Transformations vs actions in Apache Spark - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a new RDD by doubling each number.

Apache Spark

rdd2 = rdd.[1](lambda x: x * 2)

Drag options to blanks, or click blank then click option'

Acount

Breduce

Ccollect

Dmap

Attempts:

3 left

💡 Hint

Common Mistakes

Using actions like collect or count instead of transformations.

The map transformation applies a function to each element and returns a new RDD.

2fill in blank

medium

Complete the code to get the total count of elements in the RDD.

Apache Spark

total = rdd.[1]()

Drag options to blanks, or click blank then click option'

Acount

Bmap

Cfilter

DflatMap

Attempts:

3 left

💡 Hint

Common Mistakes

Using transformations like map or filter instead of an action.

The count action returns the number of elements in the RDD and triggers computation.

3fill in blank

hard

Fix the error in the code to collect all elements as a list.

Apache Spark

elements = rdd.[1]()

Drag options to blanks, or click blank then click option'

Acollect

Breduce

Cmap

Dfilter

Attempts:

3 left

💡 Hint

Common Mistakes

Using transformations like map or filter which return RDDs, not lists.

The collect action returns all elements from the RDD to the driver as a list.

4fill in blank

hard

Fill both blanks to create a filtered RDD and count its elements.

Apache Spark

filtered = rdd.[1](lambda x: x > 10)
count = filtered.[2]()

Drag options to blanks, or click blank then click option'

Afilter

Bcount

Cmap

Dcollect

Attempts:

3 left

💡 Hint

Common Mistakes

Using map instead of filter, or collect instead of count.

filter creates a new RDD with elements matching the condition. count returns the number of elements and triggers computation.

5fill in blank

hard

Fill all three blanks to create a mapped RDD, filter it, and collect the results.

Apache Spark

mapped = rdd.[1](lambda x: x * 3)
filtered = mapped.[2](lambda x: x < 20)
result = filtered.[3]()

Drag options to blanks, or click blank then click option'

Amap

Bfilter

Ccollect

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up transformations and actions, or using count instead of collect.

map transforms each element, filter selects elements, and collect brings the results to the driver as a list.

Practice

1. Which of the following best describes a transformation in Apache Spark?

easy

A. It creates a new dataset from an existing one without running the job immediately.

B. It runs the job and returns the final result immediately.

C. It saves the dataset to an external storage system.

D. It deletes data from the dataset permanently.

Solution

1. Step 1: Understand what transformations do

   Transformations in Spark create a new dataset from an existing one but do not execute the job immediately.

2. Step 2: Differentiate from actions

   Actions trigger the execution and return results or save data, unlike transformations.

3. Final Answer:

   It creates a new dataset from an existing one without running the job immediately. -> Option A

4. Quick Check:

   Transformation = Lazy evaluation [OK]

Hint: Transformations are lazy; they don't run until an action triggers them [OK]

Common Mistakes:

• Confusing transformations with actions
• Thinking transformations execute immediately
• Believing transformations save or delete data

2. Which of the following is the correct syntax to perform an action that counts the number of elements in an RDD named data?

easy

A. data.map()

B. data.count()

C. data.filter()

D. data.transform()

Solution

1. Step 1: Identify the action to count elements

   The count() method is an action that returns the number of elements in an RDD.

2. Step 2: Check syntax correctness

   Calling data.count() correctly triggers the action and returns the count.

3. Final Answer:

   data.count() -> Option B

4. Quick Check:

   Action to count = data.count() [OK]

Hint: Actions like count() end with parentheses and return results [OK]

Common Mistakes:

• Using transformations like map() as actions
• Calling non-existent methods like transform()
• Forgetting parentheses on actions

3. Given the following Spark code, what will be the output?

rdd = sc.parallelize([1, 2, 3, 4])
mapped = rdd.map(lambda x: x * 2)
result = mapped.collect()

medium

A. An error because collect() is not an action

B. [1, 2, 3, 4]

C. [2, 4, 6, 8]

D. An empty list [] because map is lazy

Solution

1. Step 1: Understand the transformation

   The map transformation multiplies each element by 2 but does not run immediately.

2. Step 2: Understand the action

   The collect() action triggers execution and returns all elements as a list.

3. Final Answer:

   [2, 4, 6, 8] -> Option C

4. Quick Check:

   Transformation + collect() = output list [OK]

Hint: collect() runs the job and returns all data as a list [OK]

Common Mistakes:

• Thinking map() runs immediately
• Believing collect() returns nothing
• Confusing transformations with actions

4. Identify the error in the following Spark code snippet:

rdd = sc.parallelize([10, 20, 30])
filtered = rdd.filter(lambda x: x > 15)
filtered.count

medium

A. filter is not a valid transformation

B. Lambda function syntax is incorrect

C. parallelize is not defined

D. Missing parentheses after count action

Solution

1. Step 1: Check the use of count

   The count method is an action and requires parentheses to execute.

2. Step 2: Identify the error

   Missing parentheses means filtered.count is a method reference, not a call, so no action runs.

3. Final Answer:

   Missing parentheses after count action -> Option D

4. Quick Check:

   Actions need () to run [OK]

Hint: Always add () to call actions like count() [OK]

Common Mistakes:

• Forgetting parentheses on actions
• Thinking filter is an action
• Assuming parallelize is undefined without context

5. You want to find the sum of all even numbers in an RDD numbers. Which sequence of operations correctly uses transformations and actions?

hard

A. Use filter to select even numbers, then reduce to sum them.

B. Use reduce first, then filter to select even numbers.

C. Use map to sum numbers, then collect to filter evens.

D. Use collect first, then filter and reduce on the driver.

Solution

1. Step 1: Apply transformation to filter even numbers

   Use filter transformation to keep only even numbers in the RDD.

2. Step 2: Use action to sum filtered numbers

   Use reduce action to sum all filtered even numbers efficiently on the cluster.

3. Final Answer:

   Use filter to select even numbers, then reduce to sum them. -> Option A

4. Quick Check:

   Transformations then actions = correct Spark pattern [OK]

Hint: Filter first, then reduce to sum -- transformations before actions [OK]

Common Mistakes:

• Trying to reduce before filtering
• Using collect() too early causing driver overload
• Misusing map() for summing