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ORCIDACM SIGMOD Conference 2020: online [Portland, OR, USA]
- David Maier, Rachel Pottinger, AnHai Doan, Wang-Chiew Tan, Abdussalam Alawini, Hung Q. Ngo:
Proceedings of the 2020 International Conference on Management of Data, SIGMOD Conference 2020, online conference [Portland, OR, USA], June 14-19, 2020. ACM 2020, ISBN 978-1-4503-6735-6
SIGMOD Keynote 1
- Ion Stoica:
Systems and ML: When the Sum is Greater than Its Parts. 1
Research 1: Crowdsourcing and Visualization
- Dong Wei, Senjuti Basu Roy, Sihem Amer-Yahia:
Recommending Deployment Strategies for Collaborative Tasks. 3-17 - Chengliang Chai, Lei Cao
, Guoliang Li, Jian Li, Yuyu Luo, Samuel Madden:
Human-in-the-loop Outlier Detection. 19-33 - Tsz Nam Chan, Reynold Cheng, Man Lung Yiu:
QUAD: Quadratic-Bound-based Kernel Density Visualization. 35-50 - Tarique Siddiqui, Paul Luh, Zesheng Wang, Karrie Karahalios, Aditya G. Parameswaran:
ShapeSearch: A Flexible and Efficient System for Shape-based Exploration of Trendlines. 51-65 - Liming Dong, Qiushi Bai, Taewoo Kim, Taiji Chen, Weidong Liu, Chen Li:
Marviq: Quality-Aware Geospatial Visualization of Range-Selection Queries Using Materialization. 67-82
Research 2: Serverless and Cloud Data Management
- Chenggang Wu, Vikram Sreekanti, Joseph M. Hellerstein:
Transactional Causal Consistency for Serverless Computing. 83-97 - Tarique Siddiqui, Alekh Jindal, Shi Qiao, Hiren Patel, Wangchao Le:
Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings. 99-113 - Ingo Müller, Renato Marroquín, Gustavo Alonso:
Lambada: Interactive Data Analytics on Cold Data Using Serverless Cloud Infrastructure. 115-130 - Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Samuel Madden:
Starling: A Scalable Query Engine on Cloud Functions. 131-141 - Benjamin Hilprecht, Carsten Binnig, Uwe Röhm:
Learning a Partitioning Advisor for Cloud Databases. 143-157
Research 3: Machine Learning for Databases I
- Matthias Jasny, Tobias Ziegler, Tim Kraska, Uwe Röhm, Carsten Binnig:
DB4ML - An In-Memory Database Kernel with Machine Learning Support. 159-173 - Lin Ma, Bailu Ding, Sudipto Das, Adith Swaminathan:
Active Learning for ML Enhanced Database Systems. 175-191 - Zongheng Yang, Badrish Chandramouli, Chi Wang, Johannes Gehrke, Yinan Li, Umar Farooq Minhas, Per-Åke Larson, Donald Kossmann, Rajeev Acharya:
Qd-tree: Learning Data Layouts for Big Data Analytics. 193-208 - Zainab Zolaktaf, Mostafa Milani, Rachel Pottinger:
Facilitating SQL Query Composition and Analysis. 209-224 - Sourav Sikdar, Chris Jermaine:
MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates. 225-240
Research 4: Uncertain, Probabilistic, and Approximate Data
- Babak Salimi, Harsh Parikh, Moe Kayali, Lise Getoor, Sudeepa Roy, Dan Suciu:
Causal Relational Learning. 241-256 - Laurel J. Orr, Magdalena Balazinska, Dan Suciu:
Sample Debiasing in the Themis Open World Database System. 257-268 - Matteo Brucato, Nishant Yadav, Azza Abouzied, Peter J. Haas, Alexandra Meliou:
Stochastic Package Queries in Probabilistic Databases. 269-283 - Xi Liang, Zechao Shang, Sanjay Krishnan, Aaron J. Elmore, Michael J. Franklin:
Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints. 285-295 - Batya Kenig, Pranay Mundra, Guna Prasaad, Babak Salimi, Dan Suciu:
Mining Approximate Acyclic Schemes from Relations. 297-312
Industry 1: Graph Databases and Knowledge Bases
