H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 56 Citations 14,290 187 World Ranking 2066 National Ranking 1144

Research.com Recognitions

Awards & Achievements

2008 - ACM Software System Award For Gamma, the first embodiment of a parallel, "shared nothing" database system running on a cluster of commodity computers, using data partitioning and innovative parallel query execution strategies.

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Database
  • Programming language

His primary scientific interests are in Database, Query optimization, Sargable, Programming language and View. Goetz Graefe has included themes like Query by Example, Theoretical computer science and B-tree in his Database study. His Query optimization research incorporates themes from Query plan, Materialized view and Plan.

Goetz Graefe usually deals with Sargable and limits it to topics linked to Query expansion and Web search query. In his work, Logical connective, Object and Path expression is strongly intertwined with Data modeling, which is a subfield of Programming language. His View research includes elements of Relational database, Column and Hash function.

His most cited work include:

  • Query evaluation techniques for large databases (1200 citations)
  • GAMMA—a high performance dataflow database machine (355 citations)
  • Encapsulation of parallelism in the Volcano query processing system (346 citations)

What are the main themes of his work throughout his whole career to date?

Goetz Graefe spends much of his time researching Database, Query optimization, Data mining, View and Parallel computing. His Set research extends to Database, which is thematically connected. His studies in Query optimization integrate themes in fields like Query by Example, Programming language, Query expansion and Sargable.

Goetz Graefe has included themes like Search engine indexing, Robustness and Index in his Data mining study. His View study focuses on Database tuning in particular. His research integrates issues of Hash join and Joins in his study of Parallel computing.

He most often published in these fields:

  • Database (31.80%)
  • Query optimization (20.31%)
  • Data mining (14.94%)

What were the highlights of his more recent work (between 2012-2020)?

  • Database transaction (9.20%)
  • Database (31.80%)
  • Backup (3.45%)

In recent papers he was focusing on the following fields of study:

Database transaction, Database, Backup, Distributed computing and Instant are his primary areas of study. The study incorporates disciplines such as Software and Commit in addition to Database transaction. In the field of Database, his study on View overlaps with subjects such as Processing cost.

He has researched View in several fields, including Query expansion and Web query classification, Online aggregation, Sargable. His Distributed computing research incorporates elements of Concurrency control and Working set. His Materialized view research focuses on Query optimization and how it connects with Web search query.

Between 2012 and 2020, his most popular works were:

  • In-memory performance for big data (35 citations)
  • Transactional support for adaptive indexing (27 citations)
  • Instant Recovery with Write-Ahead Logging: Page Repair, System Restart, and Media Restore (18 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Database
  • Programming language

Goetz Graefe mainly investigates Backup, Database, Distributed computing, Database transaction and Incremental backup. His Backup research is multidisciplinary, incorporating elements of Database server, Rollback, Reboot and Random access. His study in Database is interdisciplinary in nature, drawing from both Reliability engineering and Crash.

His work deals with themes such as Pointer swizzling, Auxiliary memory and Data set, which intersect with Distributed computing. His Database transaction study integrates concerns from other disciplines, such as Software, Real-time computing and Record locking. His research in Incremental backup tackles topics such as Rendering which are related to areas like Computer network.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Query evaluation techniques for large databases

Goetz Graefe.
ACM Computing Surveys (1993)

1977 Citations

The Volcano optimizer generator: extensibility and efficient search

G. Graefe;W.J. McKenna.
international conference on data engineering (1993)

636 Citations

GAMMA—a high performance dataflow database machine

David J. DeWitt;Goetz Graefe;Krishna B. Kumar;Robert H. Gerber.
very large data bases (1986)

569 Citations

Volcano/spl minus/an extensible and parallel query evaluation system

G. Graefe.
IEEE Transactions on Knowledge and Data Engineering (1994)

551 Citations

Encapsulation of parallelism in the Volcano query processing system

Goetz Graefe.
international conference on management of data (1990)

536 Citations

The EXODUS optimizer generator

Goetz Graefe;David J. DeWitt.
international conference on management of data (1987)

460 Citations

Multi-table joins through bitmapped join indices

Patrick O'Neil;Goetz Graefe.
international conference on management of data (1995)

447 Citations

The Architecture of the EXODUS Extensible DBMS.

Michael J. Carey;David J. DeWitt;Daniel Frank;Goetz Graefe.
On Object-Oriented Database System (1991)

437 Citations

The Cascades Framework for Query Optimization.

Goetz Graefe.
IEEE Data(base) Engineering Bulletin (1995)

383 Citations

The architecture of the EXODUS extensible DBMS

Michael J. Carey;David J. DeWitt;Daniel Frank;M. Muralikrishna.
OODS '86 Proceedings on the 1986 international workshop on Object-oriented database systems (1986)

374 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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