Big Data Systems (WS 2021/22)

Prof. Dr. Tilmann Rabl


The amount of data that can be generated and stored in academic and industrial projects and applications is increasing rapidly. Big data analytics technologies have established themselves as a solution for big data challenges to the scalability problems of traditional database systems. The vast amounts of new data that is collected, however, usually is not as easily analyzed as curated, structured data in a data warehouse is. Typically, these data are noisy, of varying format and velocity, and need to be analyzed with techniques from statistics and machine learning rather than pure SQL-like aggregations and drill-downs. Moreover, the results of the analyzes frequently are models that are used for decision making and prediction. The complete process of big data analysis is described as a pipeline, which includes data recording, cleaning,

In this lecture, we will discuss big data systems, ie, infrastructures that are used to handle all steps in typical big data processing pipelines.

Lectures

Introduction

Date: October 26, 2021
Language: English
Duration: 01:21:21

Use Case: Search Engines

Date: October 28, 2021
Language: German
Duration: 01:26:34

Exercise Session 1

Date: November 4, 2021
Language: English
Duration: 00:43:41

MapReduce I

Date: November 9, 2021
Language: English
Duration: 01:26:48

MapReduce II

Date: November 11, 2021
Language: English
Duration: 01:24:44

MapReduce II: SQL on MR & Apache Spark

Date: November 16, 2021
Language: English
Duration: 01:20:42

Data Center and Cloud Computing

Date: November 18, 2021
Language: German
Duration: 01:24:18

Data Center and Cloud Computing: Scheduling & Cloud Computing

Date: November 25, 2021
Language: English
Duration: 01:21:54

Data Center and Cloud Computing: Network File System - (Big Data) File System

Date: November 30, 2021
Language: English
Duration: 01:15:44

Key Value Store

Date: December 2, 2021
Language: German
Duration: 01:26:46