1. Distributed Computing Primer UMBC CMSC 491 Hadoop-Based Distributed Computing Spring 2016 Adam Shook Some content adapted from Dr. Kalpakis’s CMSC 621 slides

2. Agenda Distributed Computing – Evolution of Computing Infrastructure – Networking Infrastructure – Properties of Distributed Systems – Example System Architectures

3. EVOLUTION OF COMPUTING INFRASTRUCTURE

4. Mainframe – 50s to 70s Custom hardware Custom low-level specialized code Very expensive solutions

5. Client/Server – 80s to 00s IT-led architectures More portable solutions Scalable solutions based on demand Reign of the Enterprise Data Warehouse

6. Cloud – 00s to Today Consumer-grade infrastructure Growing IaaS and PaaS markets Data revolution Focus on applications and not infrastructure

7. Where does Hadoop fit? A piece of your data infrastructure – Can crunch data for analytics – Can expose data for web applications Exploration of raw data Augments today’s infrastructure IMO, a big toolbox that can do a bit of everything

8. NETWORKING INFRASTRUCTURE

9. Single Server HDD CPU RAM NIC Server Scale Up Scale Out Faster CPUs Bigger Storage More Servers

10. Local-Area Network (LAN) Rack HDD CPU RAM NIC Server HDD CPU RAM NIC Server HDD CPU RAM NIC Server HDD CPU RAM NIC Server Rack HDD CPU RAM NIC Server HDD CPU RAM NIC Server HDD CPU RAM NIC Server HDD CPU RAM NIC Server WAN Gateway

11. Wide Area Network (WAN) London, England Beijing, China New York, NY

12. PROPERTIES OF DISTRIBUTED SYSTEMS

13. Distributed Systems The development of low-cost powerful microprocessors, together with the invention of high speed networks, enable us to construct computer systems by connecting a large number of computers A distributed system is a collection of independent computers that appears to its users as a single coherent system.

14. Properties of Distributed Systems Reliability Scalability Availability Efficiency CAP Theorem

15. Reliability Can the system deliver services in face of several component failures?

16. Scalability Can the system scale to support a growing number of tasks?

17. Availability How much latency is imposed on the system when a failure occurs?

18. Efficiency How efficient is the system, in terms of latency and throughput?

19. CAP Theorem Consistent Available Partition Tolerant Trade-off between Consistency and Availability

20. Stateful vs. Stateless Whether or not a distributed system saves their state on an attached device for recovery

21. EXAMPLE SYSTEM ARCHITECTURES

22. Simple Client/Server

23. Multi-Tiered Client/Server

24. Round-Robin Client/Server

25. Linux Reference A free and open source operating system In this course, we live in Eclipse and the command line Mastery of 'vi' gets you +4 charisma http://www.ibm.com/developerworks/library/l- lpic1-v3-103-1/ http://www.linuxdevcenter.com/excerpt/LinuxPG_q uickref/linux.pdf

26. References http://webdam.inria.fr/Jorge/html/wdmch15.html Google Images