Hadoop 2.0

Hadoop 2.0, also known as Hadoop 2.x, was a significant milestone in the evolution of the Apache Hadoop ecosystem. It brought several important enhancements and changes compared to the earlier Hadoop 1.x versions. Here are some key features and improvements introduced in Hadoop 2.0:

1. YARN (Yet Another Resource Negotiator):

   • The most notable change in Hadoop 2.0 was the introduction of YARN, a resource management and job scheduling framework.
   • YARN decoupled the resource management and job scheduling aspects from the MapReduce framework, making Hadoop more versatile by allowing multiple processing frameworks to run on the same cluster.
   • With YARN, you can run not only MapReduce jobs but also other data processing frameworks like Apache Spark, Apache Flink, and more.

2. Resource Management:

   • YARN introduced a more flexible resource management system compared to the fixed slots model used in Hadoop 1.x.
   • It allows dynamic allocation of resources (CPU and memory) to different applications running on the same cluster.

3. High Availability for HDFS:

   • Hadoop 2.0 added High Availability (HA) support for the Hadoop Distributed File System (HDFS). HA ensures that the NameNode, a critical component, remains available even if one NameNode fails.

4. HDFS Federation:

   • HDFS Federation was introduced to improve the scalability of HDFS. It allows multiple independent namespaces (namespaces are divided into separate directories) within a single HDFS cluster.
   • Each namespace has its own namespace ID and block pool, improving storage efficiency and isolation.

5. Compatibility with Hadoop 1.x:

   • Hadoop 2.0 maintained backward compatibility with Hadoop 1.x, making it easier for organizations to migrate from earlier versions while retaining existing MapReduce jobs.

6. Improved Scalability:

   • Hadoop 2.0 was designed to scale more efficiently than Hadoop 1.x, addressing limitations in cluster size and node capacity.

7. Additional Ecosystem Projects:

   • Hadoop 2.0’s YARN architecture allowed the Hadoop ecosystem to expand, including the integration of new data processing frameworks alongside MapReduce.

8. Resource Scheduling:

   • YARN introduced advanced resource scheduling capabilities, allowing different applications to share cluster resources efficiently.

9. Security Enhancements:

   • Hadoop 2.0 included improvements in security, such as Hadoop Secure Mode, which enhances cluster security through user authentication and authorization.

10. Stability and Performance:

    • Hadoop 2.0 aimed to improve cluster stability, performance, and support for a wider range of workloads compared to its predecessor.