Distributed Data Management SoSe 2017

Lecture (2V+1Ü, 4 ECTS-LP) "Distributed Data Management" (Module Description), Course Number INF-24-53-V-7

  • Level:  Master
  • Language: English


This course addresses fundamental concepts of distributed data management. Emphasis is put on novel approaches/paradigms to managing Big Data. The course aims at a mixture of system issues and hands on experience (like Hadoop/HDFS) and on fundamental algorithms and techniques (such as consistent hashing or Bloom filters).

  • Big Data, Cloud Computing
  • MapReduce (Hadoop, HDFS, …)
  • Various algorithms on top of MR
  • NoSQL Stores (MongoDB, Amazon Dynamo, Riak, ...)
  • (State Machine) Replication, Paxos
  • (Eventual) Consistency Models
  • Synopses: Bloomfilter, count-min sketch, KMV, ...
  • Distributed Data Stream Processing: STREAM, Storm, ...
  • Gossip protocols, consistent hashing

 Time and Location

  • Lecture:
    • KIS entry
    • Thursday, 15:30-17:00.
    • Room 42-110
  • Exercise:
    • KIS entry
    • Wednesday, 13:15-14:45
    • Room 13-305


Date News             
16.02.2017 Website is online.






Slides will be made available roughly 24 hours before the lecture. Note that they are then still subject to change. The final version is uploaded after the lecture.

  • Lecture 1: : TBD


Exercise Sheets

  • Sheet 1:TBD


(c) AG DBIS, TU Kaiserslautern, 2015