Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables

Hammad Alenezi; Janusz Getta; Tianbing Xia

doi:doi:10.11648/j.ajist.20261003.11

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Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables

Hammad Alenezi^*

, Janusz Getta

, Tianbing Xia

Published in American Journal of Information Science and Technology (Volume 10, Issue 3)

Received: 8 June 2026 Accepted: 22 June 2026 Published: 28 July 2026

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Abstract

Relational databases use physical design techniques such as indexing, clustering, and partitioning to improve performance without altering the logical schema seen by applications. This paper proposes nesting of persistent storage structures as a new physical optimisation technique. Related tables can be implemented as a single nested persistent storage structure, eliminating join operations when processing complex queries and removing redundant foreign key repetitions on the many side of the relationship. The paper describes two independent nesting strategies. The schema driven approach selects nesting candidates from the logical schema before any workload is known. This selection subject to storage optimisation and database organisation constraints, formulating the selection as a constrained maximum-weight branching problem. The workload driven approach determines nesting decisions subject to aggregate query processing frequencies, applying nesting transformations in descending order of join frequency. To preserve logical transparency, mapping metadata records each attribute's physical access path. The paper shows how SQL queries expressed over the logical schema can be automatically transformed into equivalent queries over the nested physical structures, keeping the nested representation hidden from applications. A prototype implementation in PostgreSQL on the TPC-H benchmark demonstrates the feasibility of the proposed approach and confirms that standard indexing techniques can recover the query performance overhead introduced by nesting. By reducing storage redundancy and eliminating join operations while remaining compatible with existing relational interfaces, the technique preserves the relational programming model.

Published in	American Journal of Information Science and Technology (Volume 10, Issue 3)
DOI	10.11648/j.ajist.20261003.11
Page(s)	82-100
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Physical Database Design, Schema Nesting, Join Elimination, Workload-driven Optimisation, Query Rewriting, Logical Transparency, Mapping Metadata

References

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APA Style

Alenezi, H., Getta, J., Xia, T. (2026). Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables. American Journal of Information Science and Technology, 10(3), 82-100. https://doi.org/10.11648/j.ajist.20261003.11

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ACS Style

Alenezi, H.; Getta, J.; Xia, T. Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables. Am. J. Inf. Sci. Technol. 2026, 10(3), 82-100. doi: 10.11648/j.ajist.20261003.11

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AMA Style

Alenezi H, Getta J, Xia T. Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables. Am J Inf Sci Technol. 2026;10(3):82-100. doi: 10.11648/j.ajist.20261003.11

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@article{10.11648/j.ajist.20261003.11,
  author = {Hammad Alenezi and Janusz Getta and Tianbing Xia},
  title = {Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables},
  journal = {American Journal of Information Science and Technology},
  volume = {10},
  number = {3},
  pages = {82-100},
  doi = {10.11648/j.ajist.20261003.11},
  url = {https://doi.org/10.11648/j.ajist.20261003.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20261003.11},
  abstract = {Relational databases use physical design techniques such as indexing, clustering, and partitioning to improve performance without altering the logical schema seen by applications. This paper proposes nesting of persistent storage structures as a new physical optimisation technique. Related tables can be implemented as a single nested persistent storage structure, eliminating join operations when processing complex queries and removing redundant foreign key repetitions on the many side of the relationship. The paper describes two independent nesting strategies. The schema driven approach selects nesting candidates from the logical schema before any workload is known. This selection subject to storage optimisation and database organisation constraints, formulating the selection as a constrained maximum-weight branching problem. The workload driven approach determines nesting decisions subject to aggregate query processing frequencies, applying nesting transformations in descending order of join frequency. To preserve logical transparency, mapping metadata records each attribute's physical access path. The paper shows how SQL queries expressed over the logical schema can be automatically transformed into equivalent queries over the nested physical structures, keeping the nested representation hidden from applications. A prototype implementation in PostgreSQL on the TPC-H benchmark demonstrates the feasibility of the proposed approach and confirms that standard indexing techniques can recover the query performance overhead introduced by nesting. By reducing storage redundancy and eliminating join operations while remaining compatible with existing relational interfaces, the technique preserves the relational programming model.},
 year = {2026}
}

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TY  - JOUR
T1  - Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables
AU  - Hammad Alenezi
AU  - Janusz Getta
AU  - Tianbing Xia
Y1  - 2026/07/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ajist.20261003.11
DO  - 10.11648/j.ajist.20261003.11
T2  - American Journal of Information Science and Technology
JF  - American Journal of Information Science and Technology
JO  - American Journal of Information Science and Technology
SP  - 82
EP  - 100
PB  - Science Publishing Group
SN  - 2640-0588
UR  - https://doi.org/10.11648/j.ajist.20261003.11
AB  - Relational databases use physical design techniques such as indexing, clustering, and partitioning to improve performance without altering the logical schema seen by applications. This paper proposes nesting of persistent storage structures as a new physical optimisation technique. Related tables can be implemented as a single nested persistent storage structure, eliminating join operations when processing complex queries and removing redundant foreign key repetitions on the many side of the relationship. The paper describes two independent nesting strategies. The schema driven approach selects nesting candidates from the logical schema before any workload is known. This selection subject to storage optimisation and database organisation constraints, formulating the selection as a constrained maximum-weight branching problem. The workload driven approach determines nesting decisions subject to aggregate query processing frequencies, applying nesting transformations in descending order of join frequency. To preserve logical transparency, mapping metadata records each attribute's physical access path. The paper shows how SQL queries expressed over the logical schema can be automatically transformed into equivalent queries over the nested physical structures, keeping the nested representation hidden from applications. A prototype implementation in PostgreSQL on the TPC-H benchmark demonstrates the feasibility of the proposed approach and confirms that standard indexing techniques can recover the query performance overhead introduced by nesting. By reducing storage redundancy and eliminating join operations while remaining compatible with existing relational interfaces, the technique preserves the relational programming model.
VL  - 10
IS  - 3
ER  -

