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HOME > 행사안내 > Introduction to Big Data, MapReduce, its Use ...
 
  Introduction to Big Data, MapReduce, its Use ...

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

우종욱 교수(California State University Los Angeles) ※ Lecture in

                                                                         ENGLISH

학 력 : PhD in Computer Engineering (August 2001), Department of

          Electrical Engineering, University of Southern California (USC)

 

경 력 : 2002 – 현재: 캘리포니아 주립대 로스앤젤레스, 컴퓨터 정보 시스템 학과,

                           정교수

          1997 – 2010: 헐리우드에서 전자상거래, 검색, 데이터 통합 /피드, 빅데이터

                            관련 컨설팅

 

하둡 빅데이터 관련 논문 및 책

(1) Deeksha Lakshmi, Iksuk Kim, Jongwook Woo, “Analysis of MovieLens Data Set using Hive”, in Journal of Science and Technology, Dec 2013, Volume 3, no 12, pp1194-1198, ISSN 2225-7217, ARPN

(2) Jongwook Woo, DMKD-00150, “Market Basket Analysis Algorithms with MapReduce”, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Oct 28 2013, Volume 3, Issue 6, pp445-452, ISSN 1942-4795

(3) Jongwook Woo, “Market Basket Analysis Algorithm on Map/Reduce in AWS EC2”, in International Journal of Advanced Science and Technology (IJAST), Science & Engineering Research Support soCiety (SERSC), Sept 2012, Volume 46, No 3, pp25-38, ISSN 2005-4238,

(4) “MapReduce Example with HBase for Association Rule”, Jongwook Woo and Kilhung Lee, Future Information Technology, Lecture Notes in Electrical Engineering, Volume 276, 2014, pp 49-54, ISSN: 1876-1100

 

주요연구 관심분야 : 빅데이타 맵리듀스 알고리즘 구현, 스파크 병렬처리 알고리즘 구현, 빅데이터 시스템 아키텍처 구현, 데이터 검색, 통합, 처리

강의제목

Introduction to Big Data, MapReduce, its Use Cases, and the Ecosystems

강의요약

Big Data has been popular since Apache Hadoop project came out about 2005. USA has led Big Data industry for several years and Korean community seriously considered using it since 2013, which means that Korea is more than 4 years behind USA. Besides, Korean community generally define Big Data as a method to find out new value from large scale data, which does not have any difference using traditional RDB and Data Warehouse.

In this tutorial, I will illustrate the history, definition and pro of Big Data and Hadoop and will introduce Hadoop’s MapReduce, HDFS, and popular ecosystems. Besides, some use cases should be given. Once you take this tutorial, you would clearly see what Big Data and Hadoop is and why it has been received highlights in the world.

강의계획

시간

주제

주요내용

1

- History of Big Data

- HDFS, MapReduce

- Present Big Data history and Hadoop

- Hadoop and Distributed Parallel Processing

- Data Intensive Computing

- Hadoop Core: HDFS and MapReduce

2

- MapReduce for WordCount

- Hadoop Use Cases Ecosystems

- Hadoop MapReduce concept with WordCount example

- New York Times and Huffington Post Cases

- Present Hadoop Ecosystems: Hive, Pig, Impala, Fluem, Sqoop, Spark

참고문헌

1) https://github.com/hipic: presenting codes and manuals about how to use Hadoop and ecosystems

2) http://dal-cloudcomputing.blogspot.com/: a blog site about Cloud Computing and Big Data

3) http://www.slideshare.net/dalgual/: a site to present presentation slides that I presented at invited and conference talks

4) Hadoop The Definitive Guide, 3rd edition, Tom White, Oreille

수강자의

자격요건

전산, 전자, 또는 프로그래밍 경험이 있고 하둡이라는 데이터 인텐시브 수퍼컴퓨터로 빅데이터 저장과 처리를 하는 연구, 교육에 관심있는 사람 누구나 가능

 

 
 
 
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