GLADE: Big Data Analytics Made Easy
Summary: GLADE is a scalable distributed analytics system using a single UDA-based class with four methods for near-data execution and cluster-wide parallelism. Compared with PostgreSQL UDAs and MapReduce (Java/Pig Latin), it emphasizes expressiveness, scalability, and runtime efficiency. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yu Cheng (University of California Merced)
- 2. Chengjie Qin (University of California Merced)
- 3. Florin Rusu (University of California Merced)
BibTeX Citation
@inproceedings{cheng_sigmod12,
title = {{GLADE: Big Data Analytics Made Easy}},
author = {Cheng, Yu and Qin, Chengjie and Rusu, Florin},
series = {{SIGMOD} '12},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2213836.2213936},
url = {https://dl.acm.org/doi/10.1145/2213836.2213936},
year = {2012}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,250 | Data Management in Machine Learning: Challenges, Techniques, and Systems | 2017 | SIGMOD | 0.00011485301 |
| 1,756 | SystemDS: A Declarative Machine Learning System for the End-to-End Data Science Lifecycle | 2020 | CIDR | 9.8172465e-05 |
| 2,389 | Parallel Data Analysis Directly on Scientific File Formats | 2014 | SIGMOD | 8.6439053e-05 |
| 3,682 | In-RDBMS Hardware Acceleration of Advanced Analytics | 2018 | VLDB | 7.2035518e-05 |
| 4,067 | Distributed Deep Learning on Data Systems: A Comparative Analysis of Approaches | 2021 | VLDB | 6.9293511e-05 |
| 4,253 | Efficient and Portable Einstein Summation in SQL | 2023 | SIGMOD | 6.8029311e-05 |
| 4,799 | Scalable Asynchronous Gradient Descent Optimization for Out-of-Core Models | 2017 | VLDB | 6.5024714e-05 |
| 9,124 | Ontological Pathfinding: Mining First-Order Knowledge from Large Knowledge Bases | 2016 | SIGMOD | 5.319248e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 5 of 5 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 |
| 44 | A Comparison of Approaches to Large-Scale Data Analysis | 2009 | SIGMOD | 0.00046055057 |
| 155 | MAD Skills: New Analysis Practices for Big Data | 2009 | VLDB | 0.00028713176 |
| 1,024 | The DataPath System: A Data-Centric Analytic Processing Engine for Large Data Warehouses | 2010 | SIGMOD | 0.0001258839 |
| 1,794 | Distributed Data-Parallel Computing Using a High-Level Programming Language | 2009 | SIGMOD | 9.7399162e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 642 | Building a High-Level Dataflow System on top of Map-Reduce: The Pig Experience | 2009 | VLDB |
| 2 | 1,539 | Distributed SociaLite: A Datalog-Based Language for Large-Scale Graph Analysis | 2013 | VLDB |
| 3 | 120 | HadoopDB: An Architectural Hybrid of MapReduce and DBMS Technologies for Analytical Workloads | 2009 | VLDB |
| 4 | 6 | Pig Latin: A Not-So-Foreign Language for Data Processing | 2008 | SIGMOD |
| 5 | 7,447 | Experimental Analysis of Distributed Graph Systems | 2018 | VLDB |
| 6 | 7,932 | Hone: “Scaling Down” Hadoop on Shared-Memory Systems | 2013 | VLDB |
| 7 | 9,640 | Supporting Scalable Analytics with Latency Constraints | 2015 | VLDB |
| 8 | 2,265 | A Platform for Scalable One-Pass Analytics using MapReduce | 2011 | SIGMOD |
| 9 | 12,170 | Palette: Enabling Scalable Analytics for Big-Memory, Multicore Machines | 2014 | SIGMOD |
| 10 | 11,942 | Declarative and distributed graph analytics with GRADOOP | 2018 | VLDB |