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teaching:infoh419 [2022/09/20 12:17] ezimanyi [Groups of the current year] |
teaching:infoh419 [2023/11/20 16:18] ezimanyi [Groups of the current year] |
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| The course is given during the first semester | The course is given during the first semester | ||
| - | * Lectures on Mondays from 10 am to 12 pm at the room S.K.3.401 | + | * Lectures on Mondays from 10 am to 12 pm at the room S.C.3.122 |
| - | * Exercises on Tuesdays from 2 pm to 4 pm at the room S.P4.1.17 | + | * Exercises on Tuesdays from 2 pm to 4 pm at the room S.UB4.136 |
| ===== Grading ===== | ===== Grading ===== | ||
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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 1/11/2022) | + | * Part I: Implement the TPC-DS benchmark (deadline 1/11/2023) |
| - | * Part II: Implement the TPC-DI benchmark (deadline 24/12/2022) | + | * Part II: Implement the TPC-DI benchmark (deadline 24/12/2023) |
| 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, 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. | 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 1/10/2022 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 1/10/2023 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: | ||
| Line 114: | Line 114: | ||
| ===== Groups of the current year ===== | ===== Groups of the current year ===== | ||
| + | * SQL Server: Enxhi Nushi, Gabriel Octavio Lozano Pinzón, Gian Carlo Tejada Gargate, José Carlos Lozano Dibildox | ||
| + | * PostgreSQL: Dionisius Mayr, Jakub Kwiatkowski, Gabriela Kaczmarek, Arijit | ||
| + | * Apache Hive: Yutao Chen, Qianyun Zhuang, Min Zhang, Ziyong Zhang | ||
| + | * Spark SQL: Valerio Rocca, Alexandre Dubois, Arnaud Cools, Maria Camila Salazar | ||
| + | * MySQL: Aryan Gupta, Dilbar Isakova, Hareem Raza, Muhammad Qasim Khan | ||
| + | * DuckDB: Jintao Ma, Linhan Wang, Iyoha Peace Osamuyi, Hieu Nguyen | ||
| + | * Oracle and Pentaho Data Integration: Sony Shrestha, Aayush Paudel, MD Kamrul Islam, Shofiyyah Nadhiroh | ||
| + | * Amazon Redshift: Rana İşlek, Simon Coessens, Berat Furkan Koçak, David García Morillo | ||
| + | * MariaDB: Izmar Soumaya, Ayadi Mustapha, Nils van Es Ostos, Narmina Mahmudova | ||
| + | * SQLite: Benjamin Gold, François Diximier, Noah Laravine, Louai Bouzaher | ||
| + | * DB2: Nicolas Lermusiaux, Gaetan Poupart-Lafarge, Ozan Basaran, Onur Bacaksiz | ||
| + | |||
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| + | |||
| + | /* | ||
| * Spark SQL: Luis Alfredo Leon, Satria Bagus Wicaksono, Jezuela Gega, Isabella Forero | * Spark SQL: Luis Alfredo Leon, Satria Bagus Wicaksono, Jezuela Gega, Isabella Forero | ||
| * MySQL: Ali AbuSaleh, Liliia Aliakberova, Muhammad Rizwan Khalid, Mariana Mayorga Llano | * MySQL: Ali AbuSaleh, Liliia Aliakberova, Muhammad Rizwan Khalid, Mariana Mayorga Llano | ||
| * PostgreSQL: Mir Wise Khan, Rishika Gupta, Ahmad, Chidiebere Ogbuchi | * PostgreSQL: Mir Wise Khan, Rishika Gupta, Ahmad, Chidiebere Ogbuchi | ||
| * Oracle: Sayyor Yusupov, Nikola Ivanović, Bogdana Živković, Jose Antonio Lorencio Abril | * Oracle: Sayyor Yusupov, Nikola Ivanović, Bogdana Živković, Jose Antonio Lorencio Abril | ||
| - | * MariaDB: Prashant Gupta, Abd Alrhman Abu Sbeit, Maren, TBD. | + | * MariaDB: Prashant Gupta, Abd Alrhman Abu Sbeit, Maren, TBD. |
| + | * Citus: Manar El Amrani, Maxime Renversez, Alexandre Chapelle, Nicolas Dardenne | ||
| + | * Google BigQuery: Koumudi Ganepola, Adina Bondoc, Zyad Alazazi, Alaa Almutawa | ||
| + | * SQL Server: Arina Gepalova, Tianheng Zhou, You Xu, Marie Giot | ||
| + | * Microsoft Azure SQL: Evguéniy Starygin, Gauthier Roger France, Mathieu Pardon, Diego Rubas | ||
| + | */ | ||
| ===== Examinations from Previous Years ===== | ===== Examinations from Previous Years ===== | ||