Difference between Hadoop 1 and Hadoop 2

Hadoop is an open-source framework from the Apache Software Foundation, built on Java, designed for storing and processing Big Data across distributed clusters. Apache released Hadoop 2 as a major upgrade over Hadoop 1, introducing YARN for resource management and support for multiple processing models beyond MapReduce.

Hadoop 1

Hadoop 1 uses a tightly coupled architecture where MapReduce handles both data processing and cluster resource management. It uses a single NameNode (single point of failure) and relies on fixed map/reduce task slots for resource allocation. Hadoop 1 only supports MapReduce as its processing model.

Hadoop 2

Hadoop 2 separates resource management from data processing by introducing YARN (Yet Another Resource Negotiator). This allows multiple processing frameworks (Spark, HBase, Giraph, MPI) to run alongside MapReduce on the same cluster. Hadoop 2 also introduces NameNode High Availability and Federation, eliminating the single point of failure.

Key Differences

Conclusion

Hadoop 2 is a major improvement over Hadoop 1, introducing YARN for flexible resource management, support for multiple processing frameworks beyond MapReduce, higher scalability, and NameNode high availability. Hadoop 1 is considered legacy and has been superseded by Hadoop 2 (and later Hadoop 3).