1.Make a Mashup application including various services (e.g., Google Map, Google Chart, Google Search, Yahoo, Amazon,
Twitter, Facebook) Web Services (e.g., Google Map Services, Weather Services) using either (1) Mobile Web Technology
with HMLT5 Local DB (Refer to Tutorial 3) or (2) Android App Technology (Tutorial 3). You can use your Lab 2 work to
complete this work. If you implement mobile client application, condiser to use Opera Mobile Emulator to generate screens
for your mobile web app view http://www.opera.com/developer/mobile-emulator
2. Cloudera/MapReduce: Download the Cloudera Image, implement the WordCount MapReduce and run it. (a bonus point for
implementing a new MapReduce algorithm) The code and guidelines will be available in Tutorials/Tutorial 5.
3. Cloudera/Mahout: Configure your Cloudera with Mahout. Run Naive Bayes classifier with the input data (a bonus point
for using your own data).
4. Write a short report on your work (including screenshots).
5. Post all your work (source code and report) to Lab 3 directory of your GitHub site. And post your GitHub Lab 3 link
to the following site
cloudbearings / lab-03 Goto Github PK
View Code? Open in Web Editor NEWThis project forked from tkhgf/lab-03
1.Make a Mashup application including various services (e.g., Google Map, Google Chart, Google Search, Yahoo, Amazon, Twitter, Facebook) Web Services (e.g., Google Map Services, Weather Services) using either (1) Mobile Web Technology with HMLT5 Local DB (Refer to Tutorial 3) or (2) Android App Technology (Tutorial 3). You can use your Lab 2 work to complete this work. If you implement mobile client application, condiser to use Opera Mobile Emulator to generate screens for your mobile web app view http://www.opera.com/developer/mobile-emulator 2. Cloudera/MapReduce: Download the Cloudera Image, implement the WordCount MapReduce and run it. (a bonus point for implementing a new MapReduce algorithm) The code and guidelines will be available in Tutorials/Tutorial 5. 3. Cloudera/Mahout: Configure your Cloudera with Mahout. Run Naive Bayes classifier with the input data (a bonus point for using your own data). 4. Write a short report on your work (including screenshots). 5. Post all your work (source code and report) to Lab 3 directory of your GitHub site. And post your GitHub Lab 3 link to the following site