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Nezih Yegitbasi

dblp:242/5123 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Databases, data management, data science and information retrieval · 1

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
1 paper
Distributed and cloud data management · 50% Database system architecture and tuning · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed and cloud data management › distributed query processing
distributed query engine
0.412019
Presto: SQL on Everything · ICDE 2019
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management
0.112019
Presto: SQL on Everything · ICDE 2019
YearPublicationVenuePosition
2019 Presto: SQL on Everything
abstract
Presto is an open source distributed query engine that supports much of the SQL analytics workload at Facebook. Presto is designed to be adaptive, flexible, and extensible. It supports a wide variety of use cases with diverse characteristics. These range from user-facing reporting applications with sub-second latency requirements to multi-hour ETL jobs that aggregate or join terabytes of data. Presto's Connector API allows plugins to provide a high performance I/O interface to dozens of data sources, including Hadoop data warehouses, RDBMSs, NoSQL systems, and stream processing systems. In this paper, we outline a selection of use cases that Presto supports at Facebook. We then describe its architecture and implementation, and call out features and performance optimizations that enable it to support these use cases. Finally, we present performance results that demonstrate the impact of our main design decisions.
Raghav Sethi, Martin Traverso, Dain Sundstrom, David Phillips, Wenlei Xie, Yutian Sun, Nezih Yegitbasi, Haozhun Jin, Eric Hwang, Nileema Shingte, Christopher Berner
ICDE7