Real questions from top companies · hard
How does Autoscaling work in Databricks and what are its benefits?
How does Data Flow optimize data transformations for large datasets?
How does Databricks create clusters for running Spark jobs?
How does Databricks integrate with external storage systems?
How does Delta Lake store the transaction history in S3 buckets?
How does Glue Catalog handle schema versioning compared to Hive Metastore?
How does Kafka ensure message durability and reliability?
How does Optimize command improve query latency in Delta tables?
How does Spark execute a job? Explain the DAG and stages.
How does lazy evaluation work in Spark?
How does the driver program handle task scheduling?
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?
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