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Adaptive join operators for result rate optimization on streaming inputs

Bornea Michaela A. , Vassalos, Vasilis, Kotidis, Yannis, Deligiannakis Antonios

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/87392F80-D45C-4024-870C-286C3D50BAD5-
Αναγνωριστικόhttp://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5453375&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5453375-
Αναγνωριστικόhttps://doi.org/10.1109/TKDE.2010.64-
Γλώσσαen-
Μέγεθος16 pagesen
ΤίτλοςAdaptive join operators for result rate optimization on streaming inputsen
ΔημιουργόςBornea Michaela A. en
ΔημιουργόςVassalos, Vasilisen
ΔημιουργόςKotidis, Yannisen
ΔημιουργόςDeligiannakis Antoniosen
ΔημιουργόςΔεληγιαννακης Αντωνιοςel
ΕκδότηςInstitute of Electrical and Electronics Engineersen
ΠερίληψηAdaptive join algorithms have recently attracted a lot of attention in emerging applications where data are provided by autonomous data sources through heterogeneous network environments. Their main advantage over traditional join techniques is that they can start producing join results as soon as the first input tuples are available, thus, improving pipelining by smoothing join result production and by masking source or network delays. In this paper, we first propose Double Index NEsted-loops Reactive join (DINER), a new adaptive two-way join algorithm for result rate maximization. DINER combines two key elements: an intuitive flushing policy that aims to increase the productivity of in-memory tuples in producing results during the online phase of the join, and a novel reentrant join technique that allows the algorithm to rapidly switch between processing in-memory and disk-resident tuples, thus, better exploiting temporary delays when new data are not available. We then extend the applicability of the proposed technique for a more challenging setup: handling more than two inputs. Multiple Index NEsted-loop Reactive join (MINER) is a multiway join operator that inherits its principles from DINER. Our experiments using real and synthetic data sets demonstrate that DINER outperforms previous adaptive join algorithms in producing result tuples at a significantly higher rate, while making better use of the available memory. Our experiments also shows that in the presence of multiple inputs, MINER manages to produce a high percentage of early results, outperforming existing techniques for adaptive multiway join.en
ΤύποςPeer-Reviewed Journal Publicationen
ΤύποςΔημοσίευση σε Περιοδικό με Κριτέςel
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-11-01-
Ημερομηνία Δημοσίευσης2010-
Θεματική ΚατηγορίαQuery processingen
Θεματική ΚατηγορίαPipeline processingen
Θεματική ΚατηγορίαSmoothing methodsen
Θεματική ΚατηγορίαSwitchesen
Θεματική ΚατηγορίαDelayen
Θεματική ΚατηγορίαProductionen
Θεματική ΚατηγορίαProductivityen
Θεματική ΚατηγορίαInformation processingen
Θεματική ΚατηγορίαAdaptive systemsen
Θεματική ΚατηγορίαAlgorithm design and analysisen
Βιβλιογραφική ΑναφοράM. A. Bornea, V. Vassalos, Y. Kotidis and A. Deligiannakis, "Adaptive join operators for result rate optimization on streaming inputs", IEEE Trans. Knowl. Data Eng., vol. 22, no. 8, pp. 1110-1125, Aug. 2010. doi:10.1109/TKDE.2010.64en

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