90% of Data Engineers doesn't know this - PySpark Azure Data Engineering Interview Question Tutorial

#ApacheSpark #DataEngineering #AzureDataEngineer #SparkSQL #DataTransformation #DataFrame #InterviewQuestion #BigData #AzureDatabricks #PySpark #DataAnalysis #DataScience #SQLQuery #Optimization #Efficiency #Tutorial

Welcome to our latest video where we delve into an essential interview question for Azure Data Engineers focusing on Apache Spark. Specifically, we tackle data transformation without the need for temporary views, a crucial skill for efficient Spark SQL operations.

In this tutorial, we break down the process step-by-step. Firstly, we explore the traditional method where engineers typically create temporary views before executing Spark SQL commands. Then, we unveil a more streamlined approach that directly utilizes the DataFrame within Spark SQL queries, eliminating the need for intermediate views.

Join us as we demonstrate both methods in a hands-on demo using Azure Databricks. From defining DataFrame schemas to executing complex transformations, we guide you through the process, ensuring you grasp the concept thoroughly.

By adopting this advanced technique, you can optimize your Spark workflows, saving valuable time and resources. Whether you're a seasoned data engineer or just starting your journey, mastering this technique will enhance your efficiency and effectiveness in Apache Spark projects.

If you find this video helpful or have any questions, feel free to leave a comment below. Don't forget to like, share, and subscribe for more insightful content on mastering Apache Spark and excelling in data engineering interviews. Let's elevate our Spark skills together!

TimeStamp:

0:00:00 - Intro
0:02:08 - Demo
0:04:04 - Old Way
0:06:16 - New Way

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– – – Other useful playlist: – – –

1. Microsoft Fabric Playlist: https://www.youtube.com/playlist?list=PLrG_BXEk3kXybedCIBBI4lmaIbtbn7MdM
2. Azure General Topics Playlist: https://www.youtube.com/playlist?list=PLrG_BXEk3kXxv0IEASoJRTHuRq_DUqrjR
3. Azure Data Factory Playlist: https://www.youtube.com/playlist?list=PLrG_BXEk3kXwTClTt3_28CMz2dZoaFhKD
4. Databricks CICD Playlist: https://www.youtube.com/playlist?list=PLrG_BXEk3kXzMLDAgRbDsbIKvhoWsu-Gq
5. Azure Databricks Playlist: https://www.youtube.com/playlist?list=PLrG_BXEk3kXznRvTJXwmazGCvTSxdCMsN
6. Azure End to End Project Playlist: https://www.youtube.com/playlist?list=PLrG_BXEk3kXx6KE4nBmhf6QwSHMbznP2W
7. End to End Azure Data Engineering Project: https://youtu.be/iQ41WqhHglk

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Mr. K is a passionate teacher created this channel for only one goal "TO HELP PEOPLE LEARN ABOUT THE MODERN DATA PLATFORM SOLUTIONS USING CLOUD TECHNOLOGIES"

I will be creating playlist which covers the below topics (with DEMO)

1. Azure Beginner Tutorials
2. Azure Data Factory
3. Azure Synapse Analytics
4. Azure Databricks
5. Microsoft Power BI
6. Azure Data Lake Gen2
7. Azure DevOps
8. GitHub (and several other topics)

After creating some basic foundational videos, I will be creating some of the videos with the real time scenarios / use case specific to the three common Data Fields,

1. Data Engineer
2. Data Analyst
3. Data Scientist

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#Azure_Data_Engineer_Interview_Questions #Azure_Data_Engineering #Data_Engineering #Interview_Question #PySpark_Interview_Questions #How_to_prepare_for_Azure_Data_Engineering_Interview #ADF_Interview_Questions #Interview_Questions #Databricks_Interview_Questions #Managed_Identity #Service_Principal #Data_Engineer_Interview_Questions #Synapse_Analytics_Interview_Question #Microsoft_Fabric_interview_question #DP_203_questions #DP_203_Dumps #Questions #Interview_Tips_and_tricks

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