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Discretized streams
2013
Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles - SOSP '13
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Running these applications at ever-larger scales requires parallel platforms that automatically handle faults and stragglers. ...
We propose a new processing model, discretized streams (D-Streams), that overcomes these challenges. ...
Large-scale Streaming While several recent systems enable streaming computation with high-level APIs similar to D-Streams, they also lack the fault and straggler recovery benefits of the discretized stream ...
doi:10.1145/2517349.2522737
dblp:conf/sosp/ZahariaDLHSS13
fatcat:tndskypg6rfhta755bt5q2tk3e
Evaluating the impact of a coordinated checkpointing in distributed data streams processing systems using discrete event simulation
2020
Revista Brasileira de Computação Aplicada
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In this paper, we propose a discrete simulation model for investigating the impacts of the Coordinated Checkpoint fault tolerance strategy imposes on Data Stream Processing Systems. ...
To guarantee systems' dependability and avoid information loss, one must use a fault-tolerance strategy. ...
Nevertheless, practical evaluation of fault-tolerance mechanisms in large-scale applications such as DaSP systems is challenging. ...
doi:10.5335/rbca.v12i2.10295
fatcat:wg22iuzhebhwlhndgkztohz75y
Efficiency of Stream Processing Engines for Processing BIGDATA Streams
2016
Indian Journal of Science and Technology
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problems of Fault-Tolerance 10 , Faults & Stragglers within the second-scale latency, and maintain high-availability, data processed scalability with better performance of stream processing. ...
Keywords: Fault-Tolerance, RDD, Second-Scale Latency and Immutable Datasets, Stragglers
In-Memory Data Processing: The concept of in-memory data processing provides the high performance of complex event ...
doi:10.17485/ijst/2016/v9i14/84797
fatcat:dji434lx6nb4jdfyvwt63kn5qm
Consistent and efficient output-streams management in optimistic simulation platforms
2013
Proceedings of the 2013 ACM SIGSIM conference on Principles of advanced discrete simulation - SIGSIM-PADS '13
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vs CPU-bound behaviors at the application level. ...
At the same time, the delay for materializing the output stream (making it available for any type of audit activity) is shown to be fairly limited and constant, especially for good mixtures of I/O-bound ...
Still in the context of fault tolerance, the work in [11] presents an innovative protocol for supporting output commitment specifically aimed at promptly delivering output data, which is one of the target ...
doi:10.1145/2486092.2486133
dblp:conf/pads/AntonacciPQ13
fatcat:6zkvvdpdqvbxpgho4mpndoybb4
Maintaining balanced trees for structured distributed streaming systems
2017
Discrete Applied Mathematics
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Moreover, to minimize the delay of the streaming, the depth of the diffusion tree must also be controlled. ...
The motivation comes from live distributed streaming systems in which a source diffuses a content to peers via a tree, a node forwarding the data to its children. ...
The algorithm proposed in this paper aims at tolerating the high churn in a live distributed streaming system. ...
doi:10.1016/j.dam.2017.07.006
fatcat:gxlusd3ffba7vokpxuey3qobzy
Cloud-based data stream processing
2014
Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems - DEBS '14
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Specifically, we focus on novel approaches for (1) scalability and (2) fault tolerance in large scale distributed streaming systems. ...
In general, new fault tolerance mechanisms strive to be more robust and at the same time introduce less overhead. ...
Data streaming systems aimed at cloud platforms are no exception, and must thus be designed to efficiently cope with faults. Faults may appear in a data streaming system at several different places. ...
doi:10.1145/2611286.2611309
dblp:conf/debs/HeinzeAQJ14
fatcat:u67igik235fqdjngoraiukucr4
An Improved Stream Processing Access
2019
VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE
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Many real time streaming approaches are emerging to utilize or process large real-time data by replacing legacy centralized scenarios which are causing more memory utilization, delay and fault tolerance ...
In this paper we are focusing on improving stream processing techniques, limitations and future research directions for real-time stream processing ...
Some of the API's are lagging in terms of backpressure, flow control and time stamps, fault tolerance, state and memory utilization, stream partitioning and so on. ...
doi:10.35940/ijitee.k1147.09811s19
fatcat:hxbafhbeabbxpigf3mystx4h6m
The Stream Software Connector Design Space: Frameworks and Languages for Distributed Stream Processing
2014
2014 IEEE/IFIP Conference on Software Architecture
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On the other side, the gaps in the design space we identify point at future research directions in the area of distributed stream processing. ...
This paper introduces the design space of the stream software connector by analyzing recent stream processing engine frameworks and domain specific languages featuring native streaming support. ...
