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CERTIFIED-DATA-ENGINEER-PROFESSIONAL · Question #49

CERTIFIED-DATA-ENGINEER-PROFESSIONAL Question #49: Real Exam Question with Answer & Explanation

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Optimizing Spark Applications

Question

A user new to Databricks is trying to troubleshoot long execution times for some pipeline logic they are working on. Presently, the user is executing code cell-by-cell, using display() calls to confirm code is producing the logically correct results as new transformations are added to an operation. To get a measure of average time to execute, the user is running each cell multiple times interactively. Which of the following adjustments will get a more accurate measure of how code is likely to perform in production?

Options

  • AScala is the only language that can be accurately tested using interactive notebooks; because the
  • BThe only way to meaningfully troubleshoot code execution times in development notebooks Is to
  • CProduction code development should only be done using an IDE; executing code against a local
  • DCalling display () forces a job to trigger, while many transformations will only add to the logical
  • EThe Jobs Ul should be leveraged to occasionally run the notebook as a job and track execution

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Topics

#Spark Lazy Evaluation#Databricks Notebooks#Performance Tuning#Spark Actions
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