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Author Information

Hammad Alenezi

School of Computing and Information Technology, University of Wollongong, Wollongong, Australia

Contact Email

http://orcid.org/0009-0005-3756-9481
Janusz Getta

School of Computing and Information Technology, University of Wollongong, Wollongong, Australia

Contact Email

http://orcid.org/0000-0001-6492-5641
Tianbing Xia

School of Computing and Information Technology, University of Wollongong, Wollongong, Australia

Contact Email

http://orcid.org/0000-0002-4520-5021

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APA Style

Alenezi, H., Getta, J., Xia, T. (2026). Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables. American Journal of Information Science and Technology, 10(3), 82-100. https://doi.org/10.11648/j.ajist.20261003.11

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ACS Style

Alenezi, H.; Getta, J.; Xia, T. Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables. Am. J. Inf. Sci. Technol. 2026, 10(3), 82-100. doi: 10.11648/j.ajist.20261003.11

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AMA Style

Alenezi H, Getta J, Xia T. Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables. Am J Inf Sci Technol. 2026;10(3):82-100. doi: 10.11648/j.ajist.20261003.11

Copy | Download

@article{10.11648/j.ajist.20261003.11,
  author = {Hammad Alenezi and Janusz Getta and Tianbing Xia},
  title = {Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables},
  journal = {American Journal of Information Science and Technology},
  volume = {10},
  number = {3},
  pages = {82-100},
  doi = {10.11648/j.ajist.20261003.11},
  url = {https://doi.org/10.11648/j.ajist.20261003.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20261003.11},
  abstract = {Relational databases use physical design techniques such as indexing, clustering, and partitioning to improve performance without altering the logical schema seen by applications. This paper proposes nesting of persistent storage structures as a new physical optimisation technique. Related tables can be implemented as a single nested persistent storage structure, eliminating join operations when processing complex queries and removing redundant foreign key repetitions on the many side of the relationship. The paper describes two independent nesting strategies. The schema driven approach selects nesting candidates from the logical schema before any workload is known. This selection subject to storage optimisation and database organisation constraints, formulating the selection as a constrained maximum-weight branching problem. The workload driven approach determines nesting decisions subject to aggregate query processing frequencies, applying nesting transformations in descending order of join frequency. To preserve logical transparency, mapping metadata records each attribute's physical access path. The paper shows how SQL queries expressed over the logical schema can be automatically transformed into equivalent queries over the nested physical structures, keeping the nested representation hidden from applications. A prototype implementation in PostgreSQL on the TPC-H benchmark demonstrates the feasibility of the proposed approach and confirms that standard indexing techniques can recover the query performance overhead introduced by nesting. By reducing storage redundancy and eliminating join operations while remaining compatible with existing relational interfaces, the technique preserves the relational programming model.},
 year = {2026}
}

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TY  - JOUR
T1  - Optimization of Query Processing Through Nested Persistent Storage Implementation of Relational Tables
AU  - Hammad Alenezi
AU  - Janusz Getta
AU  - Tianbing Xia
Y1  - 2026/07/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ajist.20261003.11
DO  - 10.11648/j.ajist.20261003.11
T2  - American Journal of Information Science and Technology
JF  - American Journal of Information Science and Technology
JO  - American Journal of Information Science and Technology
SP  - 82
EP  - 100
PB  - Science Publishing Group
SN  - 2640-0588
UR  - https://doi.org/10.11648/j.ajist.20261003.11
AB  - Relational databases use physical design techniques such as indexing, clustering, and partitioning to improve performance without altering the logical schema seen by applications. This paper proposes nesting of persistent storage structures as a new physical optimisation technique. Related tables can be implemented as a single nested persistent storage structure, eliminating join operations when processing complex queries and removing redundant foreign key repetitions on the many side of the relationship. The paper describes two independent nesting strategies. The schema driven approach selects nesting candidates from the logical schema before any workload is known. This selection subject to storage optimisation and database organisation constraints, formulating the selection as a constrained maximum-weight branching problem. The workload driven approach determines nesting decisions subject to aggregate query processing frequencies, applying nesting transformations in descending order of join frequency. To preserve logical transparency, mapping metadata records each attribute's physical access path. The paper shows how SQL queries expressed over the logical schema can be automatically transformed into equivalent queries over the nested physical structures, keeping the nested representation hidden from applications. A prototype implementation in PostgreSQL on the TPC-H benchmark demonstrates the feasibility of the proposed approach and confirms that standard indexing techniques can recover the query performance overhead introduced by nesting. By reducing storage redundancy and eliminating join operations while remaining compatible with existing relational interfaces, the technique preserves the relational programming model.
VL  - 10
IS  - 3
ER  -

Copy | Download