ParaTimer: A Progress Indicator for MapReduce DAGs

Summary: ParaTimer is a DAG-aware progress estimator for MapReduce workflows, using critical-path analysis to predict remaining time across paths. It handles failures and skew with multiple scenario estimates; implemented in Pig and validated on a cluster. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4332
Venue: SIGMOD
Year: 2010
Pagerank: 0.00010069173
Overall Rank: 1,665 | 88.58%
DOI: 10.1145/1807167.1807223

Incoming Non-self Citations Over Time

Authors

1. Kristi Morton (University of Washington)
2. Magdalena Balazinska (University of Washington)
3. Dan Grossman (University of Washington)

BibTeX Citation

@inproceedings{morton_sigmod10,
        title = {{ParaTimer: A Progress Indicator for MapReduce DAGs}},
        author = {Morton, Kristi and Balazinska, Magdalena and Grossman, Dan},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807223},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807223},
        year = {2010}
}

Incoming Citations (Sorted by Pagerank)

Showing 16 of 16 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
563	Plan-Structured Deep Neural Network Models for Query Performance Prediction	2019	VLDB	0.0001650812
624	Performance Prediction for Concurrent Database Workloads	2011	SIGMOD	0.00015683402
1,054	Interactive Analytical Processing in Big Data Systems: A Cross-Industry Study of MapReduce Workloads	2012	VLDB	0.00012390673
1,694	PerfXplain: Debugging MapReduce Job Performance	2012	VLDB	9.9953156e-05
2,265	A Platform for Scalable One-Pass Analytics using MapReduce	2011	SIGMOD	8.8398946e-05
2,539	Minimal MapReduce Algorithms	2013	SIGMOD	8.4526595e-05
4,049	Resource Elasticity for Large-Scale Machine Learning	2015	SIGMOD	6.9369379e-05
5,287	PREDIcT: Towards Predicting the Runtime of Large Scale Iterative Analytics	2013	VLDB	6.2815429e-05
6,138	Operator and Query Progress Estimation in Microsoft SQL Server Live Query Statistics	2016	SIGMOD	5.9640712e-05
6,333	A Statistical Approach Towards Robust Progress Estimation	2012	VLDB	5.9094287e-05
6,375	MIFO: A Query-Semantic Aware Resource Allocation Policy	2019	SIGMOD	5.8932222e-05
7,822	Resource Bricolage for Parallel Database Systems	2015	VLDB	5.5371287e-05
8,668	Toward Progress Indicators on Steroids for Big Data Systems	2013	CIDR	5.3882971e-05
9,640	Supporting Scalable Analytics with Latency Constraints	2015	VLDB	5.2434488e-05
12,147	Big Data Research: Will Industry Solve all the Problems?	2015	VLDB	5.093636e-05
12,257	Workload Management for Big Data Analytics	2013	SIGMOD	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
6	Pig Latin: A Not-So-Foreign Language for Data Processing	2008	SIGMOD	0.0010686205
9	Online Aggregation	1997	SIGMOD	0.00077458002
1,143	Toward a Progress Indicator for Database Queries	2004	SIGMOD	0.00011999403
1,562	Estimating Progress of Execution for SQL Queries	2004	SIGMOD	0.00010354429
2,270	When Can We Trust Progress Estimators for SQL Queries?	2005	SIGMOD	8.8310714e-05
2,921	Clustera: An Integrated Computation And Data Management System	2008	VLDB	7.9626308e-05
4,138	A Disk-Based Join With Probabilistic Guarantees*	2005	SIGMOD	6.8779166e-05

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