Spark Interview Questions

71 real Spark questions asked in live technical interviews — each with a model answer. Updated weekly.

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What is Spark architecture and how does it work?🟡 Medium · Conceptual · Asked 95×How do you optimize slow running query?🟢 Easy · Asked 46×What do you know about Spark architecture, and how does it work?🟡 Medium · Conceptual · Asked 42×You're tasked with building a real‑time data pipeline using Apache Kafka and Apache Spark. The pipeline needs to process 1 million events per second and write the results to a data warehouse. How would you design the pipeline and what technologies would you use?🔴 Hard · System Design · Asked 2×You're tasked with designing a distributed data processing system using Apache Spark and Apache Kafka that can process 10 million events per second and write the results to a data warehouse. How would you design the system and what technologies would you use?🔴 Hard · System Design · Asked 2×Why do we need Spark for very complex data processing tasks?🟡 Medium · Conceptual · Asked 1×Why would I use a UDF?🟢 Easy · Conceptual · Asked 1×How would you use a Spark window function with row_number() partitioned by customer and ordered by timestamp descending to get the latest order per customer?🟡 Medium · Coding · Asked 1×Explain the architecture of Apache Spark and discuss common optimizations. Where would you write logic for a new project and why do we prioritize solving first?🟡 Medium · Conceptual · Asked 1×Why are wide transformations costly?🟡 Medium · Conceptual · Asked 1×What is the difference between narrow and wide transformations?🟢 Easy · Conceptual · Asked 1×What would you do if your Spark job fails at 50% completion?🟡 Medium · Debugging · Asked 1×What happens if a Spark job fails at 50% completion?🟡 Medium · Conceptual · Asked 1×How do you optimize Spark jobs?🟡 Medium · Conceptual · Asked 1×Let's see if you think like a senior data engineer. His Spark job takes 20 minutes every day. Today it took two hours. What's the first thing you will check?🟡 Medium · Debugging · Asked 1×Let's see if you think like a senior data engineer. His Spark job takes 20 minutes every day. Today it took two hours. What is the first thing you will check? If you answer 'was', I will see the code.🟡 Medium · Debugging · Asked 1×What will happen if your Spark job fails after 50% completion?🟡 Medium · Conceptual · Asked 1×Are you aware of aggregations? Have you used aggregations in Spark?🟡 Medium · Conceptual · Asked 1×What queries are needed to create a Spark session?🟢 Easy · Conceptual · Asked 1×How can you identify duplicate records in a dataset and determine which records are duplicated many times?🟡 Medium · Conceptual · Asked 1×Write a Spark query to process the following data.🟡 Medium · Coding · Asked 1×Are you aware of any Spark optimization techniques that have been used in projects?🟡 Medium · Conceptual · Asked 1×Can coalesce increase the number of partitions?🟢 Easy · Conceptual · Asked 1×Is coalesce the same as repartition? What is the difference between them?🟢 Easy · Conceptual · Asked 1×Can you explain the architecture of Spark?🟡 Medium · Conceptual · Asked 1×What is the difference between repartition and coalesce in Spark, and when would you use each?🟡 Medium · Conceptual · Asked 1×Explain how repartitioning works in Spark and when it is used.🟡 Medium · Conceptual · Asked 1×In a Spark‑based pipeline built with PySpark, there are multiple compute options available. Which compute option would you prefer and why? Also, how would you parameterize the pipeline?🟡 Medium · Conceptual · Asked 1×How would you optimize Spark jobs?🟡 Medium · Conceptual · Asked 1×What is the difference between repartition and coalesce?🟡 Medium · Conceptual · Asked 1×What is the difference between RDD, DataFrame, and Dataset?🟡 Medium · Conceptual · Asked 1×Do you have experience in PySpark?🟢 Easy · Behavioral · Asked 1×Given employee ID, name, department, salary, and location, process the data in Spark and handle invalid records.🟡 Medium · Coding · Asked 1×Let's say you have used re-partition and it has increased shuffling, but it's not helping. How would you handle it?🟡 Medium · Debugging · Asked 1×What is the difference between cache and persist in Spark?🟢 Easy · Conceptual · Asked 1×How can you avoid repeating all transformations when using both cache and persist?