Friday, May 15, 2015


11:41 PM - By ajay desai 0

                                              I   Node Failure

The computational job is divided into number of tasks and assigned to several computing nodes. So, if any one node fails, then the job cannot be completed till that node becomes live. Due to which, we have downtime.

                                              II  Data Loss

Sometimes the data stored by a node might get corrupted, which stops the entire processing job and results in down time.

                                            III  Network and Bandwidth Issues

In a distributed system, one node processes the data and intimates about its task completion  to the next successive node which then starts its processing work. If the nodes are not able to communicate due to network failure or due to less bandwidth, the entire computational job gets halted.

                                           IV Horizontal Scalability problems

Adding new nodes the existing group of computing nodes is very difficult as a lot of expensive hardware has to be used.

                                             V Slow Processing

As the computing nodes in a distributed system need to communicate with each other for proper synchronization and also manage node failures. It takes a lot of time to complete the processing job.

To resolve these issues, a new Technology called Hadoop was introduced in the market. Which is also a distributed system but quite different from the traditional distributed systems.


About the Author

I am Azeheruddin Khan having more than 6 year experience in c#, and ms sql.My work comprise of medium and enterprise level projects using and other Microsoft .net technologies. Please feel free to contact me for any queries via posting comments on my blog,i will try to reply as early as possible. Follow me @fresher2programmer
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