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Exam Certified Associate Developer for Apache Spark All Questions

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Exam Certified Associate Developer for Apache Spark topic 1 question 52 discussion

Which of the following operations can perform an outer join on two DataFrames?

  • A. DataFrame.crossJoin()
  • B. Standalone join() function
  • C. DataFrame.outerJoin()
  • D. DataFrame.join()
  • E. DataFrame.merge()
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Suggested Answer: D 🗳️

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Chosen Answer:
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cookiemonster42
Highly Voted 1 year, 4 months ago
Selected Answer: D
D. result_df = df1.join(df2, on="id", how="outer")
upvoted 5 times
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juliom6
Most Recent 1 year ago
Selected Answer: D
D is correct. There is no exists outerJoin() operation in pyspark.
upvoted 2 times
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4be8126
1 year, 6 months ago
Selected Answer: C
The correct answer is C - DataFrame.outerJoin(). The outer join operation can be performed by specifying the join type as "outer" when calling the outerJoin() function on a DataFrame. The join() function in Spark only performs an inner join, while the merge() function is not a valid function in Spark SQL. The crossJoin() function performs a Cartesian product between two DataFrames, which is not an outer join.
upvoted 1 times
65bd33e
7 months ago
Wrong answer, check documentation
upvoted 1 times
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ZSun
1 year, 5 months ago
There is no outerjoin, bro! only dataframe.join(how='outer')
upvoted 9 times
Seeker_thunder
1 year ago
this guy always post wrong answers, sometime gpts as well. ignore his commnmets
upvoted 1 times
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