RAMP: A System for Capturing and Tracing Provenance in MapReduce Workflows
Summary: RAMP extends Hadoop to automatically capture and trace provenance for MapReduce workflows via a wrapper-based approach, preserving parallelism and fault tolerance with minimal user intervention. Demonstrated on a Pig-script Twitter sentiment workflow, it enables drill-down provenance verification of outputs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hyunjung Park (Stanford University)
- 2. Robert Ikeda (Stanford University)
- 3. Jennifer Widom (Stanford University)
BibTeX Citation
@article{park_vldb11,
title = {{RAMP: A System for Capturing and Tracing Provenance in MapReduce Workflows}},
author = {Park, Hyunjung and Ikeda, Robert and Widom, Jennifer},
journal = {PVLDB},
series = {{VLDB} '11},
volume = {4},
number = {12},
pages = {1351},
doi = {10.14778/3402755.3402768},
url = {https://doi.org/10.14778/3402755.3402768},
year = {2011}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,663 | Partial Results in Database Systems | 2014 | SIGMOD | 8.2818137e-05 |
| 2,851 | Fine-Grained, Secure and Efficient Data Provenance on Blockchain Systems | 2019 | VLDB | 8.0462369e-05 |
| 4,756 | Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture | 2020 | VLDB | 6.5221401e-05 |
| 8,509 | Hypothetical Reasoning via Provenance Abstraction | 2019 | SIGMOD | 5.4120069e-05 |
| 8,610 | Distributed Time-aware Provenance | 2013 | VLDB | 5.4022415e-05 |
| 11,814 | Demonstration of Interactive Runtime Debugging of Distributed Dataflows in Texera | 2020 | VLDB | 5.093636e-05 |
| 11,842 | Ariadne: Online Provenance for Big Graph Analytics | 2019 | SIGMOD | 5.093636e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 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 |
| 1,366 | Provenance for Generalized Map and Reduce Workflows | 2011 | CIDR | 0.00011016972 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 4,599 | Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications | 2018 | SIGMOD |
| 2 | 12,322 | ReStore: Reusing Results of MapReduce Jobs in Pig | 2012 | SIGMOD |
| 3 | 1,883 | ReStore: Reusing Results of MapReduce Jobs | 2012 | VLDB |
| 4 | 2,265 | A Platform for Scalable One-Pass Analytics using MapReduce | 2011 | SIGMOD |
| 5 | 1,786 | Putting Lipstick on Pig: Enabling Database-style Workflow Provenance | 2012 | VLDB |
| 6 | 2,486 | Stubby: A Transformation-based Optimizer for MapReduce Workflows | 2012 | VLDB |
| 7 | 13,686 | RAFT at Work: Speeding-Up MapReduce Applications under Task and Node Failures | 2011 | SIGMOD |
| 8 | 642 | Building a High-Level Dataflow System on top of Map-Reduce: The Pig Experience | 2009 | VLDB |
| 9 | 6,612 | TRAMP: Understanding the Behavior of Schema Mappings through Provenance | 2010 | VLDB |
| 10 | 1,366 | Provenance for Generalized Map and Reduce Workflows | 2011 | CIDR |