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IMPLEMENTATIONS LOCUS file system OS TABS (Camelot) Data servers OS

IMPLEMENTATIONS LOCUS file system OS TABS (Camelot) Data servers OS RAID Database level (server) SDD-1 Transaction manager Data manager System – R* Database level ARGUS Guardian (server) TABS section II, III C – data server LOCUS set 3.4.3 - opening/reading file

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IMPLEMENTATIONS LOCUS file system OS TABS (Camelot) Data servers OS

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  1. IMPLEMENTATIONS • LOCUS file system OS • TABS (Camelot) Data servers OS • RAID Database level (server) • SDD-1 Transaction manager Data manager • System – R* Database level • ARGUS Guardian (server) TABS section II, III C – data server LOCUS set 3.4.3 - opening/reading file set 3.5 - synch. dist. file system activity ARGUS nested trans/guardians Rand Slides

  2. CPU time used by RAID servers in executing transactions (in seconds Rand Slides

  3. Rand Slides

  4. Experiences with RAID Distributed Database • Unix influences must be factored out. • Communications software costs dominate everything else. • Server based systems can provide modularity and efficiency. • Concurrent execution in several server types is hard to achieve. • Need very tuned system to conduct experiments. • Data is not available from others for validation. • Expensive research direction, but is respected and rewarded. Rand Slides

  5. LAYERS • Transaction • Transparent to errors • RPC – executed within transaction • Communication • Datagram as basic unit • RPC – user level IPC (provides atomicity/reliability) • Broadcast • Input/Output System • Lower level I/O (reading and writing raw data) • Stable storage (log, UNDO, REDO) • Upper level I/O (reliable read/write) Rand Slides

  6. Description of Symbols Rand Slides

  7. Times reported in seconds Rand Slides

  8. The THOUSAND Relation Some example tuples from the thousand relation Rand Slides

  9. Execution times in 1-site RAID (in seconds) Rand Slides

  10. Execution times in 2-site RAID (in seconds) Rand Slides

  11. Execution times in 3-site RAID (in seconds) Rand Slides

  12. Execution times in 4-site RAID (in seconds) Rand Slides

  13. Local Database User Process (UI and AD) (2 messages) TM Process (AM, AC, CC, RC) (2 messages) Remote RAID Sites Rand Slides

  14. RAID Distributed System DBMS other applications DBOS other applications RAID OS OS • RAID supports reliability • transactions • stable storage • buffer pool management Rand Slides

  15. Figure 11. Performance comparison of the communication libraries Rand Slides

  16. Query Language DBMS completed transactions Atomicity Controller Atomicity Controller Atomicity Controller Atomicity Controller RAID Transactions Rand Slides

  17. UIO TR LIO SS PC LMM UMM CO RPC Figure 2. Dependency graph for proposed layered, distributed system Rand Slides

  18. site j, k, l,… User Transaction . . . . . . . . . . Database after commit log//diff file Parser read only compiled transactions updates Action Driver (interpret transactions) Action Driver (interpret transactions) compiled transactions Action Driver (ensure transaction atomicity across sites) Atomic Controller abort or commit compiled transactions Concurrency Controler Action Driver (ensure serializability) Rand Slides

  19. New Algorithm Concurrency Control Algorithm (Research Task 1) Specification • Causal Model • Events • Causal Relationships • Causal Graph • Scheduler Graph • Transaction Graph (Research Task 7) Analysis of classes Analysis (Research Task 6) correctness correctness (Research Task 5) (Research Task 3) (Research Task 4) Classes of Serializability (Research task 2) Response-time & throughput (Simulation and Analysis) RESEARCH TASKS & OVERVIEW Rand Slides

  20. Raidcomm V.1 Raidcomm V.2 Raidcomm V.3 Time (ms) 150 100 50 AD RC AC CC AM Rand Slides

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