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Joe Stein

dblp:166/8384 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

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

TopicWeightPapersLastEvidence papers
Distributed systems › replication › state machine replication
log replication
0.212015
Building a Replicated Logging System with Apache Kafka · Proc. VLDB Endow. 2015
Distributed systems
replication
0.212015
Building a Replicated Logging System with Apache Kafka · Proc. VLDB Endow. 2015

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

publish-subscribe messaging · 0.2
YearPublicationVenuePosition
2015 Building a Replicated Logging System with Apache Kafka
abstract
Apache Kafka is a scalable publish-subscribe messaging system with its core architecture as a distributed commit log. It was originally built at LinkedIn as its centralized event pipelining platform for online data integration tasks. Over the past years developing and operating Kafka, we extend its log-structured architecture as a replicated logging backbone for much wider application scopes in the distributed environment. In this abstract, we will talk about our design and engineering experience to replicate Kafka logs for various distributed data-driven systems at LinkedIn, including source-of-truth data storage and stream processing.
Guozhang Wang, Joel Koshy, Sriram Subramanian, Kartik Paramasivam, Mammad Zadeh, Neha Narkhede, Jun Rao, Jay Kreps, Joe Stein
Proc. VLDB Endow.9