Wednesday 12:50PM - 2:05PM in NVidia Auditorium, Jen-Hsun Huang Engineering Center
This course will talk about Apache Hadoop and the projects in the Hadoop ecosystem in the context of (massive scale) data mining. The objective is to give students a foundation in Apache Hadoop and related technologies. The class will be lecture-only with a few small assignments to help students cement the concepts discussed in lecture.
Topics will include Apache Hadoop, MapReduce, HDFS, implementing Hadoop jobs, combiners, secondary sort, distributed cache, Hadoop streaming, debugging Hadoop jobs, TF-IDF, Apache Hive, Impala, and Apache Pig. As time permits, additional ecosystem tools will be explored, potentially including Apache Sqoop, Apache Spark, Apache Mahout, Oryx, and others.
CS246H is intended as a supplementary section to CS246.
The content of this class is derived largely from the Cloudera Developer Training for Apache Hadoop and Cloudera Data Analyst Training: Using Pig, Hive, and Impala with Hadoop , which are made available to Stanford through the Cloudera Academic Parntership program. Additional content has been developed specifically for this course in conjunction with Cloudera.
Tentative list of topics to be covered. These topics may change slightly as the quarter progresses.
This course will include weekly Gradiance quizzes to check that students are learning the concepts. Some of the quizzes will require students to complete short programming assignments to produce the answers.
The Gradiance token for this class is 3EFD3DC8.
Slides will be posted on-line.
Course handouts and other reading materials can be downloaded here.
The coursework for the course will consist of:
General course questions should be posted Piazza.
If you need to reach the course staff, you can reach us at cs246h-win1415-staff@lists.stanford.edu (consists of the TAs and the professor).