You have an Azure subscription that contains an Azure Synapse Analytics workspace named Workspace1, a Log Analytics workspace named Workspace2, and an Azure Data Lake Storage Gen2 container named Container1. Workspace1 contains an Apache Spark job named Job1 that writes data to Container1. Workspace1 sends diagnostics to Workspace2. From Synapse Studio, you submit Job1. What should you use to review the LogQuery output of the job?

Question

Accepted Answer

D. the Apache Spark applications option on the Monitor tab The Apache Spark applications option on the Monitor tab in Synapse Studio aggregates job logs, driver/executor output, and diagnostics in one place, making it the correct surface for reviewing LogQuery output of a job submitted interactively from Synapse Studio.

Answer

A. the files in the result subfolder of Container1 Container1 result subfolders store job output data written by the application, not diagnostic log streams or LogQuery telemetry.

Answer

B. the Spark monitoring URL returned after Job1 is submitted The Spark monitoring URL provides cluster-level Spark UI metrics such as DAG stages and task timings, but does not surface LogQuery diagnostic output sent to Log Analytics.

Answer

C. a table in Workspace2 While Workspace2 (Log Analytics) receives diagnostics from Workspace1, querying a Log Analytics table requires opening the Log Analytics workspace separately and writing KQL queries, and is not the intended path for reviewing output directly after submitting a job from Synapse Studio.

You have an Azure subscription that contains an Azure Synapse Analytics workspace named Workspace1, a Log Analytics workspace named Workspace2, and an Azure Data Lake Storage Gen2 container named Cont

Question

Options

How the community answered

Why each option

Topics

Community Discussion