A new fragments allocating method for join query in distributed database

References

[1] Cherniack M, Balakrishnan H, Balazinska M, Carney D, Çetintemel U, Xing Y, Zdonik S B. Scalable distributed stream processing. In: Proceedings of the Conference on Innovative Data Systems Research. 2003

[2] Kloudas K, Mamede M, Preguiça N, Rodrigues R. Pixida: optimizing data parallel jobs in wide-area data analytics. Proceedings of the VLDB Endowment, 2015, 9(2): 72–83

[3] Rupprecht L,Culhane W, Pietzuch P. Squirreljoin: network-aware distributed join processing with lazy partitioning. Proceedings of the VLDB Endowment, 2017, 10(11): 1250–1261

[4] Yi L, Shanbhag A A,Jindal A, Madden S R. AdaptDB: adaptive partitioning for distributed joins. Proceedings of the VLDB Endowment, 2017, 10(5): 589–600

[5] Li T, Xu Z, Tang T, Wang Y. Model-free control for distributed stream data processing using deep reinforcement learning. Proceedings of the VLDB Endowment, 2018, 11(6): 705–718

[6] Ammar K,Mcsherry F,Salihoglu S, Joglekar M. Distributed evaluation of subgraph queries using worstcase optimal lowmemory dataflows. Proceedings of the VLDB Endowment, 2018, 11(6): 691–704

[7] Kathuria T, Sudarshan S. Efficient and provable multi-query optimization. In: Proceedings of the 36th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems. 2017, 53–67

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature