Apache Spark - The Ultimate Guide [From ZERO To PRO]

Apache Spark | Databricks | PySpark | Big Data Engineering | Hadoop šŸ” What You'll Learn: This 6+ hour video is your complete guide to mastering Apache Spark from scratch. It covers everything from Spark architecture to advanced topics like Shuffle Joins, Broadcast Joins, Executor Out of Memory issues, Salting, Caching and Persisting, Dynamic Partition Pruning, Adaptive Query Execution, and much more. Timestamps: 0:00 Introduction 13:26 What is Apache Spark 21:03 Apache Spark V/S Hadoop MapReduce 33:36 Spark Architecture 49:40 Application Master Container 59:08 Databricks Free Account 1:06:55 Spark Session 1:17:56 Lazy Evaluation and Actions 1:32:58 Spark Query Plans and Spark UI 1:39:27 Spark RDD 1:49:49 Narrow and Wide Transformations 2:10:10 Repartition VS Coalesce 2:17:54 Jobs, Stages, and Tasks in PySpark 2:47:58 Shuffle Joins in PySpark 3:12:28 Broadcast Joins in PySpark 3:33:51 Spark SQL Engine 3:41:07 Driver Memory Management 3:52:15 Executor Memory Management 4:06:16 Unified Memory Management 4:13:16 Executor Out Of Memory 4:24:16 Salting in PySpark 4:29:58 Cache and Persist in Apache Spark 4:55:23 Edge Node and Deployment Mode 5:08:49 Dynamic Partition Pruning in Apache Spark 5:28:49 Adaptive Query Execution WATCH MY PREVIOUS VIDEOS āž”ļøPySpark Full Course    • PySparkĀ TutorialĀ |Ā FullĀ CourseĀ (FromĀ ZeroĀ ...Ā Ā  āž”ļøAzure End To End Data Project    • TheĀ ONLYĀ AzureĀ End-To-EndĀ DataĀ Engineering...Ā Ā  āž”ļøDatabricks Tutorial    • DatabricksĀ TutorialĀ (FromĀ ZeroĀ toĀ Hero)Ā |Ā ...Ā Ā  REPOSITORY āž”ļøGitHub https://github.com/anshlambagit/Apach... ======================================= Join this channel to SUPPORT MY HARDWORK: Ā Ā Ā /Ā @anshlambajsrĀ Ā  ======================================= Connect with ME LinkedIn - Ā Ā /Ā ansh-lamba-793681184Ā Ā  Telegram - https://t.me/anshlambadatafam ========================= For COLLABORATION šŸ‘‡ [email protected] ========================= ⭐Hashtags⭐ #dataengineering #bigdata #apachespark #databricks

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