- Xusheng Luo, Luxin Liu, Yonghua Yang, Le Bo, Yuanpeng Cao, Jinghang Wu, Qiang Li, Keping Yang, Kenny Q. Zhu:
AliCoCo: Alibaba E-commerce Cognitive Concept Net. 313-327 - Chiranjeeb Buragohain, Knut Magne Risvik, Paul Brett, Miguel Castro, Wonhee Cho, Joshua Cowhig, Nikolas Gloy, Karthik Kalyanaraman, Richendra Khanna, John Pao, Matthew Renzelmann, Alex Shamis, Timothy Tan, Shuheng Zheng:
A1: A Distributed In-Memory Graph Database. 329-344 - Yuanyuan Tian, En Liang Xu, Wei Zhao, Mir Hamid Pirahesh, Suijun Tong, Wen Sun, Thomas Kolanko, Md. Shahidul Haque Apu, Huijuan Peng:
IBM Db2 Graph: Supporting Synergistic and Retrofittable Graph Queries Inside IBM Db2. 345-359 - Abdul Quamar, Chuan Lei, Dorian Miller, Fatma Ozcan, Jeffrey T. Kreulen, Robert J. Moore, Vasilis Efthymiou:
An Ontology-Based Conversation System for Knowledge Bases. 361-376 - Alin Deutsch, Yu Xu, Mingxi Wu, Victor E. Lee:
Aggregation Support for Modern Graph Analytics in TigerGraph. 377-392 - Bang Liu, Weidong Guo, Di Niu, Jinwen Luo, Chaoyue Wang, Zhen Wen, Yu Xu:
GIANT: Scalable Creation of a Web-scale Ontology. 393-409
SIGMOD Panel
- Magda Balazinska, Surajit Chaudhuri, Anastasia Ailamaki, Juliana Freire, Sailesh Krishnamurthy, Michael Stonebraker:
The Next 5 Years: What Opportunities Should the Database Community Seize to Maximize its Impact? 411-414
Research 5: Data Provenance
- Pierre Bourhis, Daniel Deutch, Yuval Moskovitch:
Equivalence-Invariant Algebraic Provenance for Hyperplane Update Queries. 415-429 - Anna Fariha, Suman Nath, Alexandra Meliou:
Causality-Guided Adaptive Interventional Debugging. 431-446 - Yinjun Wu, Val Tannen, Susan B. Davidson:
PrIU: A Provenance-Based Approach for Incrementally Updating Regression Models. 447-462 - Raoni Lourenço, Juliana Freire, Dennis E. Shasha:
BugDoc: Algorithms to Debug Computational Processes. 463-478 - Yuchao Tao, Xi He, Ashwin Machanavajjhala, Sudeepa Roy:
Computing Local Sensitivities of Counting Queries with Joins. 479-494
Research 6: Transaction Processing and Query Optimization
- Jong-Bin Kim, Hyunsoo Cho, Kihwang Kim, Jaeseon Yu, Sooyong Kang, Hyungsoo Jung:
Long-lived Transactions Made Less Harmful. 495-510 - Erfan Zamanian, Julian Shun, Carsten Binnig, Tim Kraska:
Chiller: Contention-centric Transaction Execution and Data Partitioning for Modern Networks. 511-526 - Guna Prasaad, Alvin Cheung, Dan Suciu:
Handling Highly Contended OLTP Workloads Using Fast Dynamic Partitioning. 527-542 - Pingcheng Ruan, Dumitrel Loghin, Quang-Trung Ta, Meihui Zhang, Gang Chen, Beng Chin Ooi:
A Transactional Perspective on Execute-order-validate Blockchains. 543-557 - Surabhi Gupta, Sanket Purandare, Karthik Ramachandra:
Aggify: Lifting the Curse of Cursor Loops using Custom Aggregates. 559-573
Research 7: Security, Privacy, and Blockchain
- Yang Cao, Wenfei Fan, Yanghao Wang, Ke Yi:
Querying Shared Data with Security Heterogeneity. 575-585 - Timon Hackenjos, Florian Hahn, Florian Kerschbaum:
SAGMA: Secure Aggregation Grouped by Multiple Attributes. 587-601 - Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha:
Crypt?: Crypto-Assisted Differential Privacy on Untrusted Servers. 603-619 - Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg, Ninghui Li, Boris Skoric:
Estimating Numerical Distributions under Local Differential Privacy. 621-635 - Yanqing Peng, Min Du, Feifei Li, Raymond Cheng, Dawn Song:
FalconDB: Blockchain-based Collaborative Database. 637-652
