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teaching:infoh419 [2022/09/19 15:07] ezimanyi [Group Project] |
teaching:infoh419 [2022/09/19 15:10] ezimanyi [Grading] |
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| The course is given during the first semester | The course is given during the first semester | ||
| - | * Lectures on Tuesdays from 2 pm to 4 pm at the room S.UA4.218 | + | * Lectures on Mondays from 10 am to 12 pm at the room S.K.3.401 |
| - | * Exercises on Fridays from 2 pm to 4 pm at the room S.UB4.130 | + | * Exercises on Tuesdays from 2 pm to 4 pm at the room S.P4.1.17 |
| ===== Grading ===== | ===== Grading ===== | ||
| * Group project (30%) | * Group project (30%) | ||
| * Written exam (70%) | * Written exam (70%) | ||
| - | * the exam is open book; notes and books can be used. Laptops and other electronic devices are not allowed. | + | * the exam is open book; notes and books can be used. Laptops and other electronic devices are **not** allowed. Please prepare your paper material in advance. |
| ===== Course Summary ===== | ===== Course Summary ===== | ||
| Relational and object-oriented databases are mainly suited for operational settings in which there are many small transactions querying and writing to the database. Consistency of the database (in the presence of potentially conflicting transactions) is of utmost importance. Much different is the situation in analytical processing where historical data is analyzed and aggregated in many different ways. Such queries differ significantly from the typical transactional queries in the relational model: | Relational and object-oriented databases are mainly suited for operational settings in which there are many small transactions querying and writing to the database. Consistency of the database (in the presence of potentially conflicting transactions) is of utmost importance. Much different is the situation in analytical processing where historical data is analyzed and aggregated in many different ways. Such queries differ significantly from the typical transactional queries in the relational model: | ||
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| 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 1/10/2020 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 1/10/2022 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: | ||