What is the difference between Hadoop 1 and Hadoop 2?

What is the difference between Hadoop 1 and Hadoop 2?

When comparing Hadoop 1 and Hadoop 2, there are several key differences that are important to note:

1. Architecture: Hadoop 1 follows a Master/Slave architecture where JobTracker and TaskTracker are the main components. Hadoop 2 introduces the concept of ResourceManager and NodeManager, following a more scalable and efficient architecture.
2. High Availability: Hadoop 1 lacks support for high availability, meaning that a single point of failure can disrupt the entire system. Hadoop 2 introduces High Availability with the addition of standby NodeManagers and ResourceManager, improving system reliability.
3. YARN: Hadoop 1 has a limitation in terms of resource management with only MapReduce as the processing framework. Hadoop 2 includes YARN (Yet Another Resource Negotiator), which allows for multiple processing frameworks to run on top of Hadoop, enabling more flexibility and improved resource utilization.
4. Scalability: Hadoop 1 has limitations in scaling beyond a certain point due to its architecture constraints. Hadoop 2 is designed to be more scalable, supporting larger cluster sizes and accommodating diverse workloads efficiently.
5. Compatibility: Hadoop 2 maintains compatibility with Hadoop 1, ensuring that existing applications can seamlessly transition to the newer version without major disruptions.

Overall, the transition from Hadoop 1 to Hadoop 2 represents a significant evolution in the Hadoop ecosystem, bringing improvements in scalability, reliability, and flexibility to handle the growing demands of Big Data processing.