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A Layered Aggregate Engine for Analytics Workloads
Summary: LMFAO is an in-memory, layered engine for batches of group-by aggregates over joins in analytics. It uses layered optimizations, sharing, and code specialization to accelerate ridge regression, trees, Chow-Liu networks, and data cubes, outperforming DBMSs and ML frameworks on these tasks.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h46cbbd2219cd8458
Venue
SIGMOD
Year
2019
Pagerank
8.1581558e-05
Overall Rank
2,663 | 82.10%
DOI
10.1145/3299869.3324961
Incoming Non-self Citations Over Time
BibTeX Citation
@inproceedings{schleich_sigmod19,
title = {{A Layered Aggregate Engine for Analytics Workloads}},
author = {Schleich, Maximilian and Olteanu, Dan and Khamis, Mahmoud Abo and Ngo, Hung Q. and Nguyen, XuanLong},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3324961},
url = {https://dl.acm.org/doi/10.1145/3299869.3324961},
year = {2019}
}
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Pagerank
4,161
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Optimizing Tensor Programs on Flexible Storage 2023
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LMFAO: An Engine for Batches of Group-By Aggregates 2020
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InferF: Declarative Factorization of AI/ML Inferences over Joins 2026
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BaCon: Efficient Batch Processing of Counting Queries 2026
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The Data World Is Not Flat: Efficient Factorized Execution for Relational Systems 2026
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Lightweight Materialization for Fast Dashboards Over Joins 2023
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Outgoing Citations (Sorted by Pagerank)
Showing 25 of 25 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Cited Paper
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Venue
Pagerank
11
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SIGMOD
0.00071084324
21
Efficiently Compiling Efficient Query Plans for Modern Hardware 2011
VLDB
0.00056855599
105
The MADlib Analytics Library or MAD Skills, the SQL 2012
VLDB
0.00033638251
208
EmptyHeaded: A Relational Engine for Graph Processing 2016
SIGMOD
0.00024884544
213
Eager Aggregation and Lazy Aggregation 1995
VLDB
0.00024759805
357
FAQ: Questions Asked Frequently 2016
PODS
0.00020020639
415
SystemML: Declarative Machine Learning on Spark 2016
VLDB
0.0001865959
479
The Making of TPC-DS 2006
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0.00017622471
503
Towards a Unified Architecture for in-RDBMS Analytics 2012
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0.00017202276
521
Learning Linear Regression Models over Factorized Joins 2016
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0.00016929744
605
Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask 2018
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0.00015647561
730
Learning Generalized Linear Models Over Normalized Data 2015
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0.00014406936
777
To Join or Not to Join? Thinking Twice about Joins before Feature Selection 2016
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0.00014054709
849
Aggregation and Ordering in Factorised Databases 2013
VLDB
0.00013504405
901
Maintenance of Data Cubes and Summary Tables in a Warehouse 1997
SIGMOD
0.00013185553
1,256
Towards Linear Algebra over Normalized Data 2017
VLDB
0.00011314687
1,473
Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware 2016
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0.00010557973
1,742
How to Architect a Query Compiler 2016
SIGMOD
9.7378418e-05
2,225
Shared Workload Optimization 2014
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8.8081001e-05
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FDB: A Query Engine for Factorised Relational Databases 2012
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8.6889284e-05
2,419
How to Architect a Query Compiler, Revisited 2018
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8.4923505e-05
2,975
In-Database Learning with Sparse Tensors 2018
PODS
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3,330
SPOOF: Sum-Product Optimization and Operator Fusion for Large-Scale Machine Learning 2017
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3,984
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