查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

106-2 240667 大數據技術與管理 1 3.0 3 ★ 王怡鈞職電機所 22 0 綜科館414

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
106-2	240667	大數據技術與管理	1	3.0	3	★	王怡鈞	職電機所	22	0	綜科館414

教學大綱與進度：

教師姓名王怡鈞

Email bnwntut8@ntut.edu.tw

最後更新時間 2018-02-23 15:27:08

課程大綱 (English description is shown in the last paragraph) 由於雲端運算的快速發展，大量資料收集與儲存技術已成瓶頸，大數據技術與管理提供一套具延展性與容錯能力的分散儲存與計算架構, 能有效處理大量複雜數據資料的儲存與運算。本課程除介紹現有的大數據生態與趨勢，並針對目前軟硬體架構的處理瓶頸，提供系統組態與部署、服務層級協定、監控與管理等系統性規劃的解決方案，並導入跨領域的工程管理科學知識。課程簡扼論述大數據技術與管理的重要，並在Hadoop生態系統中，以Cloudera Hadoop為應用範例，實作說明其重要性。課程內容包括：大數據的概念、應用生態與趨勢、Hadoop硬體規格與基礎架構規劃、叢集組態與部署、叢集服務層級協定、叢集監控與管理、相關生態技術、線上操作實習、以及概略介紹Hadoop認證與準備。 Because we are generating more data and faster than ever before. Although we can store and process the data, there are problems using existing techniques. For example, both accessing the data from disk in distributed systems and getting data to the processors are of the typical bottlenecks. Apache Hadoop Big Data technology is capable of eliminating the bottlenecks by its unique methods for storing and processing data per common application scenario. The course will introduce Apache Hadoop core technologies and administration with its major listed below:  Big Data in demand and its application trend  Core technologies of Hadoop for Big Data management  Management tool to simplify Hadoop Administration  Hadoop cluster deployment  YARN applications including MapReduce  Hadoop cluster hardware and software  Deployment of Hadoop ecosystem projects: Sqoop, Flume, Hive and Impala  HDFS configuration for high availability  Hadoop security  Cluster resource scheduling and configuration  Cluster monitoring and management  Hadoop certification program Hands On Lab

課程進度「大數據技術與管理」課程進度表(Syllabus, preliminary) Tue. 18:30-21:10 Week#週次課目(視需要調整) - Subject to change per needs and circumstances 1 2/27 Syllabus & organization of all mission cases from the class 2 3/06 Big Data demand and trend 3 3/13 Core technologies for Big Data management 4 3/20 Hadoop cluster deployment 5 3/27 MapReduce 6 4/03 YARN Applications 7 4/10 Hadoop Distributed File System 8 4/17 Hands On Lab-1 9 4/24 期中考 (Mid Exam or Report) 10 5/01 Planning Hadoop Cluster 11 5/08 Hands On Lab-2 12 5/15 Hadoop ecosystem projects - Sqoop and Flume 13 5/22 Hadoop I/O 14 5/29 Case Study and Demonstrations-I 15 6/05 Case Study and Demonstrations-II 16 6/12 Hadoop security & Managing resources 17 6/19 Hadoop Certification Program & Cases presentations 18 6/26 期末考(Final Exam or Report)

評量方式與標準 1.作業- Assignment including Report, Hands on Lab and Presentation：40% 2.期中考或研讀報告 (Mid-Term Exam or Study Report)：30% 3.期末考或研讀報告 (Final-Term Exam or Study Report)：30%

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：是
Reference: 參考書目 ( 參考資料:視需要隨課提供) 1. Hadoop: The Definitive Guide, Fourth Edition, April 2015, Published by O’Reilly Media, Inc., Editor: Tom White 2. Hadoop Essentials, First Edition, April 2015, Published by O’Reilly Media, Inc., Editor: Shiva Achari. 3. Hadoop Operation, First Edition, September 2012, Published by O’Reilly Media, Inc., Editor: Eric Sammer

課程諮詢管道

備註

教師姓名	王怡鈞
Email	bnwntut8@ntut.edu.tw
最後更新時間	2018-02-23 15:27:08
課程大綱	(English description is shown in the last paragraph) 由於雲端運算的快速發展，大量資料收集與儲存技術已成瓶頸，大數據技術與管理提供一套具延展性與容錯能力的分散儲存與計算架構, 能有效處理大量複雜數據資料的儲存與運算。本課程除介紹現有的大數據生態與趨勢，並針對目前軟硬體架構的處理瓶頸，提供系統組態與部署、服務層級協定、監控與管理等系統性規劃的解決方案，並導入跨領域的工程管理科學知識。課程簡扼論述大數據技術與管理的重要，並在Hadoop生態系統中，以Cloudera Hadoop為應用範例，實作說明其重要性。課程內容包括：大數據的概念、應用生態與趨勢、Hadoop硬體規格與基礎架構規劃、叢集組態與部署、叢集服務層級協定、叢集監控與管理、相關生態技術、線上操作實習、以及概略介紹Hadoop認證與準備。 Because we are generating more data and faster than ever before. Although we can store and process the data, there are problems using existing techniques. For example, both accessing the data from disk in distributed systems and getting data to the processors are of the typical bottlenecks. Apache Hadoop Big Data technology is capable of eliminating the bottlenecks by its unique methods for storing and processing data per common application scenario. The course will introduce Apache Hadoop core technologies and administration with its major listed below:  Big Data in demand and its application trend  Core technologies of Hadoop for Big Data management  Management tool to simplify Hadoop Administration  Hadoop cluster deployment  YARN applications including MapReduce  Hadoop cluster hardware and software  Deployment of Hadoop ecosystem projects: Sqoop, Flume, Hive and Impala  HDFS configuration for high availability  Hadoop security  Cluster resource scheduling and configuration  Cluster monitoring and management  Hadoop certification program Hands On Lab
課程進度	「大數據技術與管理」課程進度表(Syllabus, preliminary) Tue. 18:30-21:10 Week#週次課目(視需要調整) - Subject to change per needs and circumstances 1 2/27 Syllabus & organization of all mission cases from the class 2 3/06 Big Data demand and trend 3 3/13 Core technologies for Big Data management 4 3/20 Hadoop cluster deployment 5 3/27 MapReduce 6 4/03 YARN Applications 7 4/10 Hadoop Distributed File System 8 4/17 Hands On Lab-1 9 4/24 期中考 (Mid Exam or Report) 10 5/01 Planning Hadoop Cluster 11 5/08 Hands On Lab-2 12 5/15 Hadoop ecosystem projects - Sqoop and Flume 13 5/22 Hadoop I/O 14 5/29 Case Study and Demonstrations-I 15 6/05 Case Study and Demonstrations-II 16 6/12 Hadoop security & Managing resources 17 6/19 Hadoop Certification Program & Cases presentations 18 6/26 期末考(Final Exam or Report)
評量方式與標準	1.作業- Assignment including Report, Hands on Lab and Presentation：40% 2.期中考或研讀報告 (Mid-Term Exam or Study Report)：30% 3.期末考或研讀報告 (Final-Term Exam or Study Report)：30%
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：是 Reference: 參考書目 ( 參考資料:視需要隨課提供) 1. Hadoop: The Definitive Guide, Fourth Edition, April 2015, Published by O’Reilly Media, Inc., Editor: Tom White 2. Hadoop Essentials, First Edition, April 2015, Published by O’Reilly Media, Inc., Editor: Shiva Achari. 3. Hadoop Operation, First Edition, September 2012, Published by O’Reilly Media, Inc., Editor: Eric Sammer
課程諮詢管道
備註