๐๐จ ๐๐ง๐ก๐๐ง๐๐ ๐ฒ๐จ๐ฎ๐ซ ๐๐๐ซ๐๐๐ซ ๐๐ฌ ๐ ๐๐ฅ๐จ๐ฎ๐ ๐๐๐ญ๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ, ๐๐ก๐๐๐ค trendytech.in/?src=youtube&su... for curated courses developed by me.
๐๐๐ง๐ญ ๐ญ๐จ ๐๐๐ฌ๐ญ๐๐ซ ๐๐๐? ๐๐๐๐ซ๐ง ๐๐๐ ๐ญ๐ก๐ ๐ซ๐ข๐ ๐ก๐ญ ๐ฐ๐๐ฒ ๐ญ๐ก๐ซ๐จ๐ฎ๐ ๐ก ๐ญ๐ก๐ ๐ฆ๐จ๐ฌ๐ญ ๐ฌ๐จ๐ฎ๐ ๐ก๐ญ ๐๐๐ญ๐๐ซ ๐๐จ๐ฎ๐ซ๐ฌ๐ - ๐๐๐ ๐๐ก๐๐ฆ๐ฉ๐ข๐จ๐ง๐ฌ ๐๐ซ๐จ๐ ๐ซ๐๐ฆ!
"๐ 8 ๐ฐ๐๐๐ค ๐๐ซ๐จ๐ ๐ซ๐๐ฆ ๐๐๐ฌ๐ข๐ ๐ง๐๐ ๐ญ๐จ ๐ก๐๐ฅ๐ฉ ๐ฒ๐จ๐ฎ ๐๐ซ๐๐๐ค ๐ญ๐ก๐ ๐ข๐ง๐ญ๐๐ซ๐ฏ๐ข๐๐ฐ๐ฌ ๐จ๐ ๐ญ๐จ๐ฉ ๐ฉ๐ซ๐จ๐๐ฎ๐๐ญ ๐๐๐ฌ๐๐ ๐๐จ๐ฆ๐ฉ๐๐ง๐ข๐๐ฌ ๐๐ฒ ๐๐๐ฏ๐๐ฅ๐จ๐ฉ๐ข๐ง๐ ๐ ๐ญ๐ก๐จ๐ฎ๐ ๐ก๐ญ ๐ฉ๐ซ๐จ๐๐๐ฌ๐ฌ ๐๐ง๐ ๐๐ง ๐๐ฉ๐ฉ๐ซ๐จ๐๐๐ก ๐ญ๐จ ๐ฌ๐จ๐ฅ๐ฏ๐ ๐๐ง ๐ฎ๐ง๐ฌ๐๐๐ง ๐๐ซ๐จ๐๐ฅ๐๐ฆ."
๐๐๐ซ๐ ๐ข๐ฌ ๐ก๐จ๐ฐ ๐ฒ๐จ๐ฎ ๐๐๐ง ๐ซ๐๐ ๐ข๐ฌ๐ญ๐๐ซ ๐๐จ๐ซ ๐ญ๐ก๐ ๐๐ซ๐จ๐ ๐ซ๐๐ฆ -
๐๐๐ ๐ข๐ฌ๐ญ๐ซ๐๐ญ๐ข๐จ๐ง ๐๐ข๐ง๐ค (๐๐จ๐ฎ๐ซ๐ฌ๐ ๐๐๐๐๐ฌ๐ฌ ๐๐ซ๐จ๐ฆ ๐๐ง๐๐ข๐) : rzp.io/l/SQLINR
๐๐๐ ๐ข๐ฌ๐ญ๐ซ๐๐ญ๐ข๐จ๐ง ๐๐ข๐ง๐ค (๐๐จ๐ฎ๐ซ๐ฌ๐ ๐๐๐๐๐ฌ๐ฌ ๐๐ซ๐จ๐ฆ ๐จ๐ฎ๐ญ๐ฌ๐ข๐๐ ๐๐ง๐๐ข๐) : rzp.io/l/SQLUSD
I have trained over 20,000+ professionals in the field of Data Engineering in the last 5 years.
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
Our highly experienced guest interviewer, Chandrali Sarkar, / chandrali-sarkar-4570a... shares invaluable insights and practical guidance drawn from her extensive expertise in the Big Data Domain.
Our expert guest interviewee, Soumya Ranjan Parida, / soumya-parida has an interesting approach to answering the interview questions on Apache Spark, SQL and Azure Cloud Services.
Link of Free SQL & Python series developed by me are given below -
SQL Playlist - โข SQL tutorial for every...
Python Playlist - โข Complete Python By Sum...
Don't miss out - Subscribe to the channel for more such informative interviews and unlock the secrets to success in this thriving field!
Social Media Links :
LinkedIn - / bigdatabysumit
Twitter - / bigdatasumit
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Student Testimonials - trendytech.in/#testimonials
TIMESTAMPS : Questions Discussed
00:35 Introduction
01:40 Explain your project's end-to-end pipeline and overview.
03:17 What is the data source for your project?
03:36 Where does the data get ingested?
04:36 What types of data are being processed?
05:04 How do you capture incremental data in an OLTP environment?
07:52 What is the frequency and volume of the incoming data?
08:28 Which file formats have you worked with?
09:00 What is the predicate pushdown?
10:14 What optimizations have you applied in Spark?
10:45 Define broadcast join.
11:10 List some transformations you've used in Spark.
11:27 Explain narrow and wide transformations.
12:03 What is the difference between reduceByKey and groupByKey.
12:56 Have you encountered "out of memory" errors in Spark? How did you resolve them?
14:22 How will salting help in resolving out of memory error?
14:46 What is data skewness?
15:22 Explain cache and persist in Spark.
16:57 If memory and disk are full then in that case what will happen?
17:40 When would you use coalesce and repartition?
18:00 Provide a scenario where coalesce and repartition can be used?
18:38 Where does repartition happen at driver or executor level?
19:30 What is the difference between rank, dense rank, and row number functions?
22:06 Describe the internal process of submitting a Spark job.
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#mockinterview #bigdata #career #dataengineering #data #datascience #dataanalysis #productbasedcompanies #interviewquestions #apachespark #google #interview #faang #companies #amazon #walmart #flipkart #microsoft #azure #databricks #jobs
27 ะผะฐะน 2024
