This paper describes the use of Storm at Twitter. Storm is a realtime fault-tolerant and distributed stream data processing system. Storm is currently being used to run various critical computations in Twitter at scale, and in real-time. This paper describes the architecture of Storm and its methods for distributed scale-out and fault-tolerance. This paper also describes how queries (aka. topologies) are executed in Storm, and presents some operational stories based on running Storm at Twitter. We also present results from an empirical evaluation demonstrating the resilience of Storm in dealing with machine failures. Storm is under active development at Twitter and we also present some potential directions for future work.

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The international journal of neurocomputing (NC) is considered to be one of the most sought out journals in the computer science research fraternity. In this paper, an extensive bibliometric overview of this journal is performed. The bibliometric data is extracted from the Web of Science (WoS) repository. The main objective of this study is to reveal internal structures and hidden inferences, such as highly productive and influential authors, most contributing countries, top institutions, collaborating authors, and so on. The CiteSpace and VOS viewer is used to visualize the graphical mapping of the bibliometric data. Further, the document co-citations network, cluster detection and references with strong citation burst is analyzed to reveal the intellectual base of NC publications.