Ives ZG, Levy AY, Weld DS, Florescu D, Friedman M (2000) Adaptive Query Processing for Internet Applications. IEEE Data Engineering Bulletin 23:19--26  Home/Search   Document Details and Download   Summary   Related Articles   Check

....the remote relation 2 using the metrics associated with 22 , and the cost of any join operators involving 2 . For simplicity, we assume that the cost of the join is calculated based on the hash join implementation. We note that operators such as XJOIN [43, 44] or other adaptive operators [26, 25] would result in improved performance. Note that any join ordering of subgoals is possible for this pre plan and we assume that the best ordering will be chosen by the optimizer [50] 8 For the first pre plan, the pre optimizer will assume that the dependency corresponding to ( R 2 ) will ....

....will assume that the dependency corresponding to ( R 2 ) will lead to a top down dependent join evaluation [9] Again, for simplicity, the cost is calculated using the nested loop join implementation, using the metrics associated with 21 . Adaptive operators such as those proposed in [26, 25] and WSQ QSQ [18] would also improve performance in the actual plan. To correctly determine the cost, since 2 is the operand on the right subtree, we have to calculate the (output) cardinality of the left subtree tuples (that include relation 3 ) that join with 2 . We assume that the ....

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Z. Ives, A. Levy, D. Weld, D. Florescu, and M. Friedman. Adaptive query processing for internet applications. IEEE Data Engineering Bulletin, 23(2):19--26, 2000.

....the benefit of sophisticated heuristics over our simple approach. Our overall motivation, and specifically our focus on Web forms, is consistent with the extensive investigation of software or information agents (eg, the seminal ShopBot agent [4] and more recent data integration research (e.g. [7]) As far as we are aware, these agents all rely either on manual form annotation, or on hand crafted task specific form classification rules Probabilistic models involving unobserved latent random variables have been used in numerous diverse settings, such as classifying structured XML documents ....

Z. Ives, A. Levy, D. Weld, D. Florescu, and M. Friedman. Adaptive query processing for Internet applications. IEEE Data Engineering Bulletin, 23(2), 2000.

....query materialisation points for data reuse, and result approximation. Examples of this work are pipelined hash join [31] hash ripple join [14] and the Xjoin [29] Most of this work is with relational data and concerns aggregation queries as examples [1, 15] however some have looked at XML [17]. Nevertheless this work has been very focused and has not examined the complete database systems architecture. 3 Adaptive Data Management Architecture This section presents a general architecture to support adaptive data management. It is the basic framework used in the subsequent applications ....

Ives Z G., Levy A Y., Weld D. S., Florescu D., Friedman M. 'Adaptive Query Processing for Internet Applications'. IEEE Data Engineering Bulletin vol 23 no 2, pp 19-26, 2000

....that may produce di#erent query plans at any time in the future, in response to changes in the environment, while the present survey focuses on query processing techniques that can adapt to changing conditions during execution time. Also, 11] uses a very limited set of classification criteria. [14] extends this set by proposing some dimensions over which AQP systems may di#er. Other previous surveys on query optimisation, like [10, 12] include techniques that have a dynamic flavour, in the sense that the QP they produce at compile time is not completely fixed, but such techniques are not ....

.... [1, 2, 26] rem any no no dar trt in av inter D G A Pipeline Scheduler [25] op or PJ no no user pr irt dr user in intra D O A Bouganim et al. [6, 7] rem PJ maybe maybe dar mem fl trt dr mem av intra D O G A Conquest [16, 17] rem any yes yes any trt stats inter P G A Tukwila [13, 14] rem PJ maybe yes any trt irt stats inter D O G S Telegraph [11] op or parl no yes any trt stats l dr intra D O L S dQUOB [21, 22] op or no no no ac statstrt stats inter D L A Table 1. Properties of existing adaptive query processing techniques (PPHJs) is proposed in [20] Initially, ....

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Z. Ives, A. Levy, D. Weld, D. Florescu, and M. Friedman. Adaptive query processing for internet applications. IEEE Data Engineering Bulletin, 23(2):19--26, 2000.

....6 Related Work There has been some work on adaptive query processing. Examples of this work are pipelined hash join [9] hash ripple join [10] and the Xjoin [11] Most of this work is with relational data and concerns aggregation queries as examples [12, 10, 13] however some have looked at XML [14]. Nevertheless this work has been very focused and they do not provide the level of customisation supported by MAGNET. Contemporary research in mobile computing has explored problems with mobility and the unreliability of wireless communication networks [15] Fluctuations in quality of service ....

Ives Z G., Levy A Y., Weld D. S., Florescu D., Friedman M. `Adaptive Query Processing for Internet Applications'. IEEE Data Engineering Bulletin vol 23 no 2, pp 19-26, 2000

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Zachary G. Ives, Alon Y. Levy, Daniel S. Weld, Daniela Florescu, and Marc Friedman. Adaptive query processing for internet applications. IEEE Data Engineering Bulletin Special Issue on Adaptive Query Processing, 23(2), June 2000.

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Zachary Ives, Alon Levy, Dan Weld, Daniela Florescu, and Marc Friedman. Adaptive query processing for internet applications. Data Engineering Bulletin 23(3), 2000.

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Ives ZG, Levy AY, Weld DS, Florescu D, Friedman M (2000) Adaptive Query Processing for Internet Applications. IEEE Data Engineering Bulletin 23:19--26

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Z. G. Ives, A. Y. Levy, D. S. Weld, D. Florescu, and M. Friedman. Adaptive query processing for internet applications. In IEEE Data Engineering Bulletin, volume 23, June 2000.

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Ives, Z. G., Levy, A. Y., Weld, D. S., Florescu, D., Friedman, M.: Adaptive Query Processing for Internet Applications. IEEE Data Engineering Bulletin, Vol.23, No.2, pp.19-26, 2000.

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Zachary G. Ives, Alon Y. Levy, Daniel S. Weld, Daniela Florescu, and Marc Friedman. Adaptive Query Processing for Internet Applications. IEEE Data Engineering Bulletin, 2000.

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Z. G. Ives, A. Y. Levy, D. S. Weld, D. Florescu, and M. Friedman. Adaptive Query Processing for Internet Applications. IEEE Data Engineering Bulletin, 23(2):19-26, June 2000.

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Z. Ives, A. Levy, D. Weld, D. Florescu, and M. Friedman. Adaptive query processing for internet applications. Data Engineering Bulletin, 23(2), 2000.

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Z. Ives, A. Levy, D. Weld, D. Florescu, and M. Friedman. Adaptive query processing for internet applications. IEEE Data Engineering Bulletin, 23(2):19--26, 2000.

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