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teaching:infoh419 [2021/10/17 13:35] ezimanyi [Group Project] |
teaching:infoh419 [2022/09/19 11:25] ezimanyi [Books] |
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| ===== Books ===== | ===== Books ===== | ||
| - | * [[https://www.springer.com/9783642546549|Data Warehouse Systems: Design and Implementation]] by Alejandro A. Vaisman and Esteban Zimányi. Springer, 2014. | + | * [[https://link.springer.com/978-3-662-65167-4|Data Warehouse Systems: Design and Implementation]], second edition, Alejandro A. Vaisman and Esteban Zimányi. Springer, 2022. |
| * [[http://www.morganclaypool.com/doi/abs/10.2200/s00299ed1v01y201009dtm009|Multidimensional Databases and Data Warehousing]] by Cristian S. Jensen, Torben Bach Pedersen, and Christian Thomsen. Morgan & Claypool Publishers. | * [[http://www.morganclaypool.com/doi/abs/10.2200/s00299ed1v01y201009dtm009|Multidimensional Databases and Data Warehousing]] by Cristian S. Jensen, Torben Bach Pedersen, and Christian Thomsen. Morgan & Claypool Publishers. | ||
| * [[http://www.mcgraw-hill.co.uk/html/0071610391.html|Data Warehouse Design: Modern Principles and Methodologies]] by Matteo Golfarelli and Stefano Rizzi. McGraw-Hill, 2009 | * [[http://www.mcgraw-hill.co.uk/html/0071610391.html|Data Warehouse Design: Modern Principles and Methodologies]] by Matteo Golfarelli and Stefano Rizzi. McGraw-Hill, 2009 | ||
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| You have free choice to use the tools on which the two benchmarks will be implemented. For example, the TPC-DS benchmark could be implemented on SQL Server Analysis Services, Pentaho Analysis Services (aka Mondrian), etc. Similarly, the TPC-DI benchmark could be implemented on SQL Server Integration Services, Pentaho Data Integration, Talend Data Studio, SQL scripts, etc., which then load the data warehouse on a DBMS such as SQL Server, Oracle, PostgreSQL, etc. | You have free choice to use the tools on which the two benchmarks will be implemented. For example, the TPC-DS benchmark could be implemented on SQL Server Analysis Services, Pentaho Analysis Services (aka Mondrian), etc. Similarly, the TPC-DI benchmark could be implemented on SQL Server Integration Services, Pentaho Data Integration, Talend Data Studio, SQL scripts, etc., which then load the data warehouse on a DBMS such as SQL Server, Oracle, PostgreSQL, etc. | ||
| - | Furthermore, both benchmarks must be implemented with several scale factors, which determine the size of the resulting data warehouse. You DO NOT need to use the scale factors mentioned in the TPC requirements. The pedagogical objectives aimed at is that you learn how to properly perform a benchmark. Therefore, you need to estimate the biggest scale factor that you can put on your own computer: this will be your reference scale factor (SF), say SF 1.0, and then you will need to have 3 smaller scale factors, e.g., at 0.1, 0.2, and 0.5 of the full size in order to see the evolution of the performance. | + | Furthermore, both benchmarks must be implemented with several scale factors, which determine the size of the resulting data warehouse. You DO NOT need to use the scale factors mentioned in the TPC requirements. The pedagogical objectives aimed at is that you learn how to properly perform a benchmark. Therefore, you need to estimate the biggest scale factor that you can put on your own computer: this will be your reference scale factor, say 1.0, and then you will need to have 3 smaller scale factors, e.g., at 0.1, 0.2, and 0.5 of the full size in order to see the evolution of the performance. |
| The project is carried out in groups of 3-4 persons, which will be the same for the two parts. Before you can submit part I of the project, you will have to register in a group. For this, please send an email to the lecturer with the information about your group by 1/10/2020 at the latest. The submission deadlines for parts I and II are strict. | The project is carried out in groups of 3-4 persons, which will be the same for the two parts. Before you can submit part I of the project, you will have to register in a group. For this, please send an email to the lecturer with the information about your group by 1/10/2020 at the latest. The submission deadlines for parts I and II are strict. | ||
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| * DB2/Airflow: Md Jamiur Rahman Rifat, Khushnur Binte Jahangir, Asha Said Seif, Pietro Ferrazzi | * DB2/Airflow: Md Jamiur Rahman Rifat, Khushnur Binte Jahangir, Asha Said Seif, Pietro Ferrazzi | ||
| * Microsoft Azure SQL: Davide Rendina, Marita Hernandez, Luiz Fonseca, Zyrako Musaj | * Microsoft Azure SQL: Davide Rendina, Marita Hernandez, Luiz Fonseca, Zyrako Musaj | ||
| - | * ScylaDB: Nazgul K. Rakhimzhanova, Mohammad Ismail Tirmizi, Maël Touret, Wassim Kezai | + | * Citus: Nazgul K. Rakhimzhanova, Mohammad Ismail Tirmizi, Maël Touret, Wassim Kezai |
| * AWS Aurora: Hind Bakkali, Gaëlle Frauenkron, Mahmut Asım Onat, Salma Salmani | * AWS Aurora: Hind Bakkali, Gaëlle Frauenkron, Mahmut Asım Onat, Salma Salmani | ||
| * Google BigQuery: Soufian El Bakkali Tamara, Maciej Piekarski, David Silberwasser, Sami Abdul Sater | * Google BigQuery: Soufian El Bakkali Tamara, Maciej Piekarski, David Silberwasser, Sami Abdul Sater | ||