Traditional Approach
In this approach, an enterprise will have a computer to store and
process big data. Here data will be stored in an RDBMS like Oracle
Database, MS SQL Server or DB2 and sophisticated softwares can be
written to interact with the database, process the required data and
present it to the users for analysis purpose.
Limitation
This approach works well where we have less volume of data that can
be accommodated by standard database servers, or up to the limit of the
processor which is processing the data. But when it comes to dealing
with huge amounts of data, it is really a tedious task to process such
data through a traditional database server.
Google’s Solution
Google solved this problem using an algorithm called MapReduce. This
algorithm divides the task into small parts and assigns those parts to
many computers connected over the network, and collects the results to
form the final result dataset.
Above diagram shows various commodity hardwares which could be single CPU machines or servers with higher capacity.
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