Meesho PySpark Interview Questions for Data Engineers in 2025 Preparing for a PySpark interview? Let’s tackle some commonly asked questions, along with practical answers and insights to ace your next Data Engineering interview at Meesho or any top-tier tech company. 1. Explain how caching and persistence work in PySpark. When would you use cache() versus persist() and what are their performance implications? Answer : Caching : Stores data in memory (default) for faster retrieval. Use cache() when you need to reuse a DataFrame or RDD multiple times in a session without specifying storage levels. Example: python df.cache() df.count() # Triggers caching Persistence : Allows you to specify storage levels (e.g., memory, disk, or a combination). Use persist() when memory is limited, and you want a fallback to disk storage. Example: python from pyspark import StorageLevel df.persist(StorageLevel.MEMORY_AND_DISK) df.count() # Triggers persistence Performance Implications : cache() is ...
EXL Interview Experience for Power BI Developer (3 Years of Experience) I recently appeared for an interview at EXL for the role of Power BI Developer . The selection process consisted of three rounds: 2 Technical Rounds 1 Managerial Round Here, I’ll share the key technical questions I encountered, along with my approach to answering them. SQL Questions 1️⃣ Write a SQL query to find the second most recent order date for each customer from a table Orders ( OrderID , CustomerID , OrderDate ). To solve this, I used the ROW_NUMBER() window function: sql WITH RankedOrders AS ( SELECT CustomerID, OrderDate, ROW_NUMBER () OVER ( PARTITION BY CustomerID ORDER BY OrderDate DESC ) AS RowNum FROM Orders ) SELECT CustomerID, OrderDate AS SecondMostRecentOrderDate FROM RankedOrders WHERE RowNum = 2 ; 2️⃣ Write a query to find the nth highest salary from a table Employees with columns ( EmployeeID , Name , Salary ). The DENSE_RANK() fu...