Understanding Hadoop 2.0
In this post, we’ll explain the difference between Hadoop 1.0 and 2.0. After all, what is Hadoop 2.0? What is YARN?
For starters – what is Hadoop and what is 1.0? The Apache Hadoop project is the core of an entire ecosystem of projects. It consists of four modules (see here):
- Hadoop Common: The common utilities that support the other Hadoop modules.
- Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
- Hadoop YARN: A framework for job scheduling and cluster resource management.
- Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.
Hadoop 1.0 is based on the Hadoop .20.205 branch (it went 0.18 -> 0.19 -> 0.20 -> 0.20.2 -> 0.20.205 -> 1.0). Hard to follow? Check out this chart. Not hard for an open source developer, but obscure for an enterprise product – so everyone agreed to call 0.20.205 ’1.0′, the project having matured to that point.
Hadoop 2.0 is from the Hadoop 0.23 branch, with major components re-written to enable support for features like High Availability, and MapReduce 2.0 (YARN), and to enable Hadoop to scale out past 4,000 machines per cluster. Specifically, Hadoop 2.0 adds (see here):
- HDFS Federation – multiple, redundant namenodes acting in congress
- MapReduce NextGen aka YARN aka MRv2 – which transforms Hadoop into a full blown platform as a service. See here.
Hadoop 1.0 is rock-solid, Hadoop 2.0 is still in active development and is considered Alpha. Work continues to stabilize Hadoop 2.0, so stay tuned!