ch21 - Database System Concepts, 5th Ed . ©Silberschatz,...

Info iconThis preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Database System Concepts, 5th Ed . ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Chapter 21: Parallel Databases Chapter 21: Parallel Databases ©Silberschatz, Korth and Sudarshan 21.<number> Database System Concepts - 5 th Edition, Aug 22, 2005. Chapter 21: Parallel Databases Chapter 21: Parallel Databases ■ Introduction ■ I/O Parallelism ■ Interquery Parallelism ■ Intraquery Parallelism ■ Intraoperation Parallelism ■ Interoperation Parallelism ■ Design of Parallel Systems ©Silberschatz, Korth and Sudarshan 21.<number> Database System Concepts - 5 th Edition, Aug 22, 2005. Introduction Introduction ■ Parallel machines are becoming quite common and affordable ● Prices of microprocessors, memory and disks have dropped sharply ● Recent desktop computers feature multiple processors and this trend is projected to accelerate ■ Databases are growing increasingly large ● large volumes of transaction data are collected and stored for later analysis. ● multimedia objects like images are increasingly stored in databases ■ Large-scale parallel database systems increasingly used for: ● storing large volumes of data ● processing time-consuming decision-support queries ● providing high throughput for transaction processing ©Silberschatz, Korth and Sudarshan 21.<number> Database System Concepts - 5 th Edition, Aug 22, 2005. Parallelism in Databases Parallelism in Databases ■ Data can be partitioned across multiple disks for parallel I/O. ■ Individual relational operations (e.g., sort, join, aggregation) can be executed in parallel ● data can be partitioned and each processor can work independently on its own partition. ■ Queries are expressed in high level language (SQL, translated to relational algebra) ● makes parallelization easier. ■ Different queries can be run in parallel with each other. Concurrency control takes care of conflicts. ■ Thus, databases naturally lend themselves to parallelism. ©Silberschatz, Korth and Sudarshan 21.<number> Database System Concepts - 5 th Edition, Aug 22, 2005. I/O Parallelism I/O Parallelism ■ Reduce the time required to retrieve relations from disk by partitioning ■ the relations on multiple disks. ■ Horizontal partitioning – tuples of a relation are divided among many disks such that each tuple resides on one disk. ■ Partitioning techniques (number of disks = n ): Round-robin : Send the i th tuple inserted in the relation to disk i mod n . Hash partitioning : ● Choose one or more attributes as the partitioning attributes. ● Choose hash function h with range 0… n - 1 ● Let i denote result of hash function...
View Full Document

Page1 / 43

ch21 - Database System Concepts, 5th Ed . ©Silberschatz,...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online