Active Disk Architecture for Databases

Abstract

Today's commodity disk drives, the basic unit of storage for computer systems large and small, are actually small computers, with a processor, memory and a network connection, in addition to the spinning magnetic material that stores the data. Large collections of data are becoming larger, and people are beginning to analyze, rather than simply store and forget, these masses of data. At the same time, advances in I/O performance have lagged the rapid development of commodity processor and memory technology. This paper describes the use of Active Disks to take advantage of the processing power on individual disk drives to run a carefully chosen portion of a relational database system. Moving a portion of the database processing to execute directly at the disk drives improves performance by: (1) dramatically reducing data traffic; and (2) exploiting the parallelism in large storage systems. It provides a new point of leverage to overcome the I/O bottleneck. This paper discusses how to map all the basic database operations - select, project, and join - onto an Active Disk system. The changes required are small and the performance gains are dramatic. A prototype based on the Postgres database system demonstrates a factor of 2x performance improvement on a small system using a portion of the TPC-D decision support benchmark, with the promise of larger improvements in more realistically-sized system.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2000
Accession Number
ADA383912

Entities

People

  • Christos Faloutsos
  • David Nagle
  • Erik Riedel

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Data Mining
  • Database Management Systems
  • Databases
  • Decision Support Systems
  • Hash Tables
  • Image Processing
  • Information Science
  • Load Monitoring
  • Operating Systems
  • Relational Database Management Systems
  • Relational Databases

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Parallel and Distributed Computing.
  • Systems Analysis and Design