Interview questions
How do you decide the number of partitions for repartitioning data in Spark?
How do you handle bad data in Databricks?
How do you identify skewed partitions in a dataset?
How do you resolve merge conflicts in Databricks notebooks?
How do you use Spark UI to debug stages, tasks, and performance issues?
How does Optimize command improve query latency in Delta tables?
How does the driver program handle task scheduling?
How is Git version control implemented in Databricks?
How would you identify and resolve a shuffle spill in Spark UI?
What are the limitations of the REORG command with respect to large datasets?
What are the performance trade-offs of using salting to mitigate data skewness?
What causes Out of Memory (OOM) issues in Databricks, and how do you resolve them?
What causes data skewness in Spark, and how can it be resolved?
What configuration parameters are critical for enabling AQE effectively?
What happens if the vacuum command is not run periodically?
What happens when an executor fails during a task execution?
What insights can you gather from the DAG visualization in Spark UI?
What is the usage of Optimize and REORG commands in Databricks?
What limitations do you face when using Delta Tables in a multi-cloud environment?
Can Schema Evolution lead to data inconsistencies? If so, how do you manage them?
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