#join

Tell me about yourself and your experience.

What is the difference between narrow and wide transformations in Apache Spark? Explain with examples.

What architecture are you following in your current project, and why?

Explain the differences between Repartition and Coalesce. When would you use each?

What is the difference between partitioning and bucketing in Spark, and when would you use bucketing?

What strategies can you use to handle skewed data in Spark?

Briefly introduce yourself and walk us through your journey as a Data Engineer so far.

Describe a time when you had to optimize a slow SQL query. What steps did you take?

Explain the difference between INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

How do you handle NULL values in SQL? Mention functions like COALESCE and NULLIF.

Write a Python function to check if a string is a palindrome.

Describe a scenario where partitioning and bucketing would improve query performance.

Explain Fact and Dimension Tables with examples.

Joins and window functions - INNER, LEFT, RIGHT, FULL OUTER, ROW_NUMBER(), RANK(), DENSE_RANK()

When would you choose a Snowflake schema over a Star schema?

Can you explain the architecture of Apache Spark and its components?

How does Spark's Catalyst Optimizer work? Explain its stages.

Explain the concept of Broadcast Join in Spark. When should it be used?

How do you optimize Spark jobs for better performance? Mention at least 5 techniques.

What challenges did you face, and how did you tackle them?