Mock Interview for Data Engineers | Spark Optimizations | Real-time Project Challenges and Scenarios

𝐓𝐨 𝐞𝐧𝐡𝐚𝐧𝐜𝐞 𝐲𝐨𝐮𝐫 𝐜𝐚𝐫𝐞𝐞𝐫 𝐚𝐬 𝐚 𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫, 𝐂𝐡𝐞𝐜𝐤 https://trendytech.in/?src=youtube&su... for curated courses developed by me.

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𝐖𝐚𝐧𝐭 𝐭𝐨 𝐌𝐚𝐬𝐭𝐞𝐫 𝐒𝐐𝐋? 𝐋𝐞𝐚𝐫𝐧 𝐒𝐐𝐋 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐰𝐚𝐲 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐭𝐡𝐞 𝐦𝐨𝐬𝐭 𝐬𝐨𝐮𝐠𝐡𝐭 𝐚𝐟𝐭𝐞𝐫 𝐜𝐨𝐮𝐫𝐬𝐞 - 𝐒𝐐𝐋 𝐂𝐡𝐚𝐦𝐩𝐢𝐨𝐧𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦!

"𝐀 8 𝐰𝐞𝐞𝐤 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐭𝐨 𝐡𝐞𝐥𝐩 𝐲𝐨𝐮 𝐜𝐫𝐚𝐜𝐤 𝐭𝐡𝐞 𝐢𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬 𝐨𝐟 𝐭𝐨𝐩 𝐩𝐫𝐨𝐝𝐮𝐜𝐭 𝐛𝐚𝐬𝐞𝐝 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐛𝐲 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐢𝐧𝐠 𝐚 𝐭𝐡𝐨𝐮𝐠𝐡𝐭 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐚𝐧𝐝 𝐚𝐧 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡 𝐭𝐨 𝐬𝐨𝐥𝐯𝐞 𝐚𝐧 𝐮𝐧𝐬𝐞𝐞𝐧 𝐏𝐫𝐨𝐛𝐥𝐞𝐦."

𝐇𝐞𝐫𝐞 𝐢𝐬 𝐡𝐨𝐰 𝐲𝐨𝐮 𝐜𝐚𝐧 𝐫𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐏𝐫𝐨𝐠𝐫𝐚𝐦 -
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤 (𝐂𝐨𝐮𝐫𝐬𝐞 𝐀𝐜𝐜𝐞𝐬𝐬 𝐟𝐫𝐨𝐦 𝐈𝐧𝐝𝐢𝐚) : https://rzp.io/l/SQLINR
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐋𝐢𝐧𝐤 (𝐂𝐨𝐮𝐫𝐬𝐞 𝐀𝐜𝐜𝐞𝐬𝐬 𝐟𝐫𝐨𝐦 𝐨𝐮𝐭𝐬𝐢𝐝𝐞 𝐈𝐧𝐝𝐢𝐚) : https://rzp.io/l/SQLUSD

30 INTERVIEWS IN 30 DAYS- BIG DATA INTERVIEW SERIES

This mock interview series is launched as a community initiative under Data Engineers Club aimed at aiding the community's growth and development

A highly experienced guest interviewer, Himanshu Mishra,   / himanshu-mishra-4796014b   conducting a well engaging interview covering all the important topics that a Data Engineer should be aware of.

Our talented guest interviewee, Hamida Bano,   / hamida-bano-793804208   answering the interview questions in a very simplistic way with good examples.

Link of Free SQL & Python series developed by me are given below -
SQL Playlist -    • SQL tutorial for everyone by Sumit Si...  
Python Playlist -    • Complete Python By Sumit Mittal Sir  

Don't miss out - Subscribe to the channel for more such informative interviews and unlock the secrets to success in this thriving field!

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Student Testimonials - https://trendytech.in/#testimonials

Discussed Questions : Timestamp
1: 40 Introduction
2:21 Challenges you faced in your project
4:40 What’s the contribution towards your project ?
6:20 File formats you have worked on in your project ?
7:53 What is wide and narrow transformations ?
9:38 Lazy evaluation in spark ?
11:25 What is fault tolerance in spark and mapreduce and how does it work ?
13:32 Client mode and Cluster mode in spark ?
14:15 Broadcast joins we have in spark ?
15:18 Memory management in spark ?
18:12 In live production, if you are facing an out of memory error. So what’s the approach you follow to debug that?
19:51 What is Data skewness ?
20:16 What is Caching ?
21:38 How do you test your spark code ?
22:17 What are the performance tuning techniques that you use to tune your spark job ?
23:18 What is coalesce and when should we use it ?
24:54 Managed and external tables with a use case
26:28 How do you deploy your spark code ?
27:29 How did you schedule your workflow ?
28:14 What are the version control tools you have used ?
28:49 What is shuffling and why do we need to think of minimising it ?
29:50 One of the Spark jobs you've developed is experiencing slow performance. How would you go about resolving this issue?
31:00 What are the transformations and actions you have performed in the current project ?
32:03 How does spark work ? Explain Spark Architecture ?
33:05 What is lineage in spark ?
33:50 Different types of joins in spark ? Use case on any one of those joins ?
35:25 What is a spark session and how do we initialise it ?
36:33 How to read a parquet file into a dataframe ?
37:37 How can you perform filters on a dataframe?
39:20 How to remove duplicates in a dataframe ?
39:56 Consider a scenario where in dataframe we want to update a column name, So how will you do this ?
40:40 Usage of withColumn ?
41:27 How to remove any column from a dataframe ?
41:50 Have you handled any null values in your dataframe ?
42:37 SQL Coding Question

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