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Robert B. Hagmann

dblp:12/2764 · DBLP profile ↗
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7ranked-venue papers
6as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 3 · 3 first-authorDatabases, data management, data science and information retrieval · 3 · 2 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
4 papers
Storage systems · 55% Performance modeling and evaluation · 31% Distributed systems · 14%
Databases, data mining, and information retrieval
4 papers
Transaction processing and concurrency control · 48% Database system architecture and tuning · 35% Indexing and storage engines · 17%

Topics — the 12 heaviest of 14, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation
benchmarking
0.021986
Performance Analysis of Several Back-End Database Architectures · ACM Trans. Database Syst. 1986
An Observation on Database Buffering Performance Metrics · VLDB 1986
Storage systems
crash recovery
0.011987
Reimplementing the Cedar File System Using Logging and Group Commit · SOSP 1987
Storage systems
file systems
0.011987
Reimplementing the Cedar File System Using Logging and Group Commit · SOSP 1987
Storage systems
logging
0.011987
Reimplementing the Cedar File System Using Logging and Group Commit · SOSP 1987
Indexing and storage engines
buffer management
0.011986
An Observation on Database Buffering Performance Metrics · VLDB 1986
Transaction processing and concurrency control › recovery
crash recovery
0.011986
Crash Recovery Scheme for a Memory-Resident Database System · IEEE Trans. Computers 1986
Database system architecture and tuning
main-memory database
0.011986
Crash Recovery Scheme for a Memory-Resident Database System · IEEE Trans. Computers 1986
Performance modeling and evaluation › benchmarking
database system benchmarking
0.011986
Performance Analysis of Several Back-End Database Architectures · ACM Trans. Database Syst. 1986
Distributed systems
distributed database
0.011986
Performance Analysis of Several Back-End Database Architectures · ACM Trans. Database Syst. 1986
Operating systems › resource management › storage management › file systems
file system reliability
0.011987
Reimplementing the Cedar File System Using Logging and Group Commit · SOSP 1987
Storage systems
database recovery
0.011986
Crash Recovery Scheme for a Memory-Resident Database System · IEEE Trans. Computers 1986
Storage systems
storage reliability
0.011986
Crash Recovery Scheme for a Memory-Resident Database System · IEEE Trans. Computers 1986
YearPublicationVenuePosition
1990 Two Epoch Algorithms for Disaster Recovery
Hector Garcia-Molina, Christos A. Polyzois, Robert B. Hagmann
VLDB3
1987 Reimplementing the Cedar File System Using Logging and Group Commit
abstract
The workstation file system for the Cedar programming environment was modified to improve its robustness and performance. Previously, the file system used hardware-provided labels on disk blocks to increase robustness against hardware and software errors. The new system does not require hardware disk labels, yet is more robust than the old system. Recovery is rapid after a crash. The performance of operations on file system metadata, e.g., file creation or open, is greatly improved.
Robert B. Hagmann
SOSP1
1986 Process Server: Sharing Processing Power in a Workstation Environment
Robert B. Hagmann
ICDCS1
1986 An Observation on Database Buffering Performance Metrics
Robert B. Hagmann
VLDB1
1986 Crash Recovery Scheme for a Memory-Resident Database System
abstract
Database systems normally have been designed with the assumption that main memory is too small to hold the entire database. With the decreasing cost and increasing performance of semiconductor memories, future database systems may be constructed that keep most or all of the data for the database in main memory. The challenge in the design of these systems is to provide fast transaction processing, to effectively use multiple processors, and to perform a fast restart after a crash. This correspondence presents a method of performing crash recovery for these systems.
Robert B. Hagmann
IEEE Trans. Computers1
1986 Performance Analysis of Several Back-End Database Architectures
abstract
The growing acceptance of database systems makes their performance increasingly more important. One way to gain performance is to off-load some of the functions of the database system to aback-end computer. The problem is what functions should be off-loaded to maximize the benefits of distributed processing. Our approach to this problem consisted of constructing several variants of an existing relational database system. INGRES, that partition the database system software into two parts, and assigning these two parts to two computers connected by a local area network. For the purposes of this experiment, six different variants of the database software were constructed to test the sir most interesting functional subdivisions. Each variant was then benchmarked using two different databases and query streams. The communication medium and the communication software were also benchmarked to measure their contribution to the performance of each configuration. Combining the database and network measurement results, various conclusions were reached about the viability of the configurations, the desirable properties of the communications mechanisms to he used, the operating system interface and overhead, and the performance of the database system. The variants to be preferred depend on the hardware technology, operating system features, database system internal structure, and network software overhead.
Robert B. Hagmann, Domenico Ferrari
ACM Trans. Database Syst.1
1983 Performance analysis of several backend database system architectures
Robert B. Hagmann
Perform. Evaluation1