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DATABRICKS-CERTIFIED-ASSOCIATE-DEVELOPER-FOR-APACHE-SPARK · Question #55

Which of the following operations can be used to return a DataFrame with no duplicate rows? Please select the most complete answer.

The correct answer is E. DataFrame.dropDuplicates(), DataFrame.distinct() and DataFrame.drop_duplicates(). In PySpark, there are three equivalent ways to remove duplicate rows from a DataFrame: (1) DataFrame.distinct() - returns a new DataFrame with duplicate rows removed; (2) DataFrame.dropDuplicates() - removes duplicate rows, optionally scoped to a subset of columns; (3)…

Perform DataFrame transformations

Question

Which of the following operations can be used to return a DataFrame with no duplicate rows? Please select the most complete answer.

Options

  • ADataFrame.distinct()
  • BDataFrame.dropDuplicates() and DataFrame.distinct()
  • CDataFrame.dropDuplicates()
  • DDataFrame.drop_duplicates()
  • EDataFrame.dropDuplicates(), DataFrame.distinct() and DataFrame.drop_duplicates()

How the community answered

(22 responses)
  • A
    5% (1)
  • C
    9% (2)
  • E
    86% (19)

Explanation

In PySpark, there are three equivalent ways to remove duplicate rows from a DataFrame: (1) DataFrame.distinct() - returns a new DataFrame with duplicate rows removed; (2) DataFrame.dropDuplicates() - removes duplicate rows, optionally scoped to a subset of columns; (3) DataFrame.drop_duplicates() - a Python-style alias for dropDuplicates() that behaves identically. Since all three methods can be used to return a DataFrame with no duplicate rows, option E is the most complete and correct answer.

Topics

#DataFrame API#Duplicate Data#PySpark#Data Cleaning

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