This document provides an overview of cloud computing, including its evolution, key characteristics, how to develop cloud applications using frameworks like MapReduce and Hadoop, and who might need cloud computing services. It discusses how cloud computing provides on-demand access to computing resources and data from any device, and how developers' key technical concern is services and data accessible over the internet. It also gives examples of major cloud computing providers like Amazon Web Services, Microsoft Azure, and Google App Engine.

1. Taste Java in the Clouds 朱仲傑 Jacky Chu

2. Agenda Evolution of computing with the network What is Cloud Computing Cloud Computing in the world How to develop a cloud application Hadoop Overview Your First Cloud Program Who needs Cloud Computing

3. Evolution of Computing with the Network

4. Internet Services around the World

5. What is Cloud Computing 松下問童子， 言師採藥去。 只在此山中， 雲深不知處。 尋隱者不遇 唐 賈島

6. Cloud Computing is … Services and data in the cloud Accessible with any device Connected to the cloud with a browser

7. The Key Technical Issue for Developers is …

8. Cloud vs. Grid Cloud Computing Grid Computing Leading Service Provider Academic Circles Standard No Yes Open Source Partial Fully Hardware PC Heterogeneous Characteristic Small data for each process A large number of repeat process Huge data for once process

9. Cloud Computing in the World

10. How to Develop a Cloud Application

11. MapReduce http://www.gridgainsystems.com/wiki/display/GG15UG/MapReduce+Overview Storage Database

12. MapReduce Map Reduce Data (Key1, Value) (Key2, Value) … (Key n, Value) (Key1, Value) (Key3, Value) … (Key m, Value) (Key2, Value) (Key3, Value) … (Key n, Value) (Key1, Value) (Key2, Value) (Key3, Value) … (Key m, Value) (Key n, Value)

13. Hadoop History Doug Cutting

14. Hadoop Overview HDFS

15. Map Class Extends MapReduceBase Implements Mapper <K1, V1, K2, V2> <WritableComparable, Writable, WritableComparable, Writable> map K1, V1 OutputCollector<K2, V2> Reporter

16. Key Class org.apache.hadoop.io.WritableComparable BooleanWritable, BytesWritable IntWritable, LongWritable VIntWritable, VLongWritable FloatWritable Text, UTF8 NullWritable

17. Value Class org.apache.hadoop.io.Writable Super Interface of WritableComparatable ArrayWritable, MapWritable ObjectWritable

18. Reduce Class Extends MapReduceBase Implements Reducer <K2, V2, K3, V3> <WritableComparable, Writable, WritableComparable, Writable> reduce K2, Iterator<V2> OutputCollector<K3, V3> Reporter

19. Job Configuration org.apache.hadoop.mapred.JobConf new JobConf(Class) setJobName(String) setMapperClass(Class <? extends Mapper>) setCombinerClass(Class <? extends Reducer>) setReducerClass(Class <? extends Reducer>) setInputFormat(Class <? extends InputFormat>) setOutputFormat(Class <? extends OutputFormat>)

20. Input/Output Format org.apache.hadoop.mapred.* FileInputFormat setInputPath(JobConf, Path ... ) The array of Path s org.apache.hadoop.fs.Path FileOutputFormat setOutputPath(JobConf, Path)

21. Run Job JobClient runJob(JobConf)

22. DEMO

23. Who needs Cloud Computing ASP (Application Service Provider) SaaS (Software as a Service) PaaS (Platform as a Service)

24. The Key is …

25. References Google AppEngine http://code.google.com/appengine Hadoop http://hadoop.apache.org Amazon Web Services http://aws.amazon.com Windows Azure http://www.microsoft.com/azure/default.mspx