Distributed Databases and Its Twelve Objectives

1. Distributed Databases and Its Twelve Objectives CS157B Name: Yingying Wu Professor: Sin-Min Lee Reference Book: An introduction to Database Systems By C.J.Date

2. Definition of Distributed Database: • A distributed database system consists of a collection of sites, connected together via some kind of communication network, in which: a. Each site is a full database system site in its own right. b. The sites have agreed to work together so that a user at any site can access data anywhere in the network exactly as if the data were all stored at the user’s own site.

3. A typical distributed database system: New York Shanghai Communication network London San Francisco

4. The Fundamental Principle of Distributed Database “To the user, a distributed system should look exactly like a nondistributed system.”

5. Local autonomy No reliance on a central site Continuous operation Location independence Fragmentation independence Replication independence Distributed query processing Distributed transaction management Hardware independence Operating system independence Network independence DBMS independence What is the 12 objectives?

6. Why study the 12 objectives? --Useful as • A basis for understanding distributed technology in general • A framework for characterizing the functionality of specific distributed systems.

7. Objective 1Local Autonomy • All operations at a given site are controlled by that site. • No site X should depend on some other site Y for its successful operation. -- Otherwise site Y is down might mean that site X is unable to run even if there is nothing wrong with site X itself.

8. Objective 2No Reliance on a Central Site • All sites must be treated as equals. • There must not be any reliance on a central “master” site for some central service—for example, centralized transaction management. Two reasons: • The central site might be a bottleneck. • If the central site went down, the whole system would be down.

9. Objective 3Continuous Operation • Provide greater reliability and greater availability – it is the advantage of distributed systems in general. • Unplanned shutdowns are undesirable, but hard to prevent entirely. • Planned shutdowns should never be required.

10. Objective 4Location Independence • Also known as location transparency. • Users should not have to know where data is physically stored, but rather should be able to behave -- as if the data were all stored at their own local site.

11. Objective 5Fragmentation Independence • A system supports data fragmentation if a given base relation can be divided into pieces or fragments for physical storage purposes. Two benefits: 1. most operations are local 2. reduce network traffic

12. Define two fragments: FRAGMENT EMP AS N_EMP AT SITE ‘New York’ WHERE DEPT# = DEPT#(‘D1’) OR DEPT# = DEPT#(‘D3’) S_EMP AT SITE ‘Shanghai’ WHERE DEPT# = DEPT#(‘D2’) An example of fragmentation User perception EMP New York N_EMP Shanghai S_EMP

13. Objective 6Replication Independence • A system supports data replication if a given base relation or fragment can be represented in storage by many distinct copies or replicas, stored at many distinct sites. • Ideally should be “transparent to the user”. Desirable for two reasons: 1. Applications can operate on local copies instead of remote sites. 2. At least one copy available

14. REPLICATE N_EMP AS SN_EMP AT SITE ‘Shanghai’; REPLICATE S_EMP AS NS_EMP AT SITE ‘New York’; An example of replication New York Shanghai S_EMP N_EMP SN_EMP (N_EMP Replica) NS_EMP (S_EMP Replica)

15. Objective 7Distributed Query Processing • A relational distributed system is likely to outperform a nonrelational one by orders of magnitude. • The query that involves several sites, there will be many possible ways of moving data around the system.

16. Example: Consider Query “Get supplier numbers for London suppliers of red parts” Database (suppliers-and-parts, simplified): S {S#, CITY} 10,000 stored tuples at site A P {P#, COLOR} 100,000 stored tuples at site B SP {S#, P#} 1,000,000 stored tuples at site A Assume every stored tuple is 25 bytes(200 bits)long. Query (“Get supplier numbers for London suppliers of red parts”): ( ( S JOIN SP JOIN P )WHERE CITY = ‘London’ AND COLOR = COLOR (‘Red’) ) { S# } Estimated cardinalities of certain intermediate results: Number of red parts = 10 Number of shipments by London suppliers = 100,000 Communication assumptions: Data rate = 50,000 bits per second Access delay = 0.1 second

17. We now briefly examine three possible strategies for processing this query, and for each strategy calculate the total communication time T from the formula: • ( total access delay ) + (total data volume / data rate) • Move parts to site A and process the query at A. • T1 = 0.1 + (100000 * 200 ) / 50000 • = 400 seconds approx. (6.67minutes) • 2. Move suppliers and shipments to site B and process the query at B. • T2 = 0.2 + ( ( 10000 + 1000000 ) * 200 ) / 50000 • = 4040 seconds approx. (1.12 hours) • 3. Restrict parts at site B to those that are red and move the result to site A. Complete the processing at site A. • T3 = 0.1 + (10 * 200 ) / 50000 • = 0.1 second approx.

18. Objective 8Distributed Transaction Management • Recovery The system must ensure that the set of agents for that transaction either all commit in unison or all roll back in unison. Achieved by two-phase commit protocol. • Concurrency Typically based on locking.

19. Two-phase commit: Force decision Log entry-end ph.1,start ph.2 Coordinator t1 t4 t5 t6 t9 GETREADY DO I T DONE I T OK t3 t7 t8 t2 Participant “In doubt” Forces a log entry for agent

20. Objective 9Hardware Independence • Real world involves a multiplicity of different machines—IBM machines, HP machines, PCs and workstations of various kinds. • Need to be able to integrate the data on all of those systems. • Desirable to be able to run the same DBMS on different hardware platform.

21. Objective 10Operating System Independence • Be able to run the same DBMS on different operating system platforms. • Have (e.g.) an OS/390 version and a UNIX version and a Windows version all participate in the same distributed system.

22. Objective 11Network Indepence • Desirable to be able to support a variety of disparate communication networks also.

23. Objective 12DBMS Independence • All needed is that the DBMS instances at different sites all support the same interface– they don’t necessarily all of the same DBMS software. For example, if Ingres and Oracle both supported the official SQL standard, the Ingres site and the Oracle site might be able to talk to each other in a distributed database system.

24. A hypothetical Ingres–provided gateway to Oracle: Ingres (SQL) Oracle (SQL) GATEWAY Distributed Ingres database Ingres database Oracle database Ingres user Site X Site Y

25. Thank you!