Research 8: Graph Query Processing
- Hanzhi Wang, Zhewei Wei, Ye Yuan, Xiaoyong Du, Ji-Rong Wen:
Exact Single-Source SimRank Computation on Large Graphs. 653-663 - Ziqiang Yu, Xiaohui Yu, Nick Koudas, Yang Liu, Yifan Li, Yueting Chen, Dingyu Yang:
Distributed Processing of k Shortest Path Queries over Dynamic Road Networks. 665-679 - Louis Jachiet, Pierre Genevès, Nils Gesbert, Nabil Layaïda:
On the Optimization of Recursive Relational Queries: Application to Graph Queries. 681-697 - Tangwei Ying, Hanhua Chen, Hai Jin:
Pensieve: Skewness-Aware Version Switching for Efficient Graph Processing. 699-713 - Grace Fan, Wenfei Fan, Yuanhao Li, Ping Lu, Chao Tian, Jingren Zhou:
Extending Graph Patterns with Conditions. 715-729
Industry 2: Machine Learning and Analytics
- Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola:
Elastic Machine Learning Algorithms in Amazon SageMaker. 731-737 - Wei Cao, Yusong Gao, Feifei Li, Sheng Wang, Bingchen Lin, Ke Xu, Xiaojie Feng, Yucong Wang, Zhenjun Liu, Gejin Zhang:
Timon: A Timestamped Event Database for Efficient Telemetry Data Processing and Analytics. 739-753 - Arash Fard, Anh Le, George Larionov, Waqas Dhillon, Chuck Bear:
Vertica-ML: Distributed Machine Learning in Vertica Database. 755-768 - Antony S. Higginson, Mihaela Dediu, Octavian Arsene, Norman W. Paton, Suzanne M. Embury:
Database Workload Capacity Planning using Time Series Analysis and Machine Learning. 769-783 - Micah J. Smith, Carles Sala, James Max Kanter, Kalyan Veeramachaneni:
The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development. 785-800
SIGMOD Keynote 2
- Natasha F. Noy:
When the Web is your Data Lake: Creating a Search Engine for Datasets on the Web. 801 - Awez Syed:
The Challenge of Building Effective, Enterprise-scale Data Lakes. 803
Research 9: Data Cleaning
- Stella Giannakopoulou, Manos Karpathiotakis, Anastasia Ailamaki:
Cleaning Denial Constraint Violations through Relaxation. 805-815 - Amir Gilad, Daniel Deutch, Sudeepa Roy:
On Multiple Semantics for Declarative Database Repairs. 817-831 - Ziheng Wei, Sven Hartmann, Sebastian Link:
Discovery Algorithms for Embedded Functional Dependencies. 833-843 - Jing Nathan Yan, Oliver Schulte, Mohan Zhang, Jiannan Wang, Reynold Cheng:
SCODED: Statistical Constraint Oriented Data Error Detection. 845-860 - Yunjia Zhang, Zhihan Guo, Theodoros Rekatsinas:
A Statistical Perspective on Discovering Functional Dependencies in Noisy Data. 861-876
Research 10: Storage and Indexing
- Michael Haubenschild, Caetano Sauer, Thomas Neumann, Viktor Leis:
Rethinking Logging, Checkpoints, and Recovery for High-Performance Storage Engines. 877-892 - Subhadeep Sarkar, Tarikul Islam Papon, Dimitris Staratzis, Manos Athanassoulis:
Lethe: A Tunable Delete-Aware LSM Engine. 893-908 - Linwei Li, Kai Zhang, Jiading Guo, Wen He, Zhenying He, Yinan Jing, Weili Han, X. Sean Wang:
BinDex: A Two-Layered Index for Fast and Robust Scans. 909-923 - Cong Yue, Zhongle Xie, Meihui Zhang, Gang Chen, Beng Chin Ooi, Sheng Wang, Xiaokui Xiao:
Analysis of Indexing Structures for Immutable Data. 925-935 - Harald Lang, Alexander Beischl, Viktor Leis, Peter A. Boncz, Thomas Neumann, Alfons Kemper:
Tree-Encoded Bitmaps. 937-967
Research 11: Machine Learning for Databases II
- Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Jaeyoung Do, Yinan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet, Tim Kraska:
