Hadoop 2.X
The extensive success of Hadoop 1.X in organizations also led to the understanding of its limitations, which are as follows:
- Hadoop gives unprecedented access to cluster computational resources to every individual in an organization. The MapReduce programming model is simple and supports a develop once deploy at any scale paradigm. This leads to users exploiting Hadoop for data processing jobs where MapReduce is not a good fit, for example, web servers being deployed in long-running map jobs. MapReduce is not known to be affable for iterative algorithms. Hacks were developed to make Hadoop run iterative algorithms. These hacks posed severe challenges to cluster resource utilization and capacity planning.
- Hadoop 1.X has a centralized job ...
Get Hadoop: Data Processing and Modelling now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
