Hadoop vs Spark comparison - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to print the main difference between Hadoop and Spark.

Hadoop

print("Hadoop processes data using [1] computing.")

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

Astreaming

Breal-time

Cbatch

Dinteractive

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'streaming' because Spark supports streaming, but Hadoop mainly uses batch.

Confusing real-time with batch processing.

Hadoop processes data mainly using batch computing, which means it handles large data sets in chunks.

2fill in blank

medium

Complete the code to show which framework is faster for iterative tasks.

Hadoop

print("Spark is generally [1] than Hadoop for iterative algorithms.")

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

Afaster

Bslower

Cequal

Dless efficient

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'slower' because Hadoop is older.

Confusing speed with efficiency.

Spark is faster than Hadoop for iterative tasks because it keeps data in memory.

3fill in blank

hard

Fix the error in the code to correctly compare data processing models.

Hadoop

model = "Spark uses [1] processing, Hadoop uses batch processing."

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

Abatch

Bstreaming

Creal-time

Doffline

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'batch' which is Hadoop's model, not Spark's.

Confusing 'real-time' with 'streaming' in this context.

Spark supports streaming processing, which allows real-time data handling, unlike Hadoop's batch model.

4fill in blank

hard

Fill both blanks to create a dictionary comparing Hadoop and Spark features.

Hadoop

comparison = {"Hadoop": "[1] processing", "Spark": "[2] processing"}

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

Abatch

Bstreaming

Cinteractive

Doffline

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up batch and streaming between Hadoop and Spark.

Using 'interactive' which is not the main model for either.

Hadoop uses batch processing, while Spark supports streaming processing for real-time data.

5fill in blank

hard

Fill all three blanks to create a summary dictionary with key features.

Hadoop

summary = {"Speed": "[1]", "Data Model": "[2]", "Memory Usage": "[3]"}

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

ASpark is faster

BHadoop uses MapReduce

CSpark uses in-memory

DHadoop uses in-memory

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing which framework uses in-memory processing.

Mixing up data models between Hadoop and Spark.

Spark is faster due to in-memory computing, Hadoop uses MapReduce as its data model and does not use in-memory processing.