Learn how to effectively remove duplicate rows from your DataFrame in Apache Spark using the dropDuplicates() function. Master the art of data deduplication with our comprehensive guide.
Table of Contents
Question
Which of the following code blocks returns a new Data Frame from DataFrame storesDF with no duplicate rows?
A. storesDF.removeDuplicates()
B. storesDF.getDistinct()
C. storesDF.duplicates.drop()
D. storesDF.duplicates()
E. storesDF.dropDuplicates()
Answer
E. storesDF.dropDuplicates()
Explanation
In Apache Spark, the dropDuplicates() function is used to return a new DataFrame with duplicate rows removed. It considers all columns. If you want to specify some columns to determine uniqueness, you can pass the column names to the dropDuplicates() function.
Here is an example of how you can use it:
# Assuming storesDF is your DataFrame distinctDF = storesDF.dropDuplicates()
In this code, distinctDF will be a new DataFrame that consists of unique rows from storesDF.
Option A is incorrect because there is no removeDuplicates() function in DataFrame API. Option B is incorrect because getDistinct() is not a valid function. Option C and D are incorrect because duplicates() and duplicates.drop() are not valid functions in DataFrame API.
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