ALEX: An Updatable Adaptive Learned Index. 969-984 - Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska:
Learning Multi-Dimensional Indexes. 985-1000 - Ani Kristo, Kapil Vaidya, Ugur Çetintemel, Sanchit Misra, Tim Kraska:
The Case for a Learned Sorting Algorithm. 1001-1016 - Yongjoo Park, Shucheng Zhong, Barzan Mozafari:
QuickSel: Quick Selectivity Learning with Mixture Models. 1017-1033 - Shohedul Hasan, Saravanan Thirumuruganathan, Jees Augustine, Nick Koudas, Gautam Das:
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries. 1035-1050
Research 12: Graph Matching and Discovery
- Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V. S. Lakshmanan, Wenjie Zhang, Xuemin Lin:
Efficient Algorithms for Densest Subgraph Discovery on Large Directed Graphs. 1051-1066 - Wentian Guo, Yuchen Li, Mo Sha, Bingsheng He, Xiaokui Xiao, Kian-Lee Tan:
GPU-Accelerated Subgraph Enumeration on Partitioned Graphs. 1067-1082 - Shixuan Sun, Qiong Luo:
In-Memory Subgraph Matching: An In-depth Study. 1083-1098 - Yeonsu Park, Seongyun Ko, Sourav S. Bhowmick, Kyoungmin Kim, Kijae Hong, Wook-Shin Han:
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching. 1099-1114 - Tahsin Reza, Matei Ripeanu, Geoffrey Sanders, Roger Pearce:
Approximate Pattern Matching in Massive Graphs with Precision and Recall Guarantees. 1115-1131
Research 13: Data Matching
- Venkata Vamsikrishna Meduri, Lucian Popa, Prithviraj Sen, Mohamed Sarwat:
A Comprehensive Benchmark Framework for Active Learning Methods in Entity Matching. 1133-1147 - Renzhi Wu, Sanya Chaba, Saurabh Sawlani, Xu Chu, Saravanan Thirumuruganathan:
ZeroER: Entity Resolution using Zero Labeled Examples. 1149-1164 - Zhaoqiang Chen, Qun Chen, Boyi Hou, Zhanhuai Li, Guoliang Li:
Towards Interpretable and Learnable Risk Analysis for Entity Resolution. 1165-1180 - Fuat Basik, Hakan Ferhatosmanoglu, Bugra Gedik:
SLIM: Scalable Linkage of Mobility Data. 1181-1196 - Yaoshu Wang, Chuan Xiao, Jianbin Qin, Xin Cao, Yifang Sun, Wei Wang, Makoto Onizuka:
Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach. 1197-1212
Research 14: Query Optimization and Execution
- Shaleen Deep, Xiao Hu, Paraschos Koutris:
Fast Join Project Query Evaluation using Matrix Multiplication. 1213-1223 - Qichen Wang, Ke Yi:
Maintaining Acyclic Foreign-Key Joins under Updates. 1225-1239 - Dixin Tang, Zechao Shang, Aaron J. Elmore, Sanjay Krishnan, Michael J. Franklin:
Thrifty Query Execution via Incrementability. 1241-1256 - Wenjia He, Michael R. Anderson, Maxwell Strome, Michael J. Cafarella:
A Method for Optimizing Opaque Filter Queries. 1257-1272 - Christian Duta, Torsten Grust:
Functional-Style SQL UDFs With a Capital 'F'. 1273-1287
Research 15: Machine Learning for Cleaning, Integration, and Search
- Sebastian Schelter, Tammo Rukat, Felix Bießmann:
Learning to Validate the Predictions of Black Box Classifiers on Unseen Data. 1289-1299 - Jose Picado, John Davis, Arash Termehchy, Ga Young Lee:
Learning Over Dirty Data Without Cleaning. 1301-1316 - Weiyuan Wu, Lampros Flokas, Eugene Wu, Jiannan Wang:
Complaint-driven Training Data Debugging for Query 2.0. 1317-1334 - Riccardo Cappuzzo, Paolo Papotti, Saravanan Thirumuruganathan:
Creating Embeddings of Heterogeneous Relational Datasets for Data Integration Tasks. 1335-1349 - Shay Gershtein, Tova Milo, Gefen Morami, Slava Novgorodov:
Minimization of Classifier Construction Cost for Search Queries. 1351-1365
Research 16: Graph and Stream Processing
