| 660 |
Hadoop++: Making a Yellow Elephant Run Like a Cheetah (Without It Even Noticing) |
2010 |
VLDB |
0.00015198804 |
| 1,468 |
Towards a Learning Optimizer for Shared Clouds |
2019 |
VLDB |
0.00010686496 |
| 1,765 |
Selecting Subexpressions to Materialize at Datacenter Scale |
2018 |
VLDB |
9.8079546e-05 |
| 1,854 |
Towards a One Size Fits All Database Architecture |
2011 |
CIDR |
9.6069414e-05 |
| 1,931 |
Performance and Resource Modeling in Highly-Concurrent OLTP Workloads |
2013 |
SIGMOD |
9.4664741e-05 |
| 2,378 |
The Uncracked Pieces in Database Cracking |
2014 |
VLDB |
8.6682285e-05 |
| 2,398 |
BigDansing: A System for Big Data Cleansing |
2015 |
SIGMOD |
8.631172e-05 |
| 2,433 |
Vertexica: Your Relational Friend for Graph Analytics! |
2014 |
VLDB |
8.5869161e-05 |
| 2,651 |
Magpie: Python at Speed and Scale using Cloud Backends |
2021 |
CIDR |
8.2918086e-05 |
| 2,822 |
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings |
2020 |
SIGMOD |
8.0898536e-05 |
| 3,605 |
Computation Reuse in Analytics Job Service at Microsoft |
2018 |
SIGMOD |
7.2640711e-05 |
| 3,614 |
Cloudy with High Chance of DBMS: A 10-year Prediction for Enterprise-Grade ML |
2020 |
CIDR |
7.2568185e-05 |
| 3,998 |
Deploying a Steered Query Optimizer in Production at Microsoft |
2022 |
SIGMOD |
6.9676473e-05 |
| 4,456 |
AdaptDB: Adaptive Partitioning for Distributed Joins |
2017 |
VLDB |
6.692321e-05 |
| 5,059 |
Steering Query Optimizers: A Practical Take on Big Data Workloads |
2021 |
SIGMOD |
6.3807509e-05 |
| 5,156 |
Only Aggressive Elephants are Fast Elephants |
2012 |
VLDB |
6.3410921e-05 |
| 6,102 |
AutoExecutor: Predictive Parallelism for Spark SQL Queries |
2021 |
VLDB |
5.976708e-05 |
| 6,121 |
The Cosmos Big Data Platform at Microsoft: Over a Decade of Progress and a Decade to Look Forward |
2021 |
VLDB |
5.9688569e-05 |
| 6,781 |
Seagull: An Infrastructure for Load Prediction and Optimized Resource Allocation |
2021 |
VLDB |
5.7764885e-05 |
| 7,059 |
A Comparison of Knives for Bread Slicing |
2013 |
VLDB |
5.7146962e-05 |
| 7,580 |
Sibyl: Forecasting Time-Evolving Query Workloads |
2024 |
SIGMOD |
5.5925285e-05 |
| 7,619 |
AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft |
2020 |
VLDB |
5.5810604e-05 |
| 7,661 |
Machine Learning for Cloud Data Systems: the Progress so far and the Path Forward |
2021 |
VLDB |
5.5736026e-05 |
| 8,040 |
PerfGuard: Deploying ML-for-Systems without Performance Regressions, Almost! |
2021 |
VLDB |
5.5018396e-05 |
| 8,175 |
SparkCruise: Workload Optimization in Managed Spark Clusters at Microsoft |
2021 |
VLDB |
5.4737932e-05 |
| 8,276 |
CARTILAGE: Adding Flexibility to the Hadoop Skeleton |
2013 |
SIGMOD |
5.4574671e-05 |
| 8,347 |
WWHow! Freeing Data Storage from Cages |
2013 |
CIDR |
5.4472422e-05 |
| 8,798 |
GEqO: ML-Accelerated Semantic Equivalence Detection |
2023 |
SIGMOD |
5.3698781e-05 |
| 8,864 |
Pipemizer: An Optimizer for Analytics Data Pipelines |
2022 |
VLDB |
5.355022e-05 |
| 9,008 |
Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning |
2023 |
SIGMOD |
5.3335632e-05 |
| 9,224 |
Phoebe: A Learning-based Checkpoint Optimizer |
2021 |
VLDB |
5.3035811e-05 |
| 9,854 |
SparkCruise: Handsfree Computation Reuse in Spark |
2019 |
VLDB |
5.2091816e-05 |
| 9,953 |
Amoeba: A Shape changing Storage System for Big Data |
2016 |
VLDB |
5.1901412e-05 |
| 12,227 |
How Achaeans Would Construct Columns in Troy |
2013 |
CIDR |
5.093636e-05 |
| 13,351 |
Turning Databases Into Generative AI Machines |
2024 |
CIDR |
- |
| 13,399 |
PikePlace: Generating Intelligence for Marketplace Datasets |
2023 |
VLDB |
- |
| 13,560 |
Robust Data Transformations |
2015 |
CIDR |
- |