Hadoop 1.x Limitations

Hadoop 1.x has many limitations or drawbacks. Main drawback of Hadoop 1.x is that MapReduce Component in it’s Architecture. That means it supports only MapReduce-based Batch/Data Processing Applications.

Hadoop 1.x has the following Limitations/Drawbacks:

  1. Only one NameNode is possible to configure i.e If NameNode fails entire cluster goes down, that is why NameNode is called as Single Point of Failure (SPOF)
  2. Secondary NameNode was just to take hourly backup of MetaData from NameNode.
    • Lets say SecondaryNameNode has taken backup at 10:00 AM, 10:45 NameNode fails then the transaction done during 10:00 to 10:45 is gone.
  3. It is only suitable for Batch Processing of Huge amount of Data, which is already in Hadoop System.
  4. It is not suitable for Real-time Data Processing.
  5. It supports upto 4000 Nodes per Cluster.
  6. It has a single component : JobTracker to perform many activities like Resource Management, Job Scheduling, Job Monitoring, Re-scheduling Jobs etc.
  7. JobTracker is the single point of failure.
  8. It supports only one Name Node and One Namespace per Cluster.
  9. It does not support Horizontal Scalability of NameNode.
  10. It runs only Map/Reduce jobs..

Naveen P.N

12+ years of experience in IT with vast experience in executing complex projects using Java, Micro Services , Big Data and Cloud Platforms. I found NPN Training Pvt Ltd a India based startup to provide high quality training for IT professionals. I have trained more than 3000+ IT professionals and helped them to succeed in their career in different technologies. I am very passionate about Technology and Training. I have spent 12 years at Siemens, Yahoo, Amazon and Cisco, developing and managing technology.