- Wentao Li, Miao Qiao, Lu Qin, Ying Zhang, Lijun Chang, Xuemin Lin:
Scaling Up Distance Labeling on Graphs with Core-Periphery Properties. 1367-1381 - Krishna Kumar P., Paul Langton, Wolfgang Gatterbauer:
Factorized Graph Representations for Semi-Supervised Learning from Sparse Data. 1383-1398 - Wentao Zhang, Xupeng Miao, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui:
Reliable Data Distillation on Graph Convolutional Network. 1399-1414 - Anil Pacaci, Angela Bonifati, M. Tamer Özsu:
Regular Path Query Evaluation on Streaming Graphs. 1415-1430 - Prashant Pandey, Shikha Singh, Michael A. Bender, Jonathan W. Berry, Martin Farach-Colton, Rob Johnson, Thomas M. Kroeger, Cynthia A. Phillips:
Timely Reporting of Heavy Hitters using External Memory. 1431-1446
Industry 3: Cloud and Distributed Databases
- Mohamed A. Soliman, Lyublena Antova, Marc Sugiyama, Michael Duller, Amirhossein Aleyasen, Gourab Mitra, Ehab Abdelhamid, Mark Morcos, Michele Gage, Dmitri Korablev, Florian M. Waas:
A Framework for Emulating Database Operations in Cloud Data Warehouses. 1447-1461 - Alex Depoutovitch, Chong Chen, Jin Chen, Paul Larson, Shu Lin, Jack Ng, Wenlin Cui, Qiang Liu, Wei Huang, Yong Xiao, Yongjun He:
Taurus Database: How to be Fast, Available, and Frugal in the Cloud. 1463-1478 - Mathieu B. Demarne, Jim Gramling, Tomer Verona, Miso Cilimdzic:
Reliability Analytics for Cloud Based Distributed Databases. 1479-1492 - Rebecca Taft, Irfan Sharif, Andrei Matei, Nathan VanBenschoten, Jordan Lewis, Tobias Grieger, Kai Niemi, Andy Woods, Anne Birzin, Raphael Poss, Paul Bardea, Amruta Ranade, Ben Darnell, Bram Gruneir, Justin Jaffray, Lucy Zhang, Peter Mattis:
CockroachDB: The Resilient Geo-Distributed SQL Database. 1493-1509 - Panagiotis Antonopoulos, Arvind Arasu, Kunal D. Singh, Ken Eguro, Nitish Gupta, Rajat Jain, Raghav Kaushik, Hanuma Kodavalla, Donald Kossmann, Nikolas Ogg, Ravi Ramamurthy, Jakub Szymaszek, Jeffrey Trimmer, Kapil Vaswani, Ramarathnam Venkatesan, Mike Zwilling:
Azure SQL Database Always Encrypted. 1511-1525
Research 17: Data Exploration and Preparation
- Ori Bar El, Tova Milo, Amit Somech:
Automatically Generating Data Exploration Sessions Using Deep Reinforcement Learning. 1527-1537 - Cong Yan, Yeye He:
Auto-Suggest: Learning-to-Recommend Data Preparation Steps Using Data Science Notebooks. 1539-1554 - Philipp Eichmann, Emanuel Zgraggen, Carsten Binnig, Tim Kraska:
IDEBench: A Benchmark for Interactive Data Exploration. 1555-1569 - Leilani Battle, Philipp Eichmann, Marco Angelini, Tiziana Catarci, Giuseppe Santucci, Yukun Zheng, Carsten Binnig, Jean-Daniel Fekete, Dominik Moritz:
Database Benchmarking for Supporting Real-Time Interactive Querying of Large Data. 1571-1587 - Sajjadur Rahman, Kelly Mack, Mangesh Bendre, Ruilin Zhang, Karrie Karahalios, Aditya G. Parameswaran:
Benchmarking Spreadsheet Systems. 1589-1599
Research 18: Main Memory Databases and Modern Hardware
- Huanchen Zhang, Xiaoxuan Liu, David G. Andersen, Michael Kaminsky, Kimberly Keeton, Andrew Pavlo:
Order-Preserving Key Compression for In-Memory Search Trees. 1601-1615 - Anil Shanbhag, Samuel Madden, Xiangyao Yu:
A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics. 1617-1632 - Clemens Lutz, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, Volker Markl:
Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects. 1633-1649 - Tiemo Bang, Ismail Oukid, Norman May, Ilia