Rob Pike

729 citations
6 papers · 549 · 1 hit paper · h-index 5

Impact in

Papers in

    • Distributed and Parallel Computing Systems 4
    • Advanced Database Systems and Queries 2
    • Distributed systems and fault tolerance 1
    • Research Data Management Practices 1
    • Cloud Computing and Resource Management 1
    • Web Data Mining and Analysis 1

Rob Pike

6 papers receiving 483 citations

Rob Pike's Hit Papers

Interpreting the Data: Parallel Analysis with Sawzall 2005 · 482 citations
4820+7+14Years since publication100200300400

Peers

Rob Pike
Comparison fields: 5 of 51
  • Computer Networks and Communications 435
  • Information Systems 355
  • Hardware and Architecture 81
  • Information Systems and Management 69
  • Signal Processing 73
Replace Harold Lim with:
Harold Lim United States
Ingo Müller Australia
Kun Ren United States
Sang Kyun South Korea
Alan Gates United States
Tim Mattson United States
Fabrice Huet France
François Llirbat France
Andrew Crotty United States
Rob Pike relative to Harold Lim United States Harold Lim's profile →
Citations per field
00.5×
Harold Lim · 1×
Citations per year

Countries citing papers authored by Rob Pike

Since Specialization
Citations

This map shows the geographic impact of Rob Pike's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rob Pike with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rob Pike more than expected).

Fields of papers citing papers by Rob Pike

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rob Pike. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rob Pike. The network helps show where Rob Pike may publish in the future.

Co-authors

The 22 scholars most cited alongside Rob Pike, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rob Pike Line = papers co-authored together Rob Pike links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1
Interpreting the Data: Parallel Analysis with Sawzall
Hit paper breakdown →
2005482
2 200635
3 201211
4 202210
5
The Hideous Name
19859
6
Astronomy should be in the clouds
20192

About Rob Pike

Rob Pike is a scholar working on Computer Networks and Communications, Information Systems, Information Systems and Management, Signal Processing and Infectious Diseases, having authored 6 papers that have together received 549 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (4 papers), Scientific Computing and Data Management (2 papers), Advanced Database Systems and Queries (2 papers), Research Data Management Practices (1 paper), Data Management and Algorithms (1 paper), Cloud Computing and Resource Management (1 paper), Web Data Mining and Analysis (1 paper) and Distributed systems and fault tolerance (1 paper). The work is most often cited by research in Computer Networks and Communications (435 citations), Information Systems (355 citations), Hardware and Architecture (81 citations), Information Systems and Management (69 citations) and Signal Processing (73 citations). Rob Pike has collaborated with scholars based in United States. Frequent co-authors include Robert Griesemer, Sean Dorward, Sean Quinlan, Jayant Madhavan, Wilson C. Hsieh, Murray Hill, Ken Thompson, A. Bolton, Ross Thomson and Arfon M. Smith. Their work appears in journals such as Communications of the ACM, Scientific Programming and Bulletin of the American Astronomical Society.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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