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Anomaly detection for NILM task with Apache Flink
Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems, 2020The topic of the 2020 DEBS Grand Challenge is to develop a solution for Non Intrusive Load Monitoring (NILM). Sensors continuously send voltage and current data into a stream processing application that would detect the pattern of power data based on the data characteristics.
Zongshun Zhang, Ethan Timoteo Go
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Code Generation in Serializers and Comparators of Apache Flink
Proceedings of the 12th Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems, 2017There is a shift in the Big Data world. Applications used to be I/O bound. InfiniBand, SSDs reduced the I/O overhead and more sophisticated algorithms were developed. CPU became a bottleneck for some applications. Using state of the art CPUs, reduced CPU usage can lead to reduced electricity costs even when an application is I/O bound.Apache Flink is ...
Gábor Horváth 0005 +2 more
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Analyzing extended property graphs with Apache Flink
Proceedings of the 1st ACM SIGMOD Workshop on Network Data Analytics, 2016Graphs are an intuitive way to model complex relationships between real-world data objects. Thus, graph analytics plays an important role in research and industry. As graphs often reflect heterogeneous domain data, their representation requires an expressive data model including the abstraction of graph collections, for example, to analyze communities ...
Martin Junghanns +4 more
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An Efficient Topology Refining Scheme for Apache Flink
2018 International Conference on Information and Communication Technology Convergence (ICTC), 2018In the past decade, there has been a boom in the volume of data and in the popularity of cloud applications with industry and academia keenly interested in big data analytics, streaming application, and social networking applications. This led to the emergence of real-time distributed stream processing systems such as Flink, Storm, Dataflow, and Samza.
Muhammad Hanif 0003, Choonhwa Lee
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Active replication for latency-sensitive stream processing in Apache Flink
2021 40th International Symposium on Reliable Distributed Systems (SRDS), 2021 Stream processing frameworks allow processing massive amounts of data shortly after it is produced, and enable a fast reaction to events in scenarios such as data center monitoring, smart transportation, or telecommunication networks.
Guillaume Rosinosky +5 more
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On the usability of Hadoop MapReduce, Apache Spark & Apache flink for data science
2017 IEEE International Conference on Big Data (Big Data), 2017Distributed data processing platforms for cloud computing are important tools for large-scale data analytics. Apache Hadoop MapReduce has become the de facto standard in this space, though its programming interface is relatively low-level, requiring many implementation steps even for simple analysis tasks.
Bilal Akil, Ying Zhou, Uwe Röhm
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Solving the 2021 DEBS grand challenge using Apache Flink
Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems, 2021The DEBS Grand Challenge is an annual event in which different event-based systems compete to solve a real-world problem. For the year 2021, the challenge is computing information given air quality sensor data. Due to the pandemic many factories are forced to close down, and the aim is to find out the cities that have improved the most in air quality ...
Mina Morcos +2 more
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Disaggregated State Management in Apache Flink® 2.0
Proceedings of the VLDB EndowmentWe present Apache Flink 2.0, an evolution of the popular stream processing system's architecture that decouples computation from state management. Flink 2.0 relies on a remote distributed file system (DFS) for primary state storage and uses local disks as a secondary cache, with state updates streamed continuously and directly to the DFS.
Yuan Mei +9 more
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A Parallel Algorithm for Tracking Dynamic Communities based on Apache Flink
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 2018Real world social networks are highly dynamic environments consisting of numerous users and communities, rendering the tracking of their evolution a challenging problem. In this work, we propose a parallel algorithm for tracking dynamic communities between consecutive timeframes of the social network, where communities are represented as undirected ...
Georgios Kechagias +3 more
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