Abstract
Massive Data Stream (MDS) is one research section of Big Data. The data streams which have large velocity are also known as Elephant Flows. The challenges of Velocity, as per Gartner’s definition, are addressed. This paper proposes an algorithm that handles and processes Massive Data Streams. The Service Oriented Architecture (SOA) is used to capture and process massive data at higher velocity. Three types of parallel task running strategies are explored for the use in SOA. The error is adjustable according to available memory for getting more accurate results. The results show that 99% confidence is achieved at the cost of hyper-logarithmic space in memory.
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