Pyspark Interview Questions

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

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A PySpark ETL on EMR must minimize cost volatility while handling variable daily loads. What EMR setup is a strong default?🟡 Medium · Conceptual · Asked 2×What specific techniques do you use while optimizing a price pump job?🟡 Medium · Conceptual · Asked 1×How do you optimize a PySpark job?🟡 Medium · Conceptual · Asked 1×Have you worked on PySpark or Scala?🟢 Easy · Behavioral · Asked 1×Earlier we discussed the silver layer, where we mainly write data cleansing logic using PySpark. I'm curious: would you still use Databricks notebooks and PySpark commands to create the gold layer? Are you familiar with dbt and can you execute dbt using traditional SQL templates?🟡 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×Which database service can be used to build a pipeline that uses native PySpark code?🟡 Medium · Conceptual · Asked 1×Do you have experience in PySpark?🟢 Easy · Behavioral · Asked 1×Can you explain some use cases you have recently handled in PySpark on Databricks?🟡 Medium · Conceptual · Asked 1×Do we need PySpark experience for a project that involves automation, leveraging Python automation libraries, working with APIs to connect to various systems, and developing an automation framework?🟡 Medium · Conceptual · Asked 1×Suppose we are re-ingesting some source data that is about 100 to 200 GB in size and we call the collect() function. What problems can arise from this?🟡 Medium · Conceptual · Asked 1×What are the differences between a broadcast join and a normal (shuffle) join in Spark?🟡 Medium · Conceptual · Asked 1×What are the different ways available in PySpark on Databricks to handle large data ingestion scenarios, and is there a particular approach that is recommended?🟡 Medium · Conceptual · Asked 1×What options are available in PySpark on Databricks to handle scenarios involving large datasets and joins?🟡 Medium · Conceptual · Asked 1×Will using a broadcast join resolve the scenario, and can you provide the syntax for it?🟡 Medium · Conceptual · Asked 1×Between Python and PySpark on Databricks, which is more professional? If you had to choose a primary skill set, what would you pick?🟡 Medium · Conceptual · Asked 1×Can you tell about any optimization techniques in PySpark?🟡 Medium · Conceptual · Asked 1×Can you tell me about the data pipeline you are using in your current project and your role in it?🟡 Medium · Conceptual · Asked 1×Explain how to perform a left join in PySpark and how broadcast join optimization can be used when the right table is small.🟡 Medium · Conceptual · Asked 1×How do you manage large volumes of data in a deep learning pipeline implementation using PySpark, including partitioning and handling bursts of data?🟡 Medium · Conceptual · Asked 1×Suppose multiple CSV files are coming daily into an S3 bucket, and sometimes the schema changes: new columns are added or data types change. How would you handle this situation in PySpark? Explain the steps and logic behind your approach.🟡 Medium · Conceptual · Asked 1×Can you explain a PySpark transformation you personally developed? What were the input DataFrames? What type of joins did you use? Did you save the input and output as views?🟡 Medium · Coding · Asked 1×Explain a complex Python PySpark code you have created in either your current or past projects. First describe the business problem, then explain the code you wrote to solve it.🟡 Medium · Behavioral · Asked 1×Are you versed with PySpark architecture?🟡 Medium · Conceptual · Asked 1×How was PySpark deployed within the AWS environment, and what services were used?🟡 Medium · Conceptual · Asked 1×Are you proficient in Spark fundamentals?🟡 Medium · Behavioral · Asked 1×You need to pull 200 million rows from a source JDBC system into Databricks. The current PySpark job uses a single partition and exhausts the driver. How would you redesign the read for parallelism (choose a partitionColumn, set lowerBound/upperBound/numPartitions, handle nulls/outliers, tune fetch size) and ensure the ingest is idempotent before writing to Bronze?🟡 Medium · Coding · Asked 1×In your primary skills, which languages do you use—Python, SQL, PySpark, AWS—and how would you rate yourself out of 10?🟢 Easy · Behavioral · Asked 1×Do you understand the tech stack? You have experience with Python, SQL, PySpark, and AWS. Is there anything else you'd like to add?🟢 Easy · Conceptual · Asked 1×Provide PySpark code to compute the acceptance rate per date based on the given table and code.🟡 Medium · Coding · Asked 1×Need PySpark code to compute acceptance rate per date.🟡 Medium · Coding · Asked 1×Give PySpark code to calculate the friend acceptance rate for each date when friend requests were sent. A request is sent if action = 'sent' and accepted if action = 'accepted'. If a request is not accepted, there is no record of it being accepted in the table. The output should only include dates where requests were sent and at least one of them was accepted (acceptance can occur on any date after the request is sent).🟡 Medium · Coding · Asked 1×

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