| 3 |
Pig Latin: A Not-So-Foreign Language for Data Processing |
2008 |
SIGMOD |
0.0024183614 |
| 35 |
MonetDB/X100: Hyper-Pipelining Query Execution |
2005 |
CIDR |
0.00076197749 |
| 60 |
Efficiently Compiling Efficient Query Plans for Modern Hardware |
2011 |
VLDB |
0.00064439773 |
| 704 |
Building Efficient Query Engines in a High-Level Language |
2014 |
VLDB |
0.00017900583 |
| 735 |
Umbra: A Disk-Based System with In-Memory Performance |
2020 |
CIDR |
0.00017452467 |
| 795 |
Conjunctive Selection Conditions in Main Memory |
2002 |
PODS |
0.00016600368 |
| 853 |
Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask |
2018 |
VLDB |
0.00015940507 |
| 1,098 |
Trill: A High-Performance Incremental Query Processor for Diverse Analytics |
2015 |
VLDB |
0.00014114442 |
| 1,108 |
Froid: Optimization of Imperative Programs in a Relational Database |
2018 |
VLDB |
0.00013984276 |
| 1,548 |
Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark |
2018 |
SIGMOD |
0.00011431383 |
| 1,750 |
Weld: A Common Runtime for High Performance Data Analytics |
2017 |
CIDR |
0.00010683647 |
| 1,873 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
0.00010253002 |
| 2,350 |
An Intermediate Representation for Optimizing Machine Learning Pipelines |
2019 |
VLDB |
8.9788641e-05 |
| 2,367 |
Here are my Data Files. Here are my Queries. Where are my Results? |
2011 |
CIDR |
8.9511058e-05 |
| 2,383 |
How to Architect a Query Compiler |
2016 |
SIGMOD |
8.9294108e-05 |
| 2,804 |
Extending Relational Query Processing with ML Inference |
2020 |
CIDR |
8.0935487e-05 |
| 2,818 |
Implicit Parallelism through Deep Language Embedding |
2015 |
SIGMOD |
8.0665558e-05 |
| 2,838 |
How to Architect a Query Compiler, Revisited |
2018 |
SIGMOD |
8.0408472e-05 |
| 2,867 |
StatusQuo: Making Familiar Abstractions Perform Using Program Analysis |
2013 |
CIDR |
7.9831651e-05 |
| 2,896 |
Evaluating End-to-End Optimization for Data Analytics Applications in Weld |
2018 |
VLDB |
7.9452051e-05 |
| 2,954 |
Magpie: Python at Speed and Scale using Cloud Backends |
2021 |
CIDR |
7.8262582e-05 |
| 3,080 |
Compiling PL/SQL Away |
2020 |
CIDR |
7.603389e-05 |
| 3,265 |
RHEEM: Enabling Cross-Platform Data Processing - May The Big Data Be With You! - |
2018 |
VLDB |
7.3083672e-05 |
| 3,296 |
Extracting Equivalent SQL from Imperative Code in Database Applications |
2016 |
SIGMOD |
7.2596583e-05 |
| 4,326 |
Fast Queries Over Heterogeneous Data Through Engine Customization |
2016 |
VLDB |
6.288323e-05 |
| 4,488 |
Analyzing Efficient Stream Processing on Modern Hardware |
2019 |
VLDB |
6.145117e-05 |
| 4,648 |
Aggify: Lifting the Curse of Cursor Loops using Custom Aggregates |
2020 |
SIGMOD |
6.0247446e-05 |
| 4,813 |
Putting Pandas in a Box |
2021 |
CIDR |
5.9049746e-05 |
| 5,193 |
LightSaber: Efficient Window Aggregation on Multi-core Processors |
2020 |
SIGMOD |
5.6371049e-05 |
| 5,427 |
The NebulaStream Platform: Data and Application Management for the Internet of Things |
2020 |
CIDR |
5.509468e-05 |
| 5,530 |
Permutable Compiled Queries: Dynamically Adapting Compiled Queries without Recompiling |
2021 |
VLDB |
5.4554282e-05 |
| 6,645 |
Functional-Style SQL UDFs With a Capital 'F' |
2020 |
SIGMOD |
4.978205e-05 |
| 6,648 |
Grizzly: Efficient Stream Processing Through Adaptive Query Compilation |
2020 |
SIGMOD |
4.9771723e-05 |
| 6,784 |
SparkR: Scaling R Programs with Spark |
2016 |
SIGMOD |
4.9265155e-05 |
| 7,448 |
DBridge: Translating Imperative Code to SQL |
2017 |
SIGMOD |
4.7273104e-05 |
| 7,925 |
Architecting a Query Compiler for Spatial Workloads |
2020 |
SIGMOD |
4.6153403e-05 |
| 8,626 |
Adaptive Code Generation for Data-Intensive Analytics |
2021 |
VLDB |
4.4829152e-05 |
| 9,001 |
The Power of Nested Parallelism in Big Data Processing – Hitting Three Flies with One Slap – |
2021 |
SIGMOD |
4.4107627e-05 |
| 9,823 |
Thriving in the No Man’s Land between Compilers and Databases |
2019 |
CIDR |
4.2754485e-05 |