CMPT 732 Lecture Notes

  1. Course Introduction [“Course Introduction” slides]
    1. Us [Us slides]
    2. This Course [This Course slides]
    3. What is Big Data? [What is Big Data? slides]
    4. How big is “Big Data”? [How big is “Big Data”? slides]
    5. “Big data” isn't always big. [“Big data” isn't always big. slides]
    6. None [None slides]
    7. Clusters [Clusters slides]
    8. Hadoop [Hadoop slides]
    9. Our Environment [Our Environment slides]
    10. Things you will do [Things you will do slides]
    11. Lecture and Labs [Lecture and Labs slides]
    12. Assignments [Assignments slides]
    13. Quizzes [Quizzes slides]
    14. Expectations [Expectations slides]
    15. Course Topics [Course Topics slides]
  2. Hadoop Concepts [“Hadoop Concepts” slides]
    1. Our Cluster [Our Cluster slides]
    2. Hadoop Pieces [Hadoop Pieces slides]
    3. HDFS [HDFS slides]
    4. YARN [YARN slides]
    5. (Simplified) Cluster Overview [(Simplified) Cluster Overview slides]
    6. Work on Hadoop [Work on Hadoop slides]
    7. MapReduce [MapReduce slides]
    8. MapReduce Stages [MapReduce Stages slides]
    9. Example: word count [Example: word count slides]
    10. MapReduce Anatomy [MapReduce Anatomy slides]
    11. Hadoop MapReduce Details [Hadoop MapReduce Details slides]
    12. Summary Output [Summary Output slides]
    13. MapReduce Parallelism [MapReduce Parallelism slides]
    14. Writables [Writables slides]
    15. Example: word count [Example: word count slides]
    16. About MapReduce [About MapReduce slides]
    17. MapReduce: One more way [MapReduce: One more way slides]
    18. MapReduce Data Flow [MapReduce Data Flow slides]
  3. Python Preliminaries
  4. Spark Concepts
  5. Spark DataFrames Concepts
  6. NoSQL & Cassandra
  7. Cloud & Data Management
  8. Data Management
  9. Spark Machine Learning
  10. Spark Streaming

Course home page.

Schedule

Week Deliverables (*) Lecture Date First Slide
1 Assign 0 Sep 10 (in lab)
2 Assign 1 Sep 14
3 Assign 2 Sep 21
4 Assign 3 Sep 28
5 Assign 4 Oct 5
6 Assign 5 Oct 12
7 Quiz 1, Assign 6 Oct 19
8 Assign 7 Oct 26
9 Assign 8 Nov 2
10 Quiz 2, Assign 9 Nov 9
11 Assign 10 Nov 16
12 Nov 23
13 Quiz 3 Nov 30
14 Project Dec 7

* Check CourSys for the actual due dates and times.