Скачать или смотреть Day 29: Apache Spark from Scratch (Part 15) | Windowing in Spark | PySpark | The Basic Teacher

Welcome to Day 29 of our Big Data & Data Engineering Training! In this session, we dive into Apache Spark, one of the most powerful frameworks for big data processing.

🔥 What You'll Learn in This Video:
✅ Introduction to Apache Spark and its architecture
✅ Spark vs. Hadoop – Why Spark is faster
✅ Spark architecture in detail
✅ Understanding RDDs, DataFrames, and Datasets
✅ RDDs, DataFrames, and Datasets
✅ Transformations in Spark
✅ Narrow Transformations in Spark
✅ Wide Transformations in Spark
✅ Narrow and Wide Transformations in Spark
✅ Hands-on Exercise: Working with RDDs, DataFrames, and Datasets.
✅ Coalesce and Repartition in Spark
✅ Cache and Persist in Spark
✅ PySpark hands-on exercise
✅ Basic Spark transformations and actions
✅ Apache Spark live session
✅ Hands-on exercises
✅ Apache Spark end-to-end project
✅ Read JSON file in Spark
✅ UDF in Spark
✅ Map and Array Data Types in Spark
✅ Functions in Spark
✅ Complex use case in Spark
✅ Joins in Spark
✅ Skew join in Spark
✅ Solving Data Skew Issues During Joins in Apache Spark
✅ Skewed dataset join in Spark
✅ Configs in Spark
✅ Optimizations in Spark
✅ CDC in Spark
✅ Change Data Capture in Spark
✅ CDC (Change Data Capture with PySpark and SQL)
✅ CDC with PySpark
✅ CDC with SQL
✅ Change Data Capture with PySpark
✅ Change Data Capture with SQL
✅ Spark Streaming
✅ Live Data Streaming in Spark
✅ Window in Spark Streaming
✅ Windowing in Spark
✅ Spark Streaming and Windowing
✅ What is Spark Streaming?
✅ What is Windowing in Spark Streaming?
✅ Tumbling Windows
✅ Sliding Windows
✅ Session Windows
✅ Use Cases of Windowing
✅ Project in Pyspark
✅ Data Engineering End-to-End Project (It is part of this video)
✅ PySpark Project (It is part of this video)
✅ Interview Preparation (It is part of this video)
✅ Data Engineering Interview (It is part of this video)



📌 This is Part 15, where we cover the fundamentals, architecture, RDD, DataFrame and Dataset. Stay tuned for the next part to explore advanced Spark operations!

🎯 Who Should Watch?
🔹 Aspiring Data Engineers & Big Data Enthusiasts
🔹 Software Developers looking to expand into Data Engineering
🔹 Anyone interested in Spark for large-scale data processing

📌 Connect with me to grab your spot in the live session for the upcoming batch!
📱 Connect on WhatsApp: +91 83539 60906
📩 Connect via email: [email protected]

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💬 Have questions? Drop them in the comments section, and I'll be happy to answer. 😊

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