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Nihal Dindar

dblp:86/7118 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2013
—ORCID · none

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

Databases, data management, data science and information retrieval · 4 · 2 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.

Databases, data mining, and information retrieval
4 papers
Data stream processing · 95% Data integration and cleaning · 5%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data stream processing › continuous query processing
window semantics
0.112010
SECRET: A Model for Analysis of the Execution Semantics of Stream Processing Systems · Proc. VLDB Endow. 2010
Data stream processing
complex event processing
0.112009
DejaVu: declarative pattern matching over live and archived streams of events · SIGMOD Conference 2009
Data integration and cleaning
heterogeneous data source integration
0.012010
A demonstration of the MaxStream federated stream processing system · ICDE 2010

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

query translation · 0.1persistency management · 0.1experimental analysis · 0.1descriptive modeling · 0.1
YearPublicationVenuePosition
2013 Modeling the execution semantics of stream processing engines with SECRET
Nihal Dindar, Nesime Tatbul, Renée J. Miller, Laura M. Haas, Irina Botan
VLDB J.1
2010 A demonstration of the MaxStream federated stream processing system
abstract
MaxStream is a federated stream processing system that seamlessly integrates multiple autonomous and heterogeneous Stream Processing Engines (SPEs) and databases. In this paper, we propose to demonstrate the key features of MaxStream using two application scenarios, namely the Sales Map & Spikes business monitoring scenario and the Linear Road Benchmark, each with a different set of requirements. More specifically, we will show how the MaxStream Federator can translate and forward the application queries to two different commercial SPEs (Coral8 and StreamBase), as well as how it does so under various persistency requirements.
Irina Botan, Younggoo Cho, Roozbeh Derakhshan, Nihal Dindar, Laura M. Haas, Chulwon Lee, Girish Mundada, Ming-Chien Shan, Nesime Tatbul, Beomjin Yun
ICDE4
2010 SECRET: A Model for Analysis of the Execution Semantics of Stream Processing Systems
abstract
There are many academic and commercial stream processing engines (SPEs) today, each of them with its own execution semantics. This variation may lead to seemingly inexplicable differences in query results. In this paper, we present SECRET, a model of the behavior of SPEs. SECRET is a descriptive model that allows users to analyze the behavior of systems and understand the results of window-based queries for a broad range of heterogeneous SPEs. The model is the result of extensive analysis and experimentation with several commercial and academic engines. In the paper, we describe the types of heterogeneity found in existing engines, and show with experiments on real systems that our model can explain the key differences in windowing behavior.
Irina Botan, Roozbeh Derakhshan, Nihal Dindar, Laura M. Haas, Renée J. Miller, Nesime Tatbul
Proc. VLDB Endow.3
2009 DejaVu: declarative pattern matching over live and archived streams of events
abstract
DejaVu is an event processing system that integrates declarative pattern matching over live and archived streams of events on top of a novel system architecture. We propose to demonstrate the key aspects of the DejaVu query language and architecture using two different application scenarios, namely a smart RFID library system and a financial market data analysis application. The demonstration will illustrate how DejaVu can uniformly handle one-time, continuous, and hybrid pattern matching queries over live and archived stream stores, using highly interactive visual monitoring tools including one that is based on the Second Life virtual world.
Nihal Dindar, Baris Güç, Patrick Lau, Asli Özal, Merve Soner, Nesime Tatbul
SIGMOD Conference1