Hadoop 2.7 3

Apache Hadoop 2.7 and Apache Hadoop 3 are two different major versions of the Hadoop framework. Each of these versions introduced various changes, improvements, and new features. Here’s a comparison between Hadoop 2.7 and Hadoop 3:

Hadoop 2.7:

1. Stability: Hadoop 2.7 is considered a stable and mature release of the Hadoop 2.x series. It was widely used in production environments and had undergone significant testing and improvements.

2. Resource Management: Hadoop 2.7 introduced YARN (Yet Another Resource Negotiator), which decoupled resource management and job scheduling from the MapReduce framework. YARN allowed the execution of various data processing frameworks beyond MapReduce, making Hadoop more versatile.

3. HDFS Federation: Hadoop 2.7 supported HDFS Federation, which allowed multiple namespaces (namespaces are logical subdivisions of HDFS) to coexist within a single HDFS cluster. This feature improved scalability and management of large Hadoop clusters.

4. High Availability (HA): Hadoop 2.7 continued to improve the high availability of the Hadoop ecosystem components, including the HDFS NameNode. It introduced features like Quorum-based storage for HA, reducing the chances of NameNode failover failures.

5. Security: Hadoop 2.7 improved security features, including support for Access Control Lists (ACLs), encryption, and Kerberos authentication.

Hadoop 3:

1. Erasure Coding: Hadoop 3 introduced support for erasure coding in HDFS as an alternative to traditional 3x replication. Erasure coding reduces storage overhead while maintaining data durability.

2. GPU Support: Hadoop 3 added support for running GPU-accelerated tasks in YARN containers, enabling the use of GPUs for accelerating machine learning and data processing workloads.

3. YARN Timeline Service v.2: The YARN Timeline Service was overhauled and introduced as version 2. It provided improved support for fine-grained resource tracking and application history.

4. Native Azure Data Lake Support: Hadoop 3 included native support for Microsoft Azure Data Lake Storage (ADLS), allowing Hadoop to interact seamlessly with Azure data services.

5. Shell Script Rewrite: The Hadoop shell script (hadoop command) was rewritten in Hadoop 3, offering better consistency and usability across different environments.

6. Performance Improvements: Hadoop 3 incorporated various performance enhancements and optimizations across different components of Hadoop, including HDFS, MapReduce, and YARN.

7. Enhanced Hadoop Docker Support: Hadoop 3 improved support for running Hadoop components in Docker containers, making it easier to set up and manage Hadoop clusters using containerization.