Introduction to Hadoop
Hadoop is a rapidly evolving ecosystem of components for
implementing the Google MapReduce algorithms in a scalable fashion on commodity
hardware. Hadoop enables users to store and process large volumes of data and
analyze it in ways not previously possible with less scalable solutions or standard
SQL-based approaches.
As an evolving technology solution, Hadoop design
considerations are new to most users and not common knowledge. As part of the Dell | Hadoop solution, Dell
has developed a series of best practices and architectural considerations to
use when designing and implementing
Hadoop solutions.
Hadoop is a highly scalable compute and storage
platform. While most users will not initially deploy servers numbered in the
hundreds or thousands, Dell recommends following the design principles that
drive large, hyper-scale deployments. This ensures that as you start with a
small Hadoop environment, you can easily scale that environment without rework
to existing servers, software,
deployment strategies, and network connectivity.
What is Hadoop good
for?
When the original MapReduce algorithms were released, and
Hadoop was subsequently developed around them, these tools were designed for specific uses. The
original use was for managing large data sets that needed to be easily searched. As time has progressed and as the
Hadoop ecosystem has evolved, several other specific uses have emerged for Hadoop as a powerful solution.
* Large Data Sets – MapReduce paired with
HDFS is a successful solution for storing large volumes of unstructured data.
* Scalable Algorithms
– Any algorithm that can scale to many
cores with minimal inter-process communication will be able to exploit the distributed
processing capability of Hadoop.http://www.hadooptrainingbangalore.in/contact/
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