30-June-2013 - CAP Theorem

[Raj]

 

Definition of CAP Theorem:

C: Consistency

A: Availability

P: Partition Tolerance

These are three attributes of distributed system.

The system which require multiple machines or multiple nodes for communicating each other over network.

 

Consistency: It provides guarantee, eg. if I write in one node and read from other node it will return what I just wrote or most recent write because somebody else will writing at the same time - always receives something newer not older.

 

Availability: Every node (if not failed) always executes queries

 

Partition Tolerance: The system continues to operate despite arbitrary message loss or failure of part of the system. Guaranteed properties are maintained even when network failures prevent some machines from communicating with others.

 

According to the theorem, a distributed system cannot satisfy all three of these guarantees at the same time.

Some good description found at below URL:

http://foundationdb.com/white-papers/the-cap-theorem/

http://blog.beany.co.kr/archives/275

What is Data Intensive?
What is Computation Intensive?

[PAVAN KUMAR Reddy]

computation Intensive is a technology where we are moving of data to the processing system(where my processing code is eg: mapreduce), This is not reliable because I am sending

huge amount of data through network,

Chances of data corruption is very high.

Time to move data to processing engine is very high ( time to upload and download)

It requires expensive systems.

Eg: SAN, SETI@HOME

Data Intensive is a technology where we are moving our processing code near to data.

--
You received this message because you are subscribed to the Google Groups "HadoopOnlineTraining9" group.
To unsubscribe from this group and stop receiving emails from it, send an email to hadooponlinetrai...@googlegroups.com.
For more options, visit https://groups.google.com/groups/opt_out.
 
 

--

Thanks & Regards

Pavan Reddy .G