24 Questions
What method in PySpark can be used to convert the data type of a column?
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Which of the following is NOT a common aggregate function in PySpark?
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What is the purpose of join in PySpark?
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Which type of join in PySpark retains only the rows present in both tables being joined?
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How can you create a new column in a PySpark DataFrame by multiplying two existing columns?
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Which function is used in PySpark to perform conditional operations while adding a new column?
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Which of the following methods is used to display the first few rows of a PySpark DataFrame?
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How can you change a specific column's data type to integer in PySpark DataFrame?
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What function can be used to add a new column in a PySpark DataFrame based on a condition?
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Which of the following is NOT a valid method for loading data into PySpark?
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Which transformation in PySpark can be used to select specific columns from a DataFrame?
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What is the purpose of the groupBy() function in PySpark?
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Which function in PySpark can be used to remove duplicate rows from a DataFrame?
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Which of the following is NOT a valid operation that can be performed using the GroupBy function in PySpark?
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What is the purpose of the RDD (Resilient Distributed Dataset) in PySpark?
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What function in PySpark can be used to calculate the maximum value of a column in a DataFrame?
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When performing aggregations in PySpark, which function is NOT typically used?
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Which type of join in PySpark combines all rows from two tables, keeping NULL values for missing matches?
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In PySpark, which function is used to perform group-wise aggregation on a DataFrame?
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When joining two DataFrames in PySpark, what method is used to specify the columns on which the join should be performed?
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When running a query involving multiple tables in PySpark, what is the importance of explicitly stating column names in the SELECT statement?
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What is the purpose of the GROUP BY clause in PySpark SQL?
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In PySpark, which type of join retains all rows from both tables regardless of match and fills in missing values with nulls?
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When executing an SQL query in PySpark, why is it important to qualify the table name for columns that are being selected?
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