| | 1 | {{{ |
| | 2 | #!html |
| | 3 | <div style="text-align: center;"><big |
| | 4 | style="font-weight: bold;"><big><big> Hadoop 資料處理平台入門班 </big></big></big></div> |
| | 5 | }}} |
| | 6 | [[PageOutline]] |
| | 7 | |
| | 8 | = 課程日期 = |
| | 9 | |
| | 10 | * 105年02月20~21日 (週六/週日 白天9:30 ~17:30 )，共2天、計14小時 。 |
| | 11 | |
| | 12 | = 上課地點 = |
| | 13 | |
| | 14 | * 10608 臺北市忠孝東路三段一號 (國立臺北科技大學光華館二樓) |
| | 15 | |
| | 16 | = 課程內容 = |
| | 17 | |
| | 18 | * [raw-attachment:wiki:NTUT160220:16-02-20_Big_Data_Hadoop_Ecosystem.pdf 完整版投影片] |
| | 19 | |
| | 20 | == '''2016-02-20（六）''' == |
| | 21 | |
| | 22 | || 上午時段 || 課程內容 || 投影片 || 實作 || 補充資料 || |
| | 23 | || 09:30~11:05 || 淺談巨量資料的趨勢、挑戰與因應對策 || [raw-attachment:wiki:NTUT160220:part-1.pdf part-1] || || || |
| | 24 | || 11:05~11:15 || 中場休息 || || || || |
| | 25 | || 11:15~12:00 || 實作一：Hadoop 單機安裝 || || [wiki:NTUT160220/Lab1 實作一][[BR]][wiki:NTUT160220/Lab2 實作二] || || |
| | 26 | || 12:00~13:00 || 午餐、午休 || || || || |
| | 27 | || 下午時段 || 課程內容 || 投影片 || 實作 || 補充資料 || |
| | 28 | || 11:10~12:00 || Hadoop 簡介：緣起與術語 || [raw-attachment:wiki:NTUT160220:part-3.pdf part-3] || || || |
| | 29 | || 13:00~14:20 || HDFS 觀念與指令解說 || [raw-attachment:wiki:NTUT160220:part-4.pdf part-4] || || || |
| | 30 | || 14:20~15:30 || 中場休息 || || || || |
| | 31 | || 15:30~16:30 || 實作二：HDFS 操作實務 || || [wiki:NTUT160220/Lab3 實作三][[BR]][wiki:NTUT160220/Lab4 實作四] || || |
| | 32 | |
| | 33 | == '''2016-02-21（日）''' == |
| | 34 | |
| | 35 | || 上午時段 || 課程內容 || 投影片 || 實作 || 補充資料 || |
| | 36 | || 09:30~11:10 || MapReduce 簡介 || [raw-attachment:wiki:NTUT160220:part-5.pdf part-5] || || || |
| | 37 | || 11:10~11:20 || 中場休息 || || || || |
| | 38 | || 11:10~12:20 || 實作三：MapReduce 範例操作 || || [wiki:NTUT160220/Lab5 實作五][[BR]][wiki:NTUT160220/Lab6 實作六] || || |
| | 39 | || 下午時段 || 課程內容 || 投影片 || 實作 || 補充資料 || |
| | 40 | || 13:30~14:00 || Hadoop 相關專案(1) Hadoop Streaming || [raw-attachment:wiki:NTUT160220:part-6.pdf part-6] || || || |
| | 41 | || 14:00~14:25 || 實作五：Hadoop Streaming 操作練習 || || [wiki:NTUT160220/Lab7 實作七][[BR]][wiki:NTUT160220/Lab8 實作八] || || |
| | 42 | || 14:25~14:35 || 中場休息 || || || || |
| | 43 | || 14:35~15:30 || Hadoop 相關專案(2) - Pig || [raw-attachment:wiki:NTUT160220:part-7.pdf part-7] || || 1.[http://stackoverflow.com/questions/10942739/a-way-to-read-table-data-from-mysql-to-pig 將 Pig 運算結果透過 DBStorage 存到 MySQL 資料庫] [[BR]] 2. [http://sublogical.blogspot.tw/2011/10/cross-posted-from-my-company-blog-post.html 將 Pig 運算結果透過 HBaseStorage 存到 HBase 資料庫] [[BR]] 3. [http://blog.mortardata.com/post/61678005593/xml-pig-loader Pig 拿 XML 當輸入] || |
| | 44 | || 15:30~16:00 || 實作六：Pig Latin 操作練習 || || [wiki:NTUT160220/Lab9 實作九] || || |
