Actual problems of distributed data storage in RAM
DOI:
https://doi.org/10.18372/2073-4751.2.8938Keywords:
распределенное хранилище данных в оперативной памяти, распределенное объединение таблиц, консистентность данныхAbstract
Requirements for speed storage systems are constantly rising. For achievement ion query performance created storage in operative term memory. This article provides an overview of the technology of distributed data storage in RAM, as well as an analysis of the shortcomings of the existing implementations of such systems thatReferences
V. Turner. The digital universe of opportunities. Research & analysis by IDC // Infobrief of EMC corporation – 04.2014 – 16 p. Проблеми інформатизації та управління, 2(50)’2015 43
P. Boncz, S. Manegold, M. Ker-sten. Database architecture optimized for the new bottleneck: Memory access // VLDB journal – 12.2000 – P. 231-246.
H. Plattner. A common database approach for OLTP and OLAP using an in-memory column database // Proceedings of the 2009 ACM SIGMOD International Con-ference on Management of data – 2009 – P. 1-2.
Gupta M. K., Verma V., Verma M. S. In-Memory Database Systems - A Para-digm Shift. // International Journal of Engi-neering Trends and Technology (IJETT) – 12. 2013– P. 333-336.
R. Cattell. Scalable SQL and NoSQL Data Stores // SIGMOD Record – 12.2010 (Vol. 39, No. 4) – P. 12-27.
J. Gray. The Transaction Concept: Virtues and Limitations.// Proceedings of the 7th International Conference on Very Large Databases – 1981 – P. 144—154.
D. Pritchett. BASE: an ACID al-ternative // Queue - Object-Relational Map-ping Volume 6 Issue 3 – 06.2008 – P.48-55.
Williams, J.W., Aggour, K.S., In-terrante, J., McHugh, J., Pool, E. Bridging high velocity and high volume industrial big data through distributed in-memory storage & analytics. // Big Data, 2014 IEEE Interna-tional Conference on – 10. 2014 – P. 932 - 941.
N. Ivanov. In-Memory Database vs. In-Memory Data Grid: Revisited // GridGain Blog. [Электронный ресурс] –06.2014 – Режим доступа: http://gridgain.com/in-memory-database-vs-in-memory-data-grid-revisited.
K. Birman, D.Freedman, Q. Huang, P. Dowell. Overcoming CAP with consistent soft-state replication // IEEE Computer – 2012 – P. 50-58
P. Denning. Thrashing: Its causes and prevention // Proceedings AFIPS, Fall Joint Computer Conference – 1968 – P. 915–922
B. Babcock, S. Babu, M. Datar, R. Motwani, J. Widom. Models and issues in data stream systems // Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of data-base systems – 2002 – P. 1-16.
M.-C. Albutiu, A. Kemper, and T. Neumann. Massively parallel sort-merge joins in main memory multi-core database systems. // PVLDB, 5(10) –2012 – P. 1064-1075.
C. Balkesen et al. Multicore, main-memory joins: Sort vs hash revisited. // PVLDB, 7(1) – Sept. 2013 – P. 85-96.
O. Polychroniou, R. Sen and K. Ross. Track join: distributed joins with min-imal network traffic. // SIGMOD Conference – 2014 – P. 1483-1494.
О. Бузовский, А. Подрубайло. Методы и алгоритмы объединения таблиц в распределенных хранилищах данных в оперативной памяти // Вестник КПИ. Информатика, управление и вычислительная техника. Выпуск 60. – 01.2015 – С.73-83.
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