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Real-Time Big Data Analytics by Shilpi Saxena, Sumit Gupta

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Real-time processing

Now that we have talked so extensively about Big Data processing and Big Data persistence in the context of distributed, batch-oriented systems, the next obvious thing to talk about is real-time or near real-time processing. Big data processing processes huge datasets in offline batch mode. When real-time stream processing is executed on the most current set of data, we operate in the dimension of now or the immediate past; examples are credit card fraud detection, security, and so on. Latency is a key aspect in these analytics.

The two operatives here are velocity and latency, and that's where Hadoop and related distributed batch processing systems fall short. They are designed to deliver in batch mode and can't operate at ...

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