| | 45 | || 16:00~16:10 || 中場休息 || || || || |
| | 46 | || 16:10~16:30 || HBase 操作觀察 || || [wiki:NTUT160220/Lab10 實作十] || 1.關於 NoSQL 的選擇依據 - [wiki:NCHCCloudCourse100928#補充資料 YCSB] [[BR]] 2. [http://nosql-database.org/ NoSQL 的種類] [[BR]] 3. [http://www.infoq.com/news/2011/04/newsql NoSQL vs NewSQL] || |
| | 47 | |
| | 48 | = 參考書目 = |
| | 49 | |
| | 50 | 1. [http://lintool.github.com/MapReduceAlgorithms/MapReduce-book-final.pdf Data-Intensive Text Processing with MapReduce] (PDF),[http://www.umiacs.umd.edu/~jimmylin/book.html Jimmy Lin, University of Maryland] |
| | 51 | |
| | 52 | = 參考資料 = |
| | 53 | |
| | 54 | * [http://trac.3du.me/cloud/wiki/NCHCCloudCourse100928_MYSQL Hadoop 與 RDBMS 的支援] |
| | 55 | * [raw-attachment:wiki:jazz/hidoop:12-07-24_hiCloud_Hadoop.pdf 運用 hiCloud 搭建 Hadoop 叢集] |
| | 56 | |
| | 57 | * Hadoop 常見應用領域： |
| | 58 | * [http://www-304.ibm.com/easyaccess/fileserve?contentid=217007 Data Intensive Analytics with Hadoop: A Look Inside] |
| | 59 | * [http://www.youtube.com/watch?v=fVL93-OF1gc Using Hadoop to fight spam in Yahoo! Mail] - 雅虎信箱 |
| | 60 | * 商業智慧 |
| | 61 | * http://www.pentaho.com/ - Pentaho 這間 BI 公司是 Hadoop 技術的長期支持者 |
| | 62 | * 金融業 |
| | 63 | * 2010-10-12 : VISA 採用 Hadoop 做風險評估 - [http://www.slideshare.net/cloudera/hw09-large-scale-transaction-analysis HadoopWorld 2009 : Large Scale Transaction Analysis] |
| | 64 | * 中國信託 |
| | 65 | * 電信業 |
| | 66 | * 2011-06-12 : [http://www.ithome.com.tw/itadm/article.php?c=68023 中華電信用Hadoop技術分析通話明細] |
| | 67 | * 人力資源 |
| | 68 | * [http://www.simplyhired.com/a/jobtrends/trend/q-xen%2C+hyper-v%2C+hbase%2C+hadoop SimplyHired 就業技能調查排行榜] |
| | 69 | * [http://www.indeed.com/jobtrends?q=xen%2C+hyper-v%2C+hbase%2C+hadoop&l= Indeed 就業技能調查排行榜] |
| | 70 | * 行銷趨勢 |
| | 71 | * [http://www.eland.com.tw/solutions/opview_insight 意藍科技 雲端服務 OpView 品牌口碑雷達] - ([http://www.eland.com.tw/news/news/20100506 2010-05-06]) |
| | 72 | * [http://www.i-buzz.com.tw/index.asp i-Buzz網路口碑研究中心] |
| | 73 | * 科學教育 |
| | 74 | * 生資 |
| | 75 | * [http://www.slideshare.net/mndoci/hadoop-for-bioinformatics Hadoop for Bioinformatics] |
| | 76 | * [http://cloudcomputing.sys-con.com/node/1869333 The Future of Hadoop in Bioinformatics] |
| | 77 | * [http://abhishek-tiwari.com/2010/08/mapreduce-and-hadoop-algorithms-in-bioinformatics-papers.html Mapreduce and Hadoop Algorithms in Bioinformatics Papers] |
| | 78 | * 統計 |
| | 79 | * [https://mpi-inf.mpg.de/~rgemulla/publications/das10ricardo.pdf Ricardo: Integrating R and Hadoop] |
| | 80 | * [http://www.rhipe.org RHIPE: R and Hadoop Integrated Programming Environment] |
