A Lightening Introduction to Parallel Computing: Using Apache Spark as an Example
By Zhenzhen WANG
Traditionally, many problems are so large and/or complex that it is impossible to solve them on a single computer, especially given limited computer memory. Parallel computing provides solutions to such problems by using multiple compute resources simultaneously to solve one computational problem. Apache Spark has emerged as the next generation of parallel processing engine. It helped ignite the big data revolution with faster processing speed, richer APIs, and more support for a variety of workloads.
This talk will provide an approachable introduction about Spark to audiences with no background in big data. It also provides audiences with a good start to learn about the big data ecology in general.
Zhenzhen Wang received her PhD in Communication from City University in 2015. After graduation, she worked as data analyst in OpenRice, focusing on big data solutions and business analysis. Currently, she is a visiting fellow in the Department of Management Science of City University of Hong Kong. Her research interest includes knowledge production and social network analysis. She published on journals such as Scientometrics and International Journal of Modern Physics C. She was the winner of 2015 top Paper award from GCSC division of International Communication Association.
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