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teaching:infoh419 [2020/10/03 11:50] ezimanyi [Groups of the current year] |
teaching:infoh419 [2021/10/17 13:35] ezimanyi [Group Project] |
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The project of the course consist of 2 parts: | The project of the course consist of 2 parts: | ||
- | * Part I: Implement the TPC-DS benchmark (deadline 1/11/2020) | + | * Part I: Implement the TPC-DS benchmark (deadline 1/11/2021) |
- | * Part II: Implement the TPC-DI benchmark (deadline 20/12/2020) | + | * Part II: Implement the TPC-DI benchmark (deadline 24/12/2021) |
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 can be implemented with several scale factors, which determine the size of the resulting data warehouse. For the purposes of this project you can use the smallest scale factor. | + | 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 2 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. |
The deliverables expected for each part of the project are the following: | The deliverables expected for each part of the project are the following: | ||
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===== Groups of the current year ===== | ===== Groups of the current year ===== | ||
- | * MariaDB: Tatiana Millan | + | * SQL Server: Nicole Zafalón, Diogo Rapas, Andrés Espinal, Adam Broniewski |
- | * MySQL: Nada Elghazouani et Jean-Charles Nsangolo | + | * PostgreSQL: Niccolò Morabito, CHUN HAN LI, Víctor Diví, Filip Sotiroski |
- | * Oracle: Ali Dhanani and Cleis Kounalis | + | * mySQL: Valada kylynnyk, Yanjian Zhang, Zhicheng Lou, Kainaat Amjid |
- | * PostgreSQL: Florian Baudry and Nathan Wolper | + | * Oracle: El Achouchi Iliass, Belgada Wassim, Ajouaou Soufiane |
- | * SQL Server: Brahim Amssafi and Astrid Soumoy | + | * SQLite: Laamiri Achraf, Mareghni Nidhal, Kuete Kamta Frank Jordan |
- | * Apache Hive: Mohammed Belfarsi and Antoine De Selys Longchamps | + | * mariadb: Tejaswini Dhupad, Himanshu Choudhary, Kamdem Tagne Thomas Borel, Sergio Postigo |
+ | * Spark SQL: Yi Wu, Hang Yu, Zhiyang Guo, Mohammad Zain Abbas | ||
+ | * 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 | ||
+ | * ScylaDB: Nazgul K. Rakhimzhanova, Mohammad Ismail Tirmizi, Maël Touret, Wassim Kezai | ||
+ | * AWS Aurora: Hind Bakkali, Gaëlle Frauenkron, Mahmut Asım Onat, Salma Salmani | ||
+ | * Google BigQuery: Soufian El Bakkali Tamara, Maciej Piekarski, David Silberwasser, Sami Abdul Sater | ||
+ | * Impala: Yahya Bakkali, Amirmohammad Fallahi, Maxime Hauwaert, Alexandre Libert | ||
===== Examinations from Previous Years ===== | ===== Examinations from Previous Years ===== | ||