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Parallel - Outline I I I I I I I Introduction Background...

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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.1 Outline Introduction Background Distributed DBMS Architecture Distributed Database Design Semantic Data Control Distributed Query Processing Distributed Transaction Management Data server approach Parallel architectures Parallel DBMS techniques Parallel execution models Parallel Database Systems Distributed Object DBMS Database Interoperability Concluding Remarks
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.2 Large volume of data use disk and large main memory I/O bottleneck (or memory access bottleneck) Speed(disk) << speed(RAM) << speed(microprocessor) Predictions (Micro-) processor speed growth : 50 % per year DRAM capacity growth : 4 × every three years Disk throughput : 2 × in the last ten years Conclusion : the I/O bottleneck worsens The Database Problem
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.3 Increase the I/O bandwidth Data partitioning Parallel data access Origins (1980's): database machines Hardware-oriented bad cost-performance failure Notable exception : ICL's CAFS Intelligent Search Processor 1990's: same solution but using standard hardware components integrated in a multiprocessor Software-oriented Standard essential to exploit continuing technology improvements The Solution
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.4 High-performance with better cost-performance than mainframe or vector supercomputer Use many nodes, each with good cost- performance, communicating through network Good cost via high-volume components Good performance via bandwidth Trends Microprocessor and memory (DRAM): off-the-shelf Network (multiprocessor edge): custom The real chalenge is to parallelize applications to run with good load balancing Multiprocessor Objectives
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.5 Data Server Architecture client interface query parsing data server interface communication channel Application server Data server database application server interface database functions Client
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.6 Objectives of Data Servers Avoid the shortcomings of the traditional DBMS approach Centralization of data and application management General-purpose OS (not DB-oriented) By separating the functions between Application server (or host computer) Data server (or database computer or back-end computer)
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 13.7 Data Server Approach: Assessment Advantages Integrated data control by the server (black box) Increased performance by dedicated system Can better exploit parallelism Fits well in distributed environments Potential problems Communication overhead between application and data server High-level interface High cost with mainframe servers
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Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez
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