EN 600.417 - Data Stream Processing

Institution:

Johns Hopkins University

Subject:

Description:

Data stream processing has emerged as a model for building computing applications that face tremendous volumes of dynamically changing data, and are required to process such data in a timely fashion. Examples include a variety of web-driven applications, such as web advertising based on Facebook and Twitter status streams, and more generally, monitoring and analysis applications including algorithmic trading on stock ticks and order books, network monitoring for denial of service attacks, and location-based applications working with GPS data streams. This course will study data stream processing from a data management and algorithms perspective. Students will be introduced to the fundamentals of data stream processing systems and architectures, incremental (windowed) stream processing languages, and stream algorithms that embody the principle of "you only get one look" when having to continually deal with data arriving at high rates. This course will provide students with significant implementation experience, in the spirit of a practicum. Students will proceed through a series of homework projects to build a data stream processor from scratch, and will use the resulting stream engine along with stream mining algorithms to analyze Twitter feeds. This course is aimed at upper-level undergraduates with prior programming experience. Graduate students should consider taking 600.617 instead. Students may receive credit for 600.417 or 600.617, but not both. [Systems] Pre-reqs: 600.120, 600.226, and 600.315/415.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.jhu.edu

Phone Number:

(410) 516-8000

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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