PySpark Interview Questions (2025) | PySpark Real Time Scenarios

PySpark Interview Qustions (2025) | PySpark Real Time Scenarios | Databricks Interview Questions

Welcome to our 4+ hour video on PySpark Interview Questions, where we dive deep into real-time scenarios to equip you with the knowledge and confidence needed to excel in your PySpark Interviews including PySpark Coding Questions and Conceptual Questions.

What You'll Learn:
- Real-Time Scenarios: Tackle practical interview questions that reflect real-world challenges in data engineering.
- Delta Lake: Understand how Delta Lake enhances data reliability and performance in your PySpark applications.
- Spark Structured Streaming: Learn how to implement real-time data processing solutions using Spark Structured Streaming.
- Spark Architecture: Gain insights into the architecture of Spark and how it efficiently processes large datasets.
- Spark Cluster: Explore the components of a Spark cluster and their roles in distributed computing.
- SparkSQL: Master querying data with SparkSQL to perform complex data manipulations.
- File Formats: Discover the various file formats supported by Spark and their appropriate use cases.


Azure End To End Data Project : https://youtu.be/6_hXeNg9TJ0?si=9naCovTmgcZn0NQQ
Databricks Tutorial : https://youtu.be/P5pEeR3xQpI?si=XbQYrYkrVp2jKjfE
PySpark Full Course : https://youtu.be/94w6hPk7nkM?si=Y2EUnifXrZRK3MOj

Notebook Link - https://github.com/anshlambagit/PySparkInterview
Telegram Channel - https://t.me/anshlambadatafam
Telegram Group - https://t.me/+9jR_HQ4YhBMzY2Q1

Connect with ME - https://www.linkedin.com/in/ansh-lamba-793681184/

Timestamps:
0:00 Introduction
14:55 Databricks Free Account
17:02 Databricks Overview
19:00 PySpark Real Time Scenarios
38:44 Apache Spark vs Hadoop MapReduce
44:35 PySpark Structured Streaming
49:45 Window Functions using PySpark
57:54 Date Functions in PySpark
1:04:18 Array Functions in PySpark
1:09:45 PySpark Advanced Level Interview Questions
1:36:22 Spark Context
1:37:31 Spark Architecture
1:41:35 Slowly Changing Dimension using Pyspark
1:48:00 Data Ingestion using InferSchema
1:50:20 Data Reading with PySpark
1:51:12 RDDs VS Dataframe VS Dataset
1:57:26 PySpark Query Optimization
2:05:08 Narrow VS Wide Transformations in PySpark
2:18:36 PySpark Aggregation Functions
2:21:06 Conditional Functions
2:28:08 Spark SQL
2:33:08 Temp Views in SparkSQL
2:37:25 Data Writing in Partitions
2:42:08 Spark Optimization using Delta Lake
2:47:53 Broadcast Variables
2:50:58 Lazy Evaluation in Spark
2:54:04 Delta Lake Benefits
3:01:11 Adaptive Query Execution (AQE) in PySpark
3:07:14 Salting in Spark
3:08:42 Broadcast Join in Apache Spark
3:12:46 Time Travel in Delta Lake
3:19:21 PySpark Real Time Interview Questions


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#pyspark #databricks #azure #dataengineering #interview