Tag-Partitioned Join

Jeong Uk KIM; Jae Moon LEE; Myunghwan KIM

Tag-Partitioned Join

Jeong Uk KIM, Jae Moon LEE, Myunghwan KIM

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A tag-partitioned join algorithm is described. The algorithm partitions only one relation, while other partition-based algorithms partition both relations. It is performed as the joinable tuples of one relation are rearranged and some of them are duplicated according to the original sequence of the join attribute values of the other relation. To do this, the algorithm first finds the positions of all the tuples of the other relation which are joinable with each tuple of one relation, and then partitions joinable tuples of one relation into buckets by using the positions found. Final joining is performed on the partitioned relation and the other relation. We analyze and compare the performance of the algorithm with that of other partition-based join algorithms. The comparison shows that our method is better than other partition-based methods under the practical values of the analysis parameters.

Publication: IEICE TRANSACTIONS on Information Vol.E75-D No.3 pp.291-297

Publication Date: 1992/05/25

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Type of Manuscript: PAPER

Category: Databases

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Jeong Uk KIM, Jae Moon LEE, Myunghwan KIM, "Tag-Partitioned Join" in IEICE TRANSACTIONS on Information, vol. E75-D, no. 3, pp. 291-297, May 1992, doi: .
Abstract: A tag-partitioned join algorithm is described. The algorithm partitions only one relation, while other partition-based algorithms partition both relations. It is performed as the joinable tuples of one relation are rearranged and some of them are duplicated according to the original sequence of the join attribute values of the other relation. To do this, the algorithm first finds the positions of all the tuples of the other relation which are joinable with each tuple of one relation, and then partitions joinable tuples of one relation into buckets by using the positions found. Final joining is performed on the partitioned relation and the other relation. We analyze and compare the performance of the algorithm with that of other partition-based join algorithms. The comparison shows that our method is better than other partition-based methods under the practical values of the analysis parameters.
URL: https://global.ieice.org/en_transactions/information/10.1587/e75-d_3_291/_p

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@ARTICLE{e75-d_3_291,
author={Jeong Uk KIM, Jae Moon LEE, Myunghwan KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Tag-Partitioned Join},
year={1992},
volume={E75-D},
number={3},
pages={291-297},
abstract={A tag-partitioned join algorithm is described. The algorithm partitions only one relation, while other partition-based algorithms partition both relations. It is performed as the joinable tuples of one relation are rearranged and some of them are duplicated according to the original sequence of the join attribute values of the other relation. To do this, the algorithm first finds the positions of all the tuples of the other relation which are joinable with each tuple of one relation, and then partitions joinable tuples of one relation into buckets by using the positions found. Final joining is performed on the partitioned relation and the other relation. We analyze and compare the performance of the algorithm with that of other partition-based join algorithms. The comparison shows that our method is better than other partition-based methods under the practical values of the analysis parameters.},
keywords={},
doi={},
ISSN={},
month={May},}

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TY - JOUR
TI - Tag-Partitioned Join
T2 - IEICE TRANSACTIONS on Information
SP - 291
EP - 297
AU - Jeong Uk KIM
AU - Jae Moon LEE
AU - Myunghwan KIM
PY - 1992
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E75-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - May 1992
AB - A tag-partitioned join algorithm is described. The algorithm partitions only one relation, while other partition-based algorithms partition both relations. It is performed as the joinable tuples of one relation are rearranged and some of them are duplicated according to the original sequence of the join attribute values of the other relation. To do this, the algorithm first finds the positions of all the tuples of the other relation which are joinable with each tuple of one relation, and then partitions joinable tuples of one relation into buckets by using the positions found. Final joining is performed on the partitioned relation and the other relation. We analyze and compare the performance of the algorithm with that of other partition-based join algorithms. The comparison shows that our method is better than other partition-based methods under the practical values of the analysis parameters.
ER -