Parallel Databases Michael French, Spencer Steele, Jill Rochelle When Parallel Lines Meet by Ken Rudin (BYTE, May 98)

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Presentation transcript:

Parallel Databases Michael French, Spencer Steele, Jill Rochelle When Parallel Lines Meet by Ken Rudin (BYTE, May 98)

What are Parallel/Scalable Databases? n Parallel/Scalable Databases: n Hardware Architecture Multiple Processors Multiple Disk Drives Large Memory Banks n Software Architecture Capable of processing parallel queries Data shipping capabilities

What makes Parallel Databases different from previous technologies?

Previous Technology n Hardware Single processor Small Disk Capacity Less Memory n Software Sequential Queries No partitioning of queries

Parallel Query: n A Query that partitions information to multiple processors and also has the ability to pipeline information

Information Partitioning n Divide the information into smaller tasks n 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 n Allows separate processors to work on separate stages of a query –Scan –Join –Sort n Concept is akin to assembly line idea n Allows multiple queries to run at the same time

Information Pipelining 2

Sequential Query Example n Two Tables with 20 million rows each run on a uniprocessor machine –To perform scan, join & sort, query takes 12 mins. n Add partitioning –Query takes 3 mins. n Add Pipelining –12 queries can be run in 12 mins.

Parallel Kinds n Share-Everything –Hardware –Software n Share-Disk –Hardware –Software n Share-Nothing –Hardware –Software

Conclusion n Pros –Allows you to process more information –Provides for faster processing of queries n Cons –Expensive hardware & software –Much higher maintenance n Is a parallel database right for your organization?