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Answer: Utilizing the REST API to export job and cluster metrics for analysis with custom Python scripts
Option B is the most suitable approach for diagnosing cluster performance degradation with custom metrics in this scenario. By leveraging the REST API provided by Databricks, you can export job and cluster metrics for in-depth analysis using custom Python scripts. This method enables you to collect specific data related to job configurations and data patterns that might be contributing to the performance degradation. Exporting metrics via the REST API allows for a customized analysis, focusing on the interactions between job configurations and specific data patterns suspected of causing the issue. This level of customization surpasses what's possible with Databricks' built-in cluster metrics alone. Moreover, employing custom Python scripts for analysis offers the flexibility to manipulate the data in a manner most relevant to your specific situation, including creating custom visualizations, performing advanced statistical analysis, and correlating different metrics to pinpoint the root cause of the performance degradation. In summary, using the REST API to export job and cluster metrics for analysis with custom Python scripts presents a more comprehensive and tailored solution for diagnosing cluster performance degradation with custom metrics in this context.
Author: LeetQuiz Editorial Team
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When your Databricks cluster shows unexpected performance degradation, and you suspect it's due to a complex interaction between job configurations and specific data patterns, what is the best method to diagnose this issue using custom metrics and logs?
A
Implementing a logging framework in your jobs that pushes custom metrics to Azure Log Analytics for advanced querying
B
Utilizing the REST API to export job and cluster metrics for analysis with custom Python scripts
C
Directly querying the Spark event logs stored in DBFS (Databricks File System) for custom job execution patterns
D
Relying solely on Databricks' built-in cluster metrics for troubleshooting without custom enhancements
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