Explanation:
Databricks notebooks facilitate the use of multiple programming languages, such as Scala and Python, in a single notebook. By employing magic commands (%scala for Scala and %python for Python), you can designate the language context for each cell. This approach enables versatile data processing workflows that capitalize on the distinct strengths of each language.
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How can you effectively combine Scala and Python code blocks for data processing within the same Databricks notebook?
A
Only Scala is compatible with the Spark engine, making it the sole option for notebooks.
B
Utilize the %scala magic command for Scala cells and %python for Python cells to specify the language context.
C
Convert all Scala code to Python prior to integration with Python cells to ensure compatibility.
D
Exclusively use Python for data processing tasks after defining all variables in Scala.