ACCT 211 Lecture Notes - Lecture 1: Cloudera, Capriolo, Radiotelevizija Slovenija
Course
BUAN 6346.002
Course Title
Big Data Analytics
Professor
Kashif Saeed
Term
Spring 2018
Meetings
Thursdays 10:00am – 12:45pm; JSOM 1.107
Professor’s Contact Information
Office Phone
(972) 883-5094
Other Phone
Office Location
2.413
Email Address
Office Hours
Wednesdays 10am-noon
TA Information
Will be provided soon.
General Course Information
Pre-
requisites,
Co-requisites,
& other
restrictions
MIS 6326 or BUAN 6320, And MIS 6324 or BUAN 6356
Course
Description
The course covers Hadoop implementation concepts, architecture, and
different tools in the Hadoop Ecosystem. The course covers theoretical as well
as hand-on topics in Hadoop. The tools covered include Sqoop, Hive, Impala,
Pig, Flume, and Spark.
Learning
Outcomes
SLO1: Students will be able to describe architecture and methods for storage
and provision in Hadoop.
SLO2: Students will develop competency in storing, querying, and processing
data in HDFS .
SLO3: Students will demonstrate competency in importing different types of
data into Hadoop. In addition, students will learn Spark - a framework for
processing data.
SLO4: Students will learn steps involved in processing data in Hadoop
environment from end-to-end perspective.
Optional
Texts &
Materials
1. O’Reilly Sqoop Cookbook by Ting and Cecho
2. O’Reilly Programming Hive by Rutherglen, Wampler, and Capriolo
3. O’Reilly Programming Pig by Alan Gates
4. O’Reilly Learning Spark by Karau and Zahaia
Hardware
Requirements
You must have at-least 8GB RAM on your computer
You must bring your laptop to every class because of the hands-on
nature of the class.
Software
Used
1. Cloudera VM – will be made available by the instructor
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
The course covers hadoop implementation concepts, architecture, and different tools in the hadoop ecosystem. The course covers theoretical as well as hand-on topics in hadoop. Slo1: students will be able to describe architecture and methods for storage and provision in hadoop. Slo2: students will develop competency in storing, querying, and processing data in hdfs . Slo3: students will demonstrate competency in importing different types of data into hadoop. In addition, students will learn spark - a framework for processing data. You must have at-least 8gb ram on your computer. You must bring your laptop to every class because of the hands-on nature of the class: cloudera vm will be made available by the instructor, vmware https://my. vmware. com/web/vmware/free#desktop_end_user_computi ng/vmware_player/7_0. Recorded lecture there will be no in-person class on 01/11. Syllabus overview and course expectations will be covered in the second lecture. All students are required to complete hadoop installation prior to the second class.