🟡 Medium · Conceptual · Asked 1×In a scenario where you perform eight to nine transformations on data, write the result to a CSV file, then apply one or two more transformations before writing to a downstream table, how would you structure your Spark job to avoid unnecessary recomputation?🟡 Medium · Conceptual · Asked 1×In a scenario where you ingest 100 to 100 GB of data from a source and call the collect function, what is wrong with this approach and what is the correct process?🟡 Medium · Conceptual · Asked 1×Given a DataFrame with columns ID and email, generate two additional columns: first name and last name, using the email column. For example, the left side of the dot is the first name, and the right side is the last name.🟡 Medium · Coding · Asked 1×What are the different Spark optimization techniques?🟡 Medium · Conceptual · Asked 1×How would you handle data skew in Spark when performing a broadcast join?🟡 Medium · Debugging · Asked 1×How can you resolve data skewing issues in Spark when performing joins?🟡 Medium · Conceptual · Asked 1×Can you tell how to optimize Spark jobs for streaming data?🟡 Medium · Conceptual · Asked 1×How would you test an application, such as a Spark or Python application, for a project?🟡 Medium · Conceptual · Asked 1×How would you optimize a job that processes large data sets and is experiencing high shuffle and low compute?🟡 Medium · Conceptual · Asked 1×Our today's topic is the Catalyst Optimizer. It is one of the well‑known concepts in Spark and is commonly asked in interviews. Can you explain the role of the Catalyst Optimizer in Spark's architecture?🟡 Medium · Conceptual · Asked 1×Did you manually connect a Spark job to an S3 bucket?🟡 Medium · Conceptual · Asked 1×Apart from Spark, do you know of other AWS services you have to use?🟢 Easy · Conceptual · Asked 1×Have you heard about broadcast join?🟡 Medium · Conceptual · Asked 1×What is the difference between repartition and coalesce queries?🟡 Medium · Conceptual · Asked 1×Which AWS platform is used to run and transform Spark jobs, and what parameters are required to trigger a Spark transformation?🟡 Medium · Conceptual · Asked 1×Write code to perform a broadcast join between sales data and stores data.🟡 Medium · Coding · Asked 1×Explain the difference between an executor and a driver in Apache Spark.🟡 Medium · Conceptual · Asked 1×What is a broadcast join?🟢 Easy · Conceptual · Asked 1×What is a stage in Spark?🟢 Easy · Conceptual · Asked 1×Can you tell what the Catalyst optimizer in Spark is?🟡 Medium · Conceptual · Asked 1×Are you proficient in Spark fundamentals?🟡 Medium · Behavioral · Asked 1×Why does coalesce not perform a full shuffle?🟢 Easy · Conceptual · Asked 1×What is the runtime for Spark?🟢 Easy · Conceptual · Asked 1×Why is Spark faster than normal Python computations?🟡 Medium · Conceptual · Asked 1×Can we run automatic operations in Python? Why don't we do that? Why use Path? Even distributed tasks can be done using Python, so why use Path at all?🟡 Medium · Conceptual · Asked 1×Why do we need to use Spark? Why can't we directly perform computations using Python itself?🟡 Medium · Conceptual · Asked 1×Why use Spark in a distributed cluster?🟡 Medium · Conceptual · Asked 1×Are there any other topics you would like to explore? We have covered Kafka, Spark, and some others.🟢 Easy · Other · Asked 1×In Spark, if you mistakenly set the number of partitions to 15 instead of 5, what would the output look like when running the command in the Spark terminal?🟡 Medium · Conceptual · Asked 1×An application processes a large dataset. One optimization technique is to use partitioning to reduce the number of partitions from 10 to fewer. What partitioning strategy would you use and why?🟡 Medium · Conceptual · Asked 1×In Spark, there is something called partition and repartition. Can you explain the difference between them?🟡 Medium · Conceptual · Asked 1×What will happen if a Spark job fails at 50% completion?🟡 Medium · Conceptual · Asked 1×How do you optimize Apache Spark jobs?🟡 Medium · Conceptual · Asked 1×Suppose you are creating ETL pipelines that perform incremental loads. You have access to an S3 bucket where files are placed at regular intervals. How would you design the pipeline so that it automatically triggers on the latest file without performing a full load?🟡 Medium · Conceptual · Asked 1×How can you compute a cumulative sum (running balance) ordered by date using an unbounded preceding window specification in a Spark DataFrame?🟡 Medium · Conceptual · Asked 1×

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