Real questions from top companies
How is Git version control implemented in Databricks?
How many stages are created in a Spark job, and how are they formed?
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How to Upsert Your Data Daily Using Spark
How would you debug a failing Spark job running on Dataproc?
How would you debug a slow-running PySpark job? What factors would you investigate?
How would you design a Kafka-based pipeline for processing streaming data in real-time?
How would you design a scalable and fault-tolerant data processing pipeline for handling large volumes of streaming data?
How would you handle a large-scale data shuffle in a Dataflow pipeline?
How would you handle unstructured data in Hive?
How would you identify and resolve a shuffle spill in Spark UI?
How would you manage the streaming data schema and handle schema evolution in Delta Lake?
How would you manage transitions to Glacier Instant Retrieval and Deep Archive?
How would you migrate metadata from Hive Metastore to Glue?
If a consumer fails to process a message due to data corruption, describe how you would configure Kafka to handle retries and avoid message loss.
In Spark, what is the difference between cores and executors?
Provide specific examples of challenges faced with PySpark and SQL and solutions implemented.
Share your experience in working with big data technologies such as Hadoop, Spark, or AWS EMR. How have you leveraged these tools in your previous projects?
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