Design Issue: Fault Tolerance Fault tolerance is a very important aspect for a stream processing system. ...
doi:10.1109/wicsa.2014.42
dblp:conf/wicsa/BabazadehP14
fatcat:kkd7mmuglfh2desuhot2hjdviy
Fault Tolerance for Stream Processing Engines
[article]
2020
arXiv
pre-print
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2016 pre-print arXiv:1605.00928v1 fatcat:dbn5m35pvrbmvlsdghnonvtdfeOther Versions
Finally, we discuss implications of the fault tolerance techniques for different streaming application requirements. ...
We discuss fault tolerance techniques that are used in modern stream processing engines that are Storm, S4, Samza, SparkStreaming and MillWheel. ...
The set of computational slices defines a computational state of an operator, where each slice is a computationally-independent unit associated with the input stream. ...
arXiv:1605.00928v3
fatcat:kvdgebicrfbktogtew77mv7ppy
ChronoStream: Elastic stateful stream computation in the cloud
2015
2015 IEEE 31st International Conference on Data Engineering
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tenants. 1 add (remove) computing nodes in a system, aka scale out (in) 2 add (remove) resources at a single node in a system, aka scale up (down) ...
We introduce ChronoStream, a distributed system specifically designed for elastic stateful stream computation in the cloud. ...
Fault tolerance. Several authors have discussed possible fault-tolerance strategies for DSPS. As a pioneering team in exploring the stream database field, Hwang et al. ...
doi:10.1109/icde.2015.7113328
dblp:conf/icde/WuT15
fatcat:7l236mp4krgxljami3tptelkee
Scalable stateful stream processing for smart grids
2014
Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems - DEBS '14
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In addition, our solution is fault-tolerant, ensuring that the large processing state of stream operators is not lost after failure. ...
When we scale out the system, the time reduces linearly to 30 minutes before the system bottlenecks at the data source. ...
Naiad [10] can scale to many nodes but is not designed to be fault tolerant when the managed state is large. ...
doi:10.1145/2611286.2611326
dblp:conf/debs/FernandezWPG14
fatcat:3q2gnupre5ephi7tli6zzumkpe
Revenue Models for Streaming Applications over Shared Clouds
2012
2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications
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When multiple users execute their streaming applications over a shared Cloud infrastructure, the provider typically captures the Quality of Service (QoS) for each application at a Service Level Agreement ...
In this paper, we analyse revenue models for in-transit streaming applications, executed over a shared Cloud infrastructure under the presence of faulty computational resources. ...
Data streams in such applications are generally large-scale and distributed, and generated continuously at a rate that cannot be estimated in advance. ...
doi:10.1109/ispa.2012.67
dblp:conf/ispa/Tolosana-CalasanzBPR12
fatcat:wyhn76z2t5fobggwkm7qisvh7m
Distributed Streaming Analytics on Large-scale Oceanographic Data using Apache Spark
[article]
2019
arXiv
pre-print
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We also verify the fault tolerance by stopping nodes in the middle of a job and making sure that the job is rescheduled and completed on other nodes. ...
In this paper, we analyze large-scale geo-temporal data collected from the USGODAE (United States Global Ocean Data Assimilation Experiment) data catalog, and showcase and assess the ability of Spark stream ...
We measure performance of a system running streaming job with various node failures to access the fault tolerance capability of the Apache Spark streaming. ...
arXiv:1907.13264v2
fatcat:ubwr334mwre2pesjs6bdxn23ly
Autonomous, failure-resilient orchestration of distributed discrete event simulations
2013
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference on - CAC '13
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In this paper, we propose an autonomous agent that provides fault tolerance functionality for discrete event simulations by predicting state changes in the simulation and adjusting its fault tolerance ...
compared to conventional distributed fault tolerance schemes. ...
To our knowledge, this is the first attempt to incorporate fault tolerance into a discrete event simulation orchestrated using a stream processing engine. ...
doi:10.1145/2494621.2494625
dblp:conf/cac/MalensekSHP13
fatcat:gpiqqp76eraava2u7efefzwir4
Tolerating Transient Late-Timing Faults in Cloud-Based Real-Time Stream Processing
2016
2016 IEEE 19th International Symposium on Real-Time Distributed Computing (ISORC)
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However, such systems struggle with transient late-timing faults -a fault classification challenging to effectively tolerate -that manifests increasingly within large-scale distributed systems. ...
This work proposes a fault-tolerant approach for QoS-aware data prediction to tolerate transient late-timing faults. ...
[10] develop a new processing model termed discretized streams (D-Streams). The main objective is a scalable means to tolerate both faults and task stragglers. ...
doi:10.1109/isorc.2016.24
dblp:conf/isorc/GarraghanPOMM16
fatcat:szi7w7k3ybeoblsq5hmlrkaeim
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