Building Real-Time Systems Using HBase

doi:https://doi.org/10.1007/978-1-4302-4864-4_14

Book Chapter10.1007/978-1-4302-4864-4_14

Building Real-Time Systems Using HBase

Sameer Wadkar,Madhu Siddalingaiah-2014-01-01-Apress eBooks

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TL;DRAbstract

So far in this book, you have studied MapReduce and its derivative APIs. You learned about batch processes that emphasize throughput (the amount of work done per unit of time) over latency (the response time). Hadoop jobs can take hours to run, but the amount of work done per unit time is phenomenal. Yet there are use-cases for which response time is important. When a Facebook user posts a comment, it is sent as a notification to all the friends. This function needs to happen in near–real time, and it would not be ideal to have to wait until the end of the day for a batch job to execute to get these notifications.

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So far in this book, you have studied MapReduce and its derivative APIs. You learned about batch processes that emphasize throughput (the amount of work done per unit of time) over latency (the response time). Hadoop jobs can take hours to run, but the amount of work done per unit time is phenomenal. Yet there are use-cases for which response time is important. When a Facebook user posts a comment, it is sent as a notification to all the friends. This function needs to happen in near–real time, and it would not be ideal to have to wait until the end of the day for a batch job to execute to get these notifications.

Keywords

Computer scienceLatency (audio)Response timeWork timeFunction (biology)Work (physics)ThroughputIdeal (ethics)

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