👶 Apache Flink Interview Questions for Freshers
Here’s a list of common Flink interview questions for freshers, often asked when the candidate is new to stream processing or just starting with Flink.
🔹 Basic Flink Concepts
- What is Apache Flink?
- What are the main features of Flink?
- How is Flink different from Spark Streaming or Kafka Streams?
- What are stream processing and batch processing?
- What are some real-world use cases of Flink?
🔹 Programming & API Basics
- What is the DataStream API in Flink?
- What is the difference between the DataSet and DataStream API?
- How do you create a Flink job?
- How do you define a source and sink in Flink?
- Can you write a simple Flink job to filter even numbers from a stream?
🔹 Time & Event Handling
- What is event time vs processing time?
- What are watermarks in Flink?
- Why is event time processing important in real-time systems?
🔹 Windowing Basics
- What are windows in Flink?
- What’s the difference between tumbling and sliding windows?
- Give an example of a use case where windowing is useful.
🔹 Fault Tolerance (Basic Level)
- What is checkpointing in Flink?
- Why is state management important in stream processing?
- What is the difference between at-least-once and exactly-once semantics?
🔹 General Java & Integration Questions (If Needed)
- Which language did you use for writing Flink jobs—Java or Scala?
- How do you integrate Flink with Kafka (or any source)?
- Have you worked on any mini-projects using Flink? What was your role?
✅ Tips for Freshers:
- Be clear on stream processing fundamentals (e.g., unbounded data, windows, watermarks).
- Practice writing very simple Flink jobs using Java.
- If you’ve done a project—even a mini one—describe the flow clearly (source → process → sink).
- Even if you haven’t worked on Flink professionally, interviewers appreciate clarity and curiosity.