Corpus ID: 27020051

A Big Data Hadoop Architecture for Online Analysis

@inproceedings{Naik2014ABD,
  title={A Big Data Hadoop Architecture for Online Analysis},
  author={Ramlal Naik},
  year={2014}
}
Big Data is a collection of data that is large or complex to process using on-hand database management tools or data processing applications. Big Data has recently become one of the issues important in the networking world. Hadoop is a distributed paradigm used to manipulate the large amount of data. This manipulation contains not only storage as well as processing on the data. Hadoop is normally used for data intensive applications. It actually holds the huge amount of data and upon… Expand

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References

SHOWING 1-2 OF 2 REFERENCES
Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters
TLDR
D-Streams support a new recovery mechanism that improves efficiency over the traditional replication and upstream backup solutions in streaming databases: parallel recovery of lost state across the cluster. Expand
Detecting DDoS attacks with Hadoop
TLDR
This work proposes a novel DDoS detection method based on Hadoop that implements a HTTP GET flooding detection algorithm in MapReduce on the distributed computing platform. Expand