Aufnahme Bib
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@ -53,6 +53,9 @@ Hierbei ist auch ein Vergleich mit anderen Technologien angedacht.
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% Anm: (dazu schreiben Sie gar nichts!) Genau das ist Ihre Aufgabe im Rahmen des Reading Courses die aktuelle Literatur - sei es in der Forschung, in Lehrbüchern, in
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% Systemliteratur etc. zum Thema Performance-Optimierung zu recherchieren, zu analysieren und den State of the Art zu beschreiben!
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% Aktell 3546-1.pdf Page 404
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\section{Vorgehen bei der Umsetzung}
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% Anm: eine mögliche Vorgehensweise. Bei der Beschreibung der Vorgehensweise beziehen Sie sich dann natürlich auf den oben beschrieben Stand in Forschung und Technik
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Zuerst werden alle Abfragen ermittelt und deren Performance in Abhängigkeit der Häufigkeit der Aufrufe und Datenmengen
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@ -1,21 +1,25 @@
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% Bibtex Gen: https://www.literatur-generator.de/info/bibtex
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% File: 3035918.3064053.pdf
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@inproceedings{10.1145/3035918.3064053,
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author = {Walenz, Brett and Roy, Sudeepa and Yang, Jun},
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title = {Optimizing Iceberg Queries with Complex Joins},
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year = {2017},
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isbn = {9781450341974},
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publisher = {Association for Computing Machinery},
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address = {New York, NY, USA},
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url = {https://doi.org/10.1145/3035918.3064053},
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doi = {10.1145/3035918.3064053},
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abstract = {Iceberg queries, commonly used for decision support, find groups whose aggregate values are above or below a threshold. In practice, iceberg queries are often posed over complex joins that are expensive to evaluate. This paper proposes a framework for combining a number of techniques---a-priori, memoization, and pruning---to optimize iceberg queries with complex joins. A-priori pushes partial GROUP BY and HAVING condition before a join to reduce its input size. Memoization caches and reuses join computation results. Pruning uses cached results to infer that certain tuples cannot contribute to the final query result, and short-circuits join computation. We formally derive conditions for correctly applying these techniques. Our practical rewrite algorithm produces highly efficient SQL that can exploit combinations of optimization opportunities in ways previously not possible. We evaluate our PostgreSQL-based implementation experimentally and show that it outperforms both baseline PostgreSQL and a commercial database system.},
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booktitle = {Proceedings of the 2017 ACM International Conference on Management of Data},
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pages = {1243–1258},
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numpages = {16},
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keywords = {postgresql, iceberg, query optimization, databases, iceberg queries},
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location = {Chicago, Illinois, USA},
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series = {SIGMOD '17}
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author = {Walenz, Brett and Roy, Sudeepa and Yang, Jun},
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title = {Optimizing Iceberg Queries with Complex Joins},
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year = {2017},
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isbn = {9781450341974},
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publisher = {Association for Computing Machinery},
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address = {New York, NY, USA},
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url = {https://doi.org/10.1145/3035918.3064053},
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doi = {10.1145/3035918.3064053},
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abstract = {Iceberg queries, commonly used for decision support, find groups whose aggregate values are above or below a threshold. In practice, iceberg queries are often posed over complex joins that are expensive to evaluate. This paper proposes a framework for combining a number of techniques---a-priori, memoization, and pruning---to optimize iceberg queries with complex joins. A-priori pushes partial GROUP BY and HAVING condition before a join to reduce its input size. Memoization caches and reuses join computation results. Pruning uses cached results to infer that certain tuples cannot contribute to the final query result, and short-circuits join computation. We formally derive conditions for correctly applying these techniques. Our practical rewrite algorithm produces highly efficient SQL that can exploit combinations of optimization opportunities in ways previously not possible. We evaluate our PostgreSQL-based implementation experimentally and show that it outperforms both baseline PostgreSQL and a commercial database system.},
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booktitle = {Proceedings of the 2017 ACM International Conference on Management of Data},
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pages = {1243–1258},
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numpages = {16},
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keywords = {postgresql, iceberg, query optimization, databases, iceberg queries},
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location = {Chicago, Illinois, USA},
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series = {SIGMOD '17}
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},
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% Website
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@online{EffwFrankWedekind,
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author = {AK Prof. Dr. Ariane Martin},
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title = {Frank Wedekind | FB 05 - AK Prof. Dr. Ariane Martin},
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@ -23,4 +27,69 @@ series = {SIGMOD '17}
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comment = {http://web.archive.org/web/20230405061538/https://www.martin.germanistik.uni-mainz.de/forschung/frank-wedekind/},
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url = {https://www.martin.germanistik.uni-mainz.de/forschung/frank-wedekind/},
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urldate = {2023-09-24}
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},
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% File: 978-1-4842-3546-1.pdf
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@BOOK{Sharan2018,
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AUTHOR = {Sharan, Kishori},
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YEAR = {2018},
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TITLE = {Java APIs, Extensions and Libraries - With JavaFX, JDBC, jmod, jlink, Networking, and the Process API},
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EDITION = {},
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ISBN = {978-1-484-23546-1},
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PUBLISHER = {Apress},
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ADDRESS = {New York},
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},
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% File: 978-1-4842-6885-8.pdf
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@BOOK{Winand2012,
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AUTHOR = {Winand, Markus},
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YEAR = {2012},
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TITLE = {SQL Performance Explained - alles, was Entwickler über SQL-Performance wissen müssen ; [für alle gängigen SQL-Datenbanken]},
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EDITION = {},
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ISBN = {978-3-950-30781-8},
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PUBLISHER = {M. Winand},
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ADDRESS = {},
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},
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% File: 978-1-4842-8992-1.pdf
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@BOOK{Royal2022,
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AUTHOR = {Royal, Peter},
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YEAR = {2022},
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TITLE = {Building Modern Business Applications ; Reactive Cloud Architecture for Java, Spring, and PostgreSQL},
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EDITION = {},
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ISBN = {978-1-4842-8991-4},
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PUBLISHER = {Apress Berkeley, CA},
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ADDRESS = {New York},
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}
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% File: fröhlich-2022-postgresql.pdf / Ehemalinger Link: doi:10.3139/9783446473157
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@book{Fröhlich2022,
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author = {Fröhlich, Lutz},
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title = {PostgreSQL},
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publisher = {Carl Hanser Verlag GmbH \& Co. KG},
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year = {2022},
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doi = {10.3139/9783446473157},
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address = {München},
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edition = {},
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URL = {https://www.hanser-elibrary.com/doi/abs/10.3139/9783446473157},
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eprint = {https://www.hanser-elibrary.com/doi/pdf/10.3139/9783446473157}
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}
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% File: müller-wehr-2012-java-persistence-api-2.pdf / Ehemaliger Link: doi:10.3139/9783446431294
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@book{MüllerWehr2012,
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author = {Müller, Bernd and Wehr, Harald},
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title = {Java Persistence API 2},
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publisher = {Carl Hanser Verlag GmbH \& Co. KG},
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year = {2012},
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doi = {10.3139/9783446431294},
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address = {München},
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edition = {},
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URL = {https://www.hanser-elibrary.com/doi/abs/10.3139/9783446431294},
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eprint = {https://www.hanser-elibrary.com/doi/pdf/10.3139/9783446431294}
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}
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% noch offen:
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% - OpenJPA: https://openjpa.apache.org/documentation.html
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% - IBN OpenJPA Cache: https://www.ibm.com/docs/de/was/8.5.5?topic=applications-configuring-openjpa-caching-improve-performance
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% File: postgresql-15-A4.pdf
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