• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • Donate

CiteSeerX logo

Tools

Sorted by:
Try your query at:
Semantic Scholar Scholar Academic
Google Bing DBLP
Results 1 - 10 of 39,718
Next 10 →

TABLE I GROWTH OF POSTGRESQL

in Using Origin Analysis to Detect Merging and Splitting of Source Code Entities
by Michael W. Godfrey, Lijie Zou

TABLE II SUMMARY OF ORIGIN ANALYSIS RESULTS FOR POSTGRESQL

in Using Origin Analysis to Detect Merging and Splitting of Source Code Entities
by Michael W. Godfrey, Lijie Zou

TABLE IV OCCURRENCES OF PATTERN INSTANCES FOUND IN POSTGRESQL.

in Using Origin Analysis to Detect Merging and Splitting of Source Code Entities
by Michael W. Godfrey, Lijie Zou

Table 3: Comparison of MySQL and PostgreSQL Features

in unknown title
by unknown authors 2001
"... In PAGE 6: ...able 2: Linux Distributions ...................................................................................................... 14 Table3 : Comparison of MySQL and PostgreSQL Features .... ..."

Table A3 Classes belonging to package onvd.postgresql

in Preface Preface
by J. Jongh, Ir. A. Wojdel 2002

Table 1 Overhead of Capturing Triggers PostgreSQL INSERT 126%

in The VLDB Journal manuscript No. (will be inserted by the editor)
by Christian Plattner, Gustavo Alonso, M. Tamer Özsu
"... In PAGE 10: ... No other load was present to obtain stable results. Table1 shows that the overhead per update statement can be as high as 61%. These figures, however, need to be prorated with the overall load as the overhead is per update statement.... ..."

Table 6: Summary of TPC-D results using PostgreSQL. A portion of the TPC-D benchmark running on the PostgreSQL database system modified to use Active Disks.

in Active Disk Architecture for Databases
by Erik Riedel, Christos Faloutsos, David Nagle 2000
"... In PAGE 12: ...4. Benchmark Evaluation Table6 shows the details of a number of the queries from the TPC-D benchmark and shows the selectivity savings possible if the various processing steps are performed at the disks. Simply using the disks for the scan primitive to eliminate table columns that are not needed in the query reduces data by a factor of three on average.... In PAGE 16: ...4. Database - Summary Table6 summarizes the results of the last several sections and compares the performance of the server system and the Active Disk prototype on several of the most expensive queries from the TPC-D benchmark. We see that the scan-intensive applications, including the 2-way join, show linear scalability, while the more complex joins have significantly higher serial overheads, but still show significant speedups with Active Disk processing.... ..."
Cited by 1

Table 6: Summary of TPC-D results using PostgreSQL. A portion of the TPC-D benchmark running on the PostgreSQL database system modified to use Active Disks.

in Active Disk Architecture for Databases
by Erik Riedel, Christos Faloutsos, David Nagle 2000
"... In PAGE 12: ...4. Benchmark Evaluation Table6 shows the details of a number of the queries from the TPC-D benchmark and shows the selectivity savings possible if the various processing steps are performed at the disks. Simply using the disks for the scan primitive to eliminate table columns that are not needed in the query reduces data by a factor of three on average.... In PAGE 16: ...4. Database - Summary Table6 summarizes the results of the last several sections and compares the performance of the server system and the Active Disk prototype on several of the most expensive queries from the TPC-D benchmark. We see that the scan-intensive applications, including the 2-way join, show linear scalability, while the more complex joins have significantly higher serial overheads, but still show significant speedups with Active Disk processing.... ..."
Cited by 1

Table 4: Performance of two homogeneous and two heterogeneous queries on modified PostgreSQL (seconds)

in INformation Systems Cooperative scans INS
by M. Zukowski, P. A. Boncz, M. L. Kersten 2004
"... In PAGE 19: ...a. 1500 chunks. In all our experiments the ChunkCache size was set to 8 chunks (16 MB). Experimental results The experiments presented in Table4 consist of two runs. The Homoge- neousRun runs of two identical disk-bound instances of Query 1 (selectivity of the first step is ca.... In PAGE 19: ... We compare 3 different execution strategies: an unmodified PostgreSQL approach, and attach and relevance strategies presented in Section 3. As the upper part of Table4 shows, for the homogeneous queries all approaches behave equally well in the synchronized scenario. However, with queries de-synchronized, the traditional PostgreSQL... ..."

Table 7. PostgreSQL configuration parameters and their P amp;B values used.

in System Administrators Guild. Sage certification study guides
by Biplob K. Debnath, James Skarie, David J. Lilja, Mohamed F. Mokbel 2002
Cited by 1
Next 10 →
Results 1 - 10 of 39,718
Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2016 The Pennsylvania State University