The Basics of Hadoop MapReduce v2, You need to know

Have you ever heard about Hadoop MapReduce? So, what is Hadoop MapReduce and Hadoop MapReduce v2? 

We are living in the era of big data, where exponential growth of phenomena such as web, social networking, smartphones, and so on are producing petabytes of data on a daily basis.

Hadoop v2 brings in several performance, scalability, and reliability improvements to HDFS. One of the most important among those is the High Availability (HA) support for the HDFS NameNode, which provides manual and automatic failover capabilities for the HDFS NameNode service. This solves the widely known NameNode single point of failure weakness of HDFS. Automatic NameNode high availability of Hadoop v2 uses Apache ZooKeeper for failure detection and for active NameNode election. Another important new feature is the support for HDFS federation. HDFS federation enables the usage of multiple independent HDFS namespaces in a single HDFS cluster. These namespaces would be managed by independent NameNodes, but share the DataNodes of the cluster to store the data. The HDFS federation feature improves the horizontal scalability of HDFS by allowing us to distribute the workload of NameNodes. Other important improvements of HDFS in Hadoop v2 include the support for HDFS snapshots, heterogeneous storage hierarchy support (Hadoop 2.3 or higher), in-memory data caching support (Hadoop 2.3 or higher), and many performance improvements. Almost all the Hadoop ecosystem data processing technologies utilize HDFS as the primary data storage. HDFS can be considered as the most important component of the Hadoop ecosystem due to its central nature in the Hadoop architecture.

The Basics of Hadoop MapReduce v2, You need to know