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Toward High-Performance Distributed Stream Processing via Approximate Fault Tolerance

Summary: AF-Stream enables approximate fault tolerance for distributed streaming by adaptively issuing backups with bounded error, reducing backup overhead. An extensible programming model with a small set of threshold knobs supports diverse streaming algorithms, delivering high throughput and robust accuracy after failures in EC2 experiments. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11567
Venue
VLDB
Year
2017
Pagerank
4.1945683e-05
Overall Rank
11,819 | 17.78%
DOI
-

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Showing 10 of 10 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
217 Ripple Joins for Online Aggregation 1999 SIGMOD 0.00033536712
314 MillWheel: Fault-Tolerant Stream Processing at Internet Scale 2013 VLDB 0.00028084774
328 An Architecture for Parallel Topic Models 2010 VLDB 0.0002728514
824 Twitter Heron: Stream Processing at Scale 2015 SIGMOD 0.0001623129
1,226 Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management 2013 SIGMOD 0.00013180799
1,340 Scalable Distributed Stream Processing 2003 CIDR 0.00012489223
1,357 Highly Available, Fault-Tolerant, Parallel Dataflows 2004 SIGMOD 0.00012392275
1,990 Fault-Tolerance in the Borealis Distributed Stream Processing System 2005 SIGMOD 9.8472819e-05
2,198 Continuous Analytics Over Discontinuous Streams 2010 SIGMOD 9.308495e-05
2,202 A Scalable Hash Ripple Join Algorithm 2002 SIGMOD 9.2987417e-05
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