Скачать или смотреть Hadoop vs Spark | MapReduce | Big Data

In this video, we delve into the key differences between Hadoop and Apache Spark, two powerful frameworks for big data processing. Here’s what you’ll learn:
• Performance Comparison: Understand why Spark is 3-5 times faster than Hadoop, thanks to its in-memory processing capabilities versus Hadoop’s disk-based storage.
• Processing Models: Explore how Hadoop uses MapReduce for batch processing, while Spark supports both batch and streaming data processing.
• Ease of Use: Learn why Spark is more developer-friendly compared to the complexity of Hadoop.
• Security Features: Discover the robust security features of Hadoop and how Spark relies on these for its operations.
• Fault Tolerance: Compare Hadoop’s data replication mechanism with Spark’s RDD-based recovery system.
• Data Storage and Management: Gain insights into HOFS (Hadoop File System) and YARN for resource management in big data environments.
• Directed Acyclic Graphs (DAGs): Understand how Spark utilizes DAGs for efficient task scheduling and execution.
Whether you’re a beginner or an experienced developer, this video provides a comprehensive overview of why Apache Spark is becoming increasingly popular in the big data ecosystem. Don’t forget to like, comment, and subscribe for more tech insights!


#Hadoop, #ApacheSpark, #BigDataAnalytics, #DataProcessing, #InMemoryComputing