Real questions from top companies in Spark/Big Data
What are the different delivery semantics in Kafka (at least-once, at-most-once, exactly-once)?
What are the different modes in which you can submit Spark jobs? Explain each.
What are the key differences between Map and Reduce in Spark?
What are the key performance tuning techniques you apply in Spark jobs to improve performance?
What are the key properties of Delta Lake that differentiate it from traditional data lakes?
What are the limitations of the REORG command with respect to large datasets?
What are the performance considerations when using Auto Loader?
What are the performance trade-offs of using salting to mitigate data skewness?
What are the steps to connect to Salesforce?
What are the steps to debug a failed workflow in Databricks?
What are the steps to efficiently process 1 TB of data in Spark?
What are the steps to execute a Python file with PySpark code on an EC2 environment?
What are the trade-offs between using Glue Catalog vs. Hive Metastore for metadata management?
What are transient clusters in EMR, and when would you use them?
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 configurations are needed to pass parameters to a Databricks notebook?
What determines the maximum parallelism achievable in Databricks?
What do you understand by data shuffling in Spark? Why is it important?
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