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Parallel database

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Execution of different operations in pipe-lined fashion. For example, if we need to join three tables, one processor may join two tables and send the result set records as and when they are produced to the other processor. In the other processor the third table can be joined with the incoming records
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database systems are not powerful enough to handle such applications. In parallel processing, many operations are performed simultaneously, as opposed to serial processing, in which the computational steps are performed sequentially. Parallel databases can be roughly divided into two groups, the
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Execution of each operation individually in different processors only if they can be executed independent of each other. For example, if we need to join four tables, then two can be joined at one processor and the other two can be joined at another processor. Final join can be done
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of various operations, such as loading data, building indexes and evaluating queries. Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations. Parallel databases improve processing and
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Execution of single complex or large operations in parallel in multiple processors. For example, ORDER BY clause of a query that tries to execute on millions of records can be parallelized on multiple processors.
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space but each processor has its own disk (HDD). If many processes run simultaneously, the speed is reduced, the same as a computer when many parallel tasks run and the computer slows down.
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in this switches or hubs are used to connect different computers its most cheapest way and simplest way only simple topologies are used to connect different computers . much smarter if
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first group of architecture is the multiprocessor architecture, the alternatives of which are the following:
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Cluster (shared nothing + shared disk: SAN/NAS), which is formed by a group of connected computers.
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Where each node has its own main memory, but all nodes share mass storage, usually a
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A single query that is executed in parallel using multiple processors or disks.
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The other architecture group is called hybrid architecture, which includes:
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Where each node has its own mass storage as well as main memory.
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Non-Uniform Memory Architecture (NUMA), which involves the
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Index

database
parallelization
input/output
CPUs
client–server
Shared-memory architecture
processors
main memory (RAM)
Shared-disk architecture
storage area network
Shared-nothing architecture
non-uniform memory access
switches
Dewitt, David
Gray, Jim
"Parallel database systems: The future of high performance database systems"
CiteSeerX
10.1.1.119.8427
doi
10.1145/129888.129894
"Parallel Database - Intraquery Parallelism - Advanced Database Management System"
Blogger
Stub icon
database
stub
expanding it
v
t
e
Categories

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