ABSTRACT
Today’s era of Big Data is witnessing a continuous increase of user and machine connectivity that produces an overwhelming ow of data that demands a paradigm shift in the computing architecture requirements and large-scale data-processing mechanisms. Therefore, concurrent computations have been receiving increased attention due to the widespread adoption of multicore processors and the emerging advancements of cloud computing technology. For example, the MapReduce framework has been introduced as a scalable and fault-tolerant data-processing framework that enables the processing of a massive volume of data in parallel on clusters of horizontally scalable commodity machines. By virtue of its simplicity, scalability, and fault-tolerance, MapReduce is becoming ubiquitous and gaining signicant momentum within both industry and academia. However, the MapReduce framework, opensourced by the Hadoop* Implementation, and its related large-scale data-processing technologies (e.g., Pig,† Hive‡) have been mainly designed for supporting batch processing tasks, but they are not adequate for supporting real-time stream processing
12.1 Introduction .................................................................................................. 389 12.2 Aurora ...........................................................................................................390 12.3 Borealis ......................................................................................................... 393 12.4 IBM System S and IBM Spade ..................................................................... 396 12.5 Deduce .......................................................................................................... 399 12.6 StreamCloud .................................................................................................400 12.7 Stormy ...........................................................................................................402 12.8 Twitter Storm ................................................................................................404 12.9 Conclusion ....................................................................................................407 References ..............................................................................................................407
