Data management data structures
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Enseignement
Détails
Faculté Faculté des sciences et de médecine Domaine Informatique Code UE-SIN.08619 Langues Anglais Type d'enseignement Cours
Cursus Master Semestre(s) SP-2023 Horaires et salles
Horaire résumé Jeudi 14:15 - 17:00, Hebdomadaire (Semestre de printemps)
Struct. des horaires 3h par semaine durant 14 semaines Heures de contact 42 Enseignement
Responsables - Cudré-Mauroux Philippe
Enseignants - Lerner Alberto
Description Data structures are often studied along algorithms but they are also essential for organizing data in database management and analytic systems.
In this class we look at fundamental families of data structures that aim at supporting efficient storage and retrieval tasks typical in the above systems.The families of data structures in which we are interested, and the respective representative instances, are the following:
- Modern Hash-base Structure - This is an important class of structure for point access. We will look into open addressing (cuckoo, swiss table) and close addressing (TBD) options.
- Scalable Trees - These structures cover in addition range access and we study examples of compact/efficient trees such as radix tree (ART) and concurrent access structures such as range index (Masstree)
- Persistent Structures - There are structures that lend themselves well to be operated in-memory but that present a persistent component. We will study structures with In-place updates (B-link* tree) and append-only (Log-Structured Merge Trees)
- Probabilistic Structures - We look into the use of approximation techniques into data structures. In particular, we look into compact set membership (Bloom Filter) and Approximate Balancing techniques (Skiplist).
- Compressed/Learned Structures - Similarly to approximation, compression also creates interesting possibilities. We look into lossless approaches in dictionary compression and lossy ones in learned Index (TBD).
Each of the five modules is comprised of two classes. There are two classes reserved for student projects presentations.Objectifs de formation Upon successful completion of this class, a student will be able to:
- Identify and understand the criteria necessary to select the best data structure to organize a given data set
- Describe a wide array of data organization structures and enumerate their advantages and disadvantages
- Explain the different access methods that each data structure facilitates, along with their performance implications
- Write and analyze source code that implements the data structuresCommentaire MSc-CS BENEFRI - (Code Ue: 63112/ Track: T6) The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/.
Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/
Softskills Non Hors domaine Non BeNeFri Oui Mobilité Oui UniPop Non -
Dates et salles
Date Heure Type d'enseignement Lieu 23.02.2023 14:15 - 17:00 Cours PER 21, salle E230 02.03.2023 14:15 - 17:00 Cours PER 21, salle E230 09.03.2023 14:15 - 17:00 Cours PER 21, salle E230 16.03.2023 14:15 - 17:00 Cours PER 21, salle E230 23.03.2023 14:15 - 17:00 Cours PER 21, salle E230 30.03.2023 14:15 - 17:00 Cours PER 21, salle E230 06.04.2023 14:15 - 17:00 Cours PER 21, salle E230 20.04.2023 14:15 - 17:00 Cours PER 21, salle E230 27.04.2023 14:15 - 17:00 Cours PER 21, salle E230 04.05.2023 14:15 - 17:00 Cours PER 21, salle E230 11.05.2023 14:15 - 17:00 Cours PER 21, salle E230 25.05.2023 14:15 - 17:00 Cours PER 21, salle E230 01.06.2023 14:15 - 17:00 Cours PER 21, salle E230 -
Modalités d'évaluation
Examen
Mode d'évaluation Par note -
Affiliation
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