Demo Data from VLDB 2026 / reviewers in the wild / expert
Haozhun Jin
dblp:151/5224
· DBLP profile ↗
2ranked-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 · 1Human-computer interaction and ubiquitous computing · 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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed and cloud data management › distributed query processing
distributed query engine |
0.4 | 1 | 2019 | Presto: SQL on Everything · ICDE 2019 |
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management |
0.1 | 1 | 2019 | Presto: SQL on Everything · ICDE 2019 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Presto: SQL on EverythingabstractPresto 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 |
ICDE | 8 |
| 2013 | Crossroads: A Framework for Developing Proximity-based Social Interactions
Chieh-Jan Mike Liang, Haozhun Jin, Yang Yang 0096, Feng Zhao 0001 |
MobiQuitous | 2 |