Explanation:
The question asks for a 15% sample without replacement. In PySpark, the sample method is used with withReplacement defaulting to False if not specified. Option E uses sample(fraction=0.15), which correctly sets the fraction to 15% and uses the default False for replacement. Other options either use incorrect fractions (A, C), use sampleBy which is for stratified sampling (B), or have missing parameters (D).
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Which of the following code blocks returns a 15% sample of rows from the DataFrame storesDF without replacement?
A
storesDF.sample(fraction = 0.10)
B
storesDF.sampleBy(fraction = 0.15)
C
storesDF.sample(True, fraction = 0.10)
D
storesDF.sample()
E
storesDF.sample(fraction = 0.15)
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