| [1] |
VEEN A H . Dataflow machine architecture[J]. ACM Computing Surveys, 1986,18(4): 365-396.
|
| [2] |
SRINI V P . An architectural comparison of dataflow systems[J]. IEEE Computer, 1986,19(3): 68-88.
|
| [3] |
DENNIS J B , MISUNAS D P . A preliminary architecture for a basic dataflow processor[C]// The 2nd Annual Symposium on Computer Architecture. New York:ACM Press, 1975: 126-132.
|
| [4] |
RUMBAUGH J . A data flow multiprocessor[J]. IEEE Transactions on Computers, 1977,26(2): 138-146.
|
| [5] |
DAVIS A L , . A data flow evaluation system based on the concept of recursive locality[C]// The 1979 International Workshop on Managing Requirements Knowledge. Piscataway:IEEE Press, 1979: 1079-1086.
|
| [6] |
MCSHERRY F , MURRAY D G , ISAACS R ,et al. Differential dataflow[C]// The 6th Biennial Conference on Innovative Data Systems Research.[S.l.:s.n. ], 2013.
|
| [7] |
MURRAY D G , MCSHERRY F , ISAACS R ,et al. Naiad:a timely dataflow system[C]// The 24th ACM Symposium on Operating Systems Principles. New York:ACM Press, 2013: 439-455.
|
| [8] |
ABADI M , BARHAM P , CHEN J ,et al. TensorFlow:a system for large-scale machine learning[C]// The 12th USENIX Symposium on Operating Systems Design and Implementation. Berkeley:USENIX Association, 2016: 265-283.
|
| [9] |
BONNA R , LOUBACH D S , UNGUREANU G ,et al. Modeling and simulation of dynamic applications using scenario-aware dataflow[J]. ACM Transactions on Design Automation of Electronic Systems, 2019,24(5): 1-29.
|
| [10] |
DEAN J , GHEMAWAT S . MapReduce:simplified data processing on large clusters[J]. Communications of the ACM, 2008,51(1): 107-113.
|
| [11] |
ZAHAR IA M , CHOWDHURY M , DAS T ,et al. Resilient distributed datasets:a fault-tolerant abstraction for in-memory cluster computing[C]// The 9th USENIX Conference on Networked Systems Design and Implementation. Berkeley:USENIX Association, 2012:2.
|
| [12] |
ZAHAR IA M , CHOWDHURY M , FRANKLIN M J ,et al. Spark:cluster computing with working sets[C]// The 2nd USENIX Workshop on Hot Topics in Cloud Computing. Berkeley:USENIX Association, 2010:10.
|
| [13] |
ZAHAR IA M , DAS T , LI H ,et al. Discretized streams:fault-tolerant streaming computation at scale[C]// The 24th Symposium on Operating Systems Principles. New York:ACM Press, 2013: 423-438.
|
| [14] |
ARMBR UST M , DAS T , TORRES J ,et al. Structured streaming:a declarative API for real-time applications in Apache Spark[C]// The 2018 International Conference on Management of Data. New York:ACM Press, 2018: 601-613.
|
| [15] |
ISARD M , BUDIU M , YU Y ,et al. Dryad:distributed data-parallel programs from sequential building blocks[C]// The 2007 EuroSys Conference. New York:ACM Press, 2007: 59-72.
|
| [16] |
TOSHN IWAL A , TANEJA S , SHUKLA A ,et al. Storm@twitter[C]// The 2014 ACM SIGMOD International Conference on Management of Data. New York:ACM Press, 2014: 147-156.
|
| [17] |
A KIDA U T , BALIKOV A , BEKIRO?LU K ,et al. MillWheel:fault-tolerant stream processing at internet scale[J]. Proceedings of the VLDB Endowment, 2013,6(11): 1033-1044.
|
| [18] |
NOGHABI S A , PARAMASIVAM K , PAN Y ,et al. Samza:stateful scalable stream processing at LinkedIn[J]. Proceedings of the VLDB Endowment, 2017,10(12): 1634-1645.
|
| [19] |
PATHIRAGE M , HYDE J , PAN Y ,et al. SamzaSQL:scalable fast data management with streaming SQL[C]// The 2016 IEEE International Parallel and Distributed Processing Symposium Workshops. Piscataway:IEEE Press, 2016: 1627-1636.
|
| [20] |
CARBO NE P , KATSIFODIMOS A , EWEN S ,et al. Apache Flink:stream and batch processing in a single engine[J]. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 2015,38(4): 28-38.
|
| [21] |
AKIDA U T , BRADSHAW R , CHAMBERS C ,et al. The dataflow model:a practical approach to balancing correctness,latency,and cost in massive-scale,unbounded,out-of-order data processing[J]. Proceedings of the VLDB Endowment, 2015,8(12): 1792-1803.
|
),周傲英
