Cloud Data Engineer Mock Interview | PySpark Coding Interview Questions |Azure Databricks #question

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ะŸะพะบะฐะทะฐั‚ัŒ ะพะฟะธัะฐะฝะธะต

I have trained over 20,000+ professionals in the field of Data Engineering in the last 5 years.

๐–๐š๐ง๐ญ ๐ญ๐จ ๐Œ๐š๐ฌ๐ญ๐ž๐ซ ๐’๐๐‹? ๐‹๐ž๐š๐ซ๐ง ๐’๐๐‹ ๐ญ๐ก๐ž ๐ซ๐ข๐ ๐ก๐ญ ๐ฐ๐š๐ฒ ๐ญ๐ก๐ซ๐จ๐ฎ๐ ๐ก ๐ญ๐ก๐ž ๐ฆ๐จ๐ฌ๐ญ ๐ฌ๐จ๐ฎ๐ ๐ก๐ญ ๐š๐Ÿ๐ญ๐ž๐ซ ๐œ๐จ๐ฎ๐ซ๐ฌ๐ž - ๐’๐๐‹ ๐‚๐ก๐š๐ฆ๐ฉ๐ข๐จ๐ง๐ฌ ๐๐ซ๐จ๐ ๐ซ๐š๐ฆ!

"๐€ 8 ๐ฐ๐ž๐ž๐ค ๐๐ซ๐จ๐ ๐ซ๐š๐ฆ ๐๐ž๐ฌ๐ข๐ ๐ง๐ž๐ ๐ญ๐จ ๐ก๐ž๐ฅ๐ฉ ๐ฒ๐จ๐ฎ ๐œ๐ซ๐š๐œ๐ค ๐ญ๐ก๐ž ๐ข๐ง๐ญ๐ž๐ซ๐ฏ๐ข๐ž๐ฐ๐ฌ ๐จ๐Ÿ ๐ญ๐จ๐ฉ ๐ฉ๐ซ๐จ๐๐ฎ๐œ๐ญ ๐›๐š๐ฌ๐ž๐ ๐œ๐จ๐ฆ๐ฉ๐š๐ง๐ข๐ž๐ฌ ๐›๐ฒ ๐๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ข๐ง๐  ๐š ๐ญ๐ก๐จ๐ฎ๐ ๐ก๐ญ ๐ฉ๐ซ๐จ๐œ๐ž๐ฌ๐ฌ ๐š๐ง๐ ๐š๐ง ๐š๐ฉ๐ฉ๐ซ๐จ๐š๐œ๐ก ๐ญ๐จ ๐ฌ๐จ๐ฅ๐ฏ๐ž ๐š๐ง ๐ฎ๐ง๐ฌ๐ž๐ž๐ง ๐๐ซ๐จ๐›๐ฅ๐ž๐ฆ."

๐‡๐ž๐ซ๐ž ๐ข๐ฌ ๐ก๐จ๐ฐ ๐ฒ๐จ๐ฎ ๐œ๐š๐ง ๐ซ๐ž๐ ๐ข๐ฌ๐ญ๐ž๐ซ ๐Ÿ๐จ๐ซ ๐ญ๐ก๐ž ๐๐ซ๐จ๐ ๐ซ๐š๐ฆ -

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

Link of Free SQL & Python series developed by me are given below -

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Timestamp : Questions Discussed
1:10 Introduction
2:38 Differences between Spark Core APIs and Higher-Level APIs?
5:00 RDD vs DataFrames vs Spark SQL: Which is the recommended approach in Spark?
6:22 What is a DAG? When is a DAG executed?
8:44 Explain Spark's job, stages, and tasks.
10:00 How does Spark execute a job from action invocation?
11:32 How to determine the number of partitions in a dataframe?
13:00 Pyspark Coding Question
18:03 Which is more efficient: inferring a schema or enforcing it?
20:06 Ways to enforce a schema?
24:05 DataFrame Read Modes?
26:00 DataFrame write modes?
28:04 What is Databricks, and what advantages does it offer over plain vanilla versions?
29:50 Explain medallion architecture in detail ?

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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
ะ ะตะบะพะผะตะฝะดะฐั†ะธะธ ะฟะพ ั‚ะตะผะต
ะšะพะผะผะตะฝั‚ะฐั€ะธะธ
ะะฒั‚ะพั€

Interviewer involvement is very high that is cooperative to the interviewee

mareswararaomalle
ะะฒั‚ะพั€

Good Job... Thank you for informative session

akshaykudale
ะะฒั‚ะพั€

best Interviewer and wish I will have same experience in next interview

meghaonnath
ะะฒั‚ะพั€

Thank you for this informative content!

jaisriram