COMP5349 – Cloud Computing
Week 13: Course Review and Exam Info
Dr. Ying Zhou School of Computer Science
COMP5349 Schedule in 2019
Week
Week 1
Week 2
Week 3
Week 4
Week 5
Topic
Cloud Computing Overview and Service Models
Virtualization Technology
Container Technology
Map/Reduce Framework
Spark Framework
Week 6
Week 7
Distributed Execution: HDFS and YARN
Distributed Execution: Spark
Week 8
Spark Data Frame
Week 9
Week 10
Week 11
Week 12
Week 13
Spark Machine Learning Library
Cloud Storage and Databases Services
Consistency in Cloud Storage and Database Service
Course Review
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-2
The Big Picture
n Cloud Computing
Shared IT services for clients to rent from
On different levels (IaaS, PaaS, SaaS, FaaS, ….)
Made possible through web and data center technology
n Enabling Technologies Virtualization
¡ Used by all IaaS providers Container
¡ Can be used in various scenarios
• IaaS customers can use container technology to deploy applications on VM
• PaaS or SaaS
¡ Active development to support Serverless computing
Key issues
¡ Illusion of a whole system to every client ¡ Performance isolation
¡ Security and others
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-3
Analytics and BigData Services
n Basic Computational Model
Storage: distributed file systems (GFS, HDFS)
Programming Paradigm: MapReduce
Hadoop MapReduce as specific (open source) example Map and Reduce phases
¡ Each phase allows multiple tasks to run in parallel
¡ Synchronization and shuffling happen between map and reduce phase
¡ Map output key is used to reorganize intermediate result in reduce phase
An analytic workload may needs several map reduce phases
Simple localized fault tolerance mechanism depends on storage and I/O n Other computation model
Spark
¡ RDD based API
¡ Data Frame based API
Main-memory based as compared with disk/batch based approach by MapReduce
n All based on functional programming paradigm
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-4
Cloud Storage and Database Services
n Cloud Storage Services
The cloud version of file system: GFS/HDFS, S3, EBS, etc
n Cloud Database Services
The cloud version of database: Bigtable, WAS, Dynamo, AWS
Aurora
n Common features Replication
Partition
Fault Tolerance
Various consistency levels
Various ways of handling read/write of the data
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-5
Cloud Storage/DB Services Consistency
n Many systems use customized algorithms for handling read/write
n Classic distributed system algorithm Paxos
¡ First phase only requests participants to make a promise, the actual value is proposed in the second phase
¡ Participant is not requested to check the value proposed, instead, participant checks the proposal’s sequence number
¡ A leader is necessary to maintain the progress of the algorithm
n Paxos can be used in replicated environment to reach
consensus
Run multiple Paxos, each is numbered and the value to be chosen represents an update command
Efficient mechanism to run infinite Paxos
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-6
Final Exam
n Online Open book two-hour exam Conducted in Canvas
n Exam questions
Multiple choice questions and short answer questions
n Multiple choice question has single correct answer
n Short answer questions are structured into multiple parts.
n Type your answers in the text field provided in the exam paper
Label answer with question part
n The exam has a 100 points in total
n The exam has a 40% barrier
You need to get at least 40 of 100 points in the final exam
to pass this subject
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-7
Final Exam Content
n Assessable: Lecture content
¡ All weeks Tutorial material
¡ All except week 1 Assignment
n Big Data programming may be assessed in various ways Questions based on a short program
Design a workload by writing code/pseudo code
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-8
Thank You!
COMP5349 “Cloud Computing” – 2020 (Y. Zhou) 13-9