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Parallel Databases Michael French_ Spencer Steele_ Jill Rochelle


									       Parallel Databases
     Michael French, Spencer Steele, Jill Rochelle

When Parallel Lines Meet
by Ken Rudin (BYTE, May
    What are Parallel/Scalable

 Parallel/Scalable Databases:
 Hardware Architecture
      Multiple Processors
      Multiple Disk Drives
      Large Memory Banks
   Software Architecture
      Capable of processing parallel queries
      Data shipping capabilities
    What makes Parallel Databases
different from previous technologies?
      Previous Technology
   Hardware
      Single processor
      Small Disk Capacity
      Less Memory
   Software
      Sequential Queries
      No partitioning of queries
           Parallel Query:

   A Query that partitions information to
    multiple processors and also has the
    ability to pipeline information
    Information Partitioning

 Divide the information into smaller
 Can have multiple meanings:
    – Distribution of info to multiple CPUs
    – Division of hard drive space to contain
      certain parts of the data
Information Partitioning 2
     Information Pipelining
   Allows separate processors to work on
    separate stages of a query
    – Scan
    – Join
    – Sort
 Concept is akin to assembly line idea
 Allows multiple queries to run at the
  same time
Information Pipelining 2
Sequential Query Example
   Two Tables with 20 million rows each
    run on a uniprocessor machine
    – To perform scan, join & sort, query takes
      12 mins.
   Add partitioning
    – Query takes 3 mins.
   Add Pipelining
    – 12 queries can be run in 12 mins.
           Parallel Kinds
   Share-Everything
    – Hardware
    – Software
   Share-Disk
    – Hardware
    – Software
   Share-Nothing
    – Hardware
    – Software
   Pros
    – Allows you to process more information
    – Provides for faster processing of queries
   Cons
    – Expensive hardware & software
    – Much higher maintenance
   Is a parallel database right for your

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