Zur Modulseite PDF generieren

#40037 / #6

SoSe 2022 - WiSe 2022/23

English

DBTLAB Database Technology Lab

6

Markl, Volker

Benotet

Portfolioprüfung

English

Zugehörigkeit


Fakultät IV

Institut für Softwaretechnik und Theoretische Informatik

34351500 FG Datenbanksysteme und Informationsmanagement (DIMA)

Keine Angabe

Kontakt


EN 7

Pandey, Varun

sekr@dima.tu-berlin.de

Lernergebnisse

The global data volume is increasing dramatically each year. Understanding how to store, process and manage these huge amounts of data efficiently is a key requirement for software engineers and data analysts in the modern IT world. This lab (following the corresponding lecture topics of DBT-Database Technology) will teach students both the fundamentals of data processing in traditional single-node database systems and how to scale out these techniques to huge amounts of data in large-scale, distributed environments. During the implementation part of the lab, students will get hands-on experience with important data processing techniques by implementing several components of a relational database system and by using parallel programming platforms like Apache Hadoop or Nephele/PACT.

Lehrinhalte

In the database technology lab, students will implement components of a relational database system and get hands-on experience with a parallel data processing platform. The actual components implemented may vary each year, but will include parsing, query optimizer, execution engine, index structures and storage system.

Modulbestandteile

Compulsory area

Die folgenden Veranstaltungen sind für das Modul obligatorisch:

LehrveranstaltungenArtNummerTurnusSpracheSWS ISIS VVZ
DBT - PRA (Database Technology Class - Practice Part)PR0434 L 468WiSeen4

Arbeitsaufwand und Leistungspunkte

DBT - PRA (Database Technology Class - Practice Part) (PR):

AufwandbeschreibungMultiplikatorStundenGesamt
Lab/Project Work (individual/group work)15.08.0h120.0h
Plenary Meetings15.04.0h60.0h
180.0h(~6 LP)
Der Aufwand des Moduls summiert sich zu 180.0 Stunden. Damit umfasst das Modul 6 Leistungspunkte.

Beschreibung der Lehr- und Lernformen

Lectures are accompanied by exercises in small groups to practically rehearse the theory taught in the lectures. In the project, the students will be split in teams and under self-control will implement some components of a database system, with the goal to have a running demonstrator at the end of the semester.

Voraussetzungen für die Teilnahme / Prüfung

Wünschenswerte Voraussetzungen für die Teilnahme an den Lehrveranstaltungen:

This course is the base course for Master's students with a focus on database systems and information management. Students should enroll in this course in the first semester of their Master's program. In contrast to TU Berlin's introductory ISDA (Informationssysteme und Datenanalyse) course, which examines database systems from an application programmer’s point of view, this advanced course focuses on the internals of database systems. To participate, students are required to have successfully completed a Bachelor's in Computer Science with a focus on database systems (e.g., DBPRA Datenbankpraktikum, DBPRO Datenbankprojekt) and have either previously completed DBT or are concurrently enrolled in DBT. Knowledge of data modeling, relational algebra, and SQL as well as a very good (!!) command of Java programming and the Git version control system are essential to participate in the course. Note: These topics will not be covered in this course.

Verpflichtende Voraussetzungen für die Modulprüfungsanmeldung:

Dieses Modul hat keine Prüfungsvoraussetzungen.

Abschluss des Moduls

Benotung

Benotet

Prüfungsform

Portfolio examination

Art der Portfolioprüfung

100 Punkte insgesamt

Sprache(n)

English

Prüfungselemente

NamePunkteKategorieDauer/Umfang
(Deliverable assessment) Implementation of database modules for IO handling (3 tasks with 10 points each)30praktisch36h (12h/task)
(Deliverable assessment) Implementation of a database index (1 tasks with 10 points)10praktisch12h
(Deliverable assessment) Implementation of database operators (3 tasks with 25 points in total)25praktisch36h (12h/task)
(Deliverable assessment) Implementation of database optimizer components (2 tasks with 25 points in total)25praktisch24h (12h/task)
(Deliverable assessment) Implementation of database components for massively parallel processing (1 task with 10 points)10praktisch12h

Notenschlüssel

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl1.01.31.72.02.32.73.03.33.74.0
100.0pt95.0pt90.0pt85.0pt80.0pt75.0pt70.0pt65.0pt60.0pt55.0pt50.0pt

Prüfungsbeschreibung (Abschluss des Moduls)

The final grade according to § 68 (2) AllgStuPO will be calculated with the faculty grading table 2. (Die Gesamtnote gemäß § 68 (2) AllgStuPO wird nach dem Notenschlüssel 2 der Fakultät IV ermittelt.)

Dauer des Moduls

Für Belegung und Abschluss des Moduls ist folgende Semesteranzahl veranschlagt:
1 Semester.

Dieses Modul kann in folgenden Semestern begonnen werden:
Wintersemester.

Maximale teilnehmende Personen

Die maximale Teilnehmerzahl beträgt 60.

Anmeldeformalitäten

Students are required to register for the course in the official TUB examination system within six weeks after commencement of the first lecture or when the first graded assignment is due, whichever happens to be first.

Literaturhinweise, Skripte

Skript in Papierform

Verfügbarkeit:  nicht verfügbar

 

Skript in elektronischer Form

Verfügbarkeit:  verfügbar

 

Literatur

Empfohlene Literatur
Hector Garcia-Molina, Jeffrey D. Ullman, Jennifer Widom: Database Systems - The Complete Book, Pearson Prentice Hall, 2009.

Zugeordnete Studiengänge


Diese Modulversion wird in folgenden Studiengängen verwendet:

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Dieses Modul findet in keinem Studiengang Verwendung.
This module is suitable for Master’s students in Computer Science, Computer Engineering, Information Systems Management, and Industrial Engineering who are interested in database systems and information management. In particular, those students who are pursuing the Data Science and Engineering Track.

Sonstiges

Keine Angabe