Spark: Key Topics for Data Engineering Interviews Part - 1

Key Topics for Data Engineering Interviews

Introduction

Spark has become the de facto standard for big data processing, and acing an Apache Spark interview requires a solid understanding of its core concepts.

In this blog series, I will dive deep into the most frequently asked Spark interview questions, complete with practical use cases, efficiency comparisons, and syntax examples.

Lets get started —

1️⃣ Repartition vs. Coalesce

Repartition:

• Functionality: Increases or decreases the number of partitions by reshuffling the data.
• When to Use: When you need even distribution across partitions.
• Syntax: rdd = rdd.repartition(10)

Coalesce:

• Functionality: Reduces the number of partitions without full shuffle.
• When to Use: When reducing partitions with minimal shuffle.
• Syntax: rdd = rdd.coalesce(2)

2️⃣ SortBy vs. OrderBy

SortBy:

• Functionality: Sorts data within each partition…