a Fabric workspace. You need to use the model to generate predictions by using the PREDICT function in a Fabric notebook. Which two languages can you use to perform model scoring? Each correct answer presents a complete solution. NOTE: Each correct answer is worth one point.
Options
- AT-SQL
- BDAX
- CSpark SQL
- DPySpark
How the community answered
(37 responses)- A19% (7)
- B11% (4)
- C70% (26)
Explanation
In Microsoft Fabric notebooks, ML model scoring via the PREDICT function is supported through SynapseML and MLflow integrations in two languages: Spark SQL (C), which allows SQL-style syntax such as SELECT PREDICT(model, *) FROM table, and PySpark (D), which allows Python DataFrame-based invocation of the model. Both run on the Spark engine and can reference models registered in the Fabric workspace. T-SQL (A) is used in Fabric warehouses and does not support the notebook-based PREDICT function. DAX (B) is a query/calculation language for semantic models and has no ML prediction capability.
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