Real questions from top companies · hard
How do you monitor and debug Spark applications in production?
How do you move a Databricks notebook to higher environments?
How do you optimize a join operation in Spark for large datasets?
How do you optimize long-running PySpark scripts on EMR?
How do you reduce shuffle operations in Spark?
How do you resolve merge conflicts in Databricks notebooks?
How do you set up CI/CD for a PySpark ETL workflow?
How do you store streaming data in Delta Lake and handle schema evolution?
How do you use Spark UI to debug stages, tasks, and performance issues?
How does Adaptive Query Execution (AQE) work?
How does Auto Loader avoid reloading files with the same name?
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.
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