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John Banning

dblp:91/1166 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

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

Software engineering, systems software and programming languages · 1 · 1 first-authorDatabases, 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
Database system architecture and tuning · 50% Distributed and cloud data management · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 4 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems › observability
large-scale monitoring		 0.112020
Monarch: Google's Planet-Scale In-Memory Time Series Database · Proc. VLDB Endow. 2020
Program analysis › static analysis
pointer analysis		 0.011979
An Efficient Way to Find Side Effects of Procedure Calls and Aliases of Variables · POPL 1979
Program analysis › effect analysis
side-effect analysis		 0.011979
An Efficient Way to Find Side Effects of Procedure Calls and Aliases of Variables · POPL 1979
Program analysis
static analysis		 0.011979
An Efficient Way to Find Side Effects of Procedure Calls and Aliases of Variables · POPL 1979

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

regionalized architecture · 0.9in-memory ingestion · 0.9global query plane · 0.9
YearPublicationVenuePosition
2020 Monarch: Google's Planet-Scale In-Memory Time Series Database
abstract
Monarch is a globally-distributed in-memory time series database system in Google. Monarch runs as a multi-tenant service and is used mostly to monitor the availability, correctness, performance, load, and other aspects of billion-user-scale applications and systems at Google. Every second, the system ingests terabytes of time series data into memory and serves millions of queries. Monarch has a regionalized architecture for reliability and scalability, and global query and configuration planes that integrate the regions into a unified system. On top of its distributed architecture, Monarch has flexible configuration, an expressive relational data model, and powerful queries. This paper describes the structure of the system and the novel mechanisms that achieve a reliable and flexible unified system on a regionalized distributed architecture. We also share important lessons learned from a decade's experience of developing and running Monarch as a service in Google.
Colin Adams, Benjamin Atkin, John Banning, Sumeer Bhola, Richard W. Buskens, Yoo Chung, Qin Jia, Nick Sakharov, George Talbot, Adam Tart
 Proc. VLDB Endow.4
1979 An Efficient Way to Find Side Effects of Procedure Calls and Aliases of Variables
abstract
Article Free Access Share on An efficient way to find the side effects of procedure calls and the aliases of variables Author: John P. Banning Stanford Linear Accelerator Center, Stanford, California and Amdahl Corporation, Sunnyvale, California Stanford Linear Accelerator Center, Stanford, California and Amdahl Corporation, Sunnyvale, CaliforniaView Profile Authors Info & Claims POPL '79: Proceedings of the 6th ACM SIGACT-SIGPLAN symposium on Principles of programming languagesJanuary 1979 Pages 29–41https://doi.org/10.1145/567752.567756Online:01 January 1979Publication History 161citation871DownloadsMetricsTotal Citations161Total Downloads871Last 12 Months15Last 6 weeks5 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
John Banning
 POPL1