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Leo Giakoumakis

dblp:31/3294 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

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

Databases, data management, data science and information retrieval · 4

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.

Databases, data mining, and information retrieval
3 papers
Query processing and optimization · 57% Indexing and storage engines · 25% Database system architecture and tuning · 19%
Software engineering, system software, and programming languages
1 paper
Software testing · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization
query optimization		 0.112010
Rule profiling for query optimizers and their implications · ICDE 2010
Software testing
random testing		 0.112007
A genetic approach for random testing of database systems · VLDB 2007
Indexing and storage engines
XML indexing		 0.012004
Indexing XML Data Stored in a Relational Database · VLDB 2004
Database system architecture and tuning
database engine testing		 0.012007
A genetic approach for random testing of database systems · VLDB 2007
Database system architecture and tuning
relational database system		 0.012004
Indexing XML Data Stored in a Relational Database · VLDB 2004

Methods — techniques the papers use, named apart from their topics

genetic algorithm · 0.1empirical study · 0.1
YearPublicationVenuePosition
2010 Rule profiling for query optimizers and their implications
abstract
Many modern optimizers use a transformation rule based framework. While there has been a lot of work on identifying new transformation rules, there has been little work focused on empirically evaluating the effectiveness of these transformation rules. In this paper we present the results of an empirical study of "profiling" transformation rules in Microsoft SQL Server using a diverse set of real world and benchmark query workloads. We also discuss the implications of these results for designing and testing query optimizers.
Surajit Chaudhuri, Leo Giakoumakis, Vivek R. Narasayya, Ravishankar Ramamurthy
 ICDE2
2007 Managing Query Compilation Memory Consumption to Improve DBMS Throughput
Boris Baryshnikov, Cipri Clinciu, Conor Cunningham, Leo Giakoumakis, Slava Oks, Stefano Stefani
 CIDR4
2007 A genetic approach for random testing of database systems
Hardik Bati, Leo Giakoumakis, Steve Herbert, Aleksandras Surna
 VLDB2
2004 Indexing XML Data Stored in a Relational Database
Shankar Pal, Istvan Cseri, Gideon Schaller, Oliver Seeliger, Leo Giakoumakis, Vasili Vasili Zolotov
 VLDB5