Why DataFrames are preferred over RDDs in Apache Spark - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a DataFrame from a list of tuples.

Apache Spark

df = spark.createDataFrame([1], ['name', 'age'])

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A[('Alice', 34), ('Bob', 45)]

B('Alice', 34, 'Bob', 45)

C['Alice', 34, 'Bob', 45]

D{'Alice': 34, 'Bob': 45}

Attempts:

3 left

💡 Hint

Common Mistakes

Using a dictionary instead of a list of tuples.

Passing a flat list instead of tuples.

The createDataFrame method expects a list of tuples representing rows.

2fill in blank

medium

Complete the code to select the 'age' column from the DataFrame.

Apache Spark

ages = df.select([1])

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A'name'

B'age'

Cage

Ddf.age

Attempts:

3 left

💡 Hint

Common Mistakes

Using the column variable without quotes.

Selecting the wrong column name.

To select a column by name, pass the column name as a string.

3fill in blank

hard

Fix the error in the code to filter rows where age is greater than 30.

Apache Spark

filtered = df.filter(df.age [1] 30)

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A<

B==

C=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' instead of '>' in filter.

Using '==' which may not work as expected in Spark filters.

Use the > operator to filter rows where age is greater than 30.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length if length is greater than 3.

Apache Spark

{word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself instead of its length.

Incorrect condition like word > 3.

The dictionary comprehension maps each word to its length, filtering words longer than 3 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their lengths if length is greater than 4.

Apache Spark

{ [1]: [2] for word in words if [3] }

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Aword.upper()

Blen(word)

Clen(word) > 4

Dword.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using word.lower() instead of upper.

Incorrect filter condition.

Swapping keys and values.

This comprehension creates a dictionary with uppercase words as keys and their lengths as values, filtering words longer than 4 characters.