Zobrazeno 1 - 5
of 5
pro vyhledávání: '"ZHIXIANG KE"'
Publikováno v:
SCIENTIA SINICA Informationis. 50:1178-1196
Many distributed in-memory data-processing systems such as Flink and Spark suffer from serious memory issues, including limited memory resources shared by many users or groups, which aggravates the competition for memory resources. If a user applicat
Autor:
XUANHUA SHI1 xhshi@hust.edu.cn, ZHIXIANG KE1 zhxke@hust.edu.cn, YONGLUAN ZHOU2 zhou@di.ku.dk, HAI JIN1 hjin@hust.edu.cn, LU LU3 shiyi.ll@alibaba-inc.com, XIONG ZHANG1 wxzhang@hust.edu.cn, LIGANG HE4 liganghe@dcs.warwick.ac.uk, ZHENYU HU1 cszhenyuhu@hust.edu.cn, FEI WANG1 feiwg@hust.edu.cn
Publikováno v:
ACM Transactions on Computer Systems. Mar2019, Vol. 36 Issue 1, p1-47. 47p.
Autor:
Hai Jin, Yongluan Zhou, Lu Lu, Xiong Zhang, Ligang He, Fei Wang, Zhixiang Ke, Xuanhua Shi, Zhenyu Hu
Publikováno v:
Shi, X, Ke, Z, Zhou, Y, Jin, H, Lu, L, Zhang, X, He, L, Hu, Z & Wang, F 2019, ' Deca : a Garbage Collection Optimizer for In-memory Data Processing ', A C M Transactions on Computer Systems, vol. 36, no. 1, 3 . https://doi.org/10.1145/3310361
In-memory caching of intermediate data and active combining of data in shuffle buffers have been shown to be very effective in minimizing the recomputation and I/O cost in big data processing systems such as Spark and Flink. However, it has also been
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0088cd5c028787d7c10fc49207eeedb
http://wrap.warwick.ac.uk/119050/1/WRAP-Deca-garbage-collection-optimizer-in-memory-data-processing-He-2019.pdf
http://wrap.warwick.ac.uk/119050/1/WRAP-Deca-garbage-collection-optimizer-in-memory-data-processing-He-2019.pdf
Publikováno v:
HPCC/SmartCity/DSS
Data-parallel applications have become prevalent due to the fast development of big data technologies. The performances of these applications are obviously one of the most crucial indexes cared about, while program analysis is a commonly used approac
Publikováno v:
ICWS
Although a data processing system often works as a batch processing system, many enterprises deploy such a system as a service, which we call the service-oriented data processing system. It has been shown that in-memory data processing systems suffer