articleTop 1% cited
Apache Spark
Communications of the ACM · 2016 · Vol. 59(11) · pp. 56–65
Matei Zaharia✉(Stanford University)Reynold XinPatrick WendellTathagata DasMichael ArmbrustAnkur Dave(University of California, Berkeley)Xiangrui MengJosh RosenShivaram Venkataraman(University of California, Berkeley)Michael J. Franklin(University of California, Berkeley)Ali Ghodsi(University of California, Berkeley)Joseph E. Gonzalez(University of California, Berkeley)Scott Shenker(University of California, Berkeley)Ion Stoica(University of California, Berkeley)
Abstract
This open source computing framework unifies streaming, batch, and interactive big data workloads to unlock new applications.
Cloud Computing and Resource ManagementGraph Theory and AlgorithmsScientific Computing and Data ManagementSPARK (programming language)Computer scienceBig dataOpen sourceStreaming dataOperating systemData miningProgramming languageSoftware
Funding
- National Science Foundation
Citations
2,270
FWCI
445.73
field-weighted impact
References
25
Percentile
100%
vs. same field & year
Citations per year
Cited by
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions
Environmental Research Letters · 2019 · 511 citations
References
A bridging model for parallel computation
Communications of the ACM · 1990 · 3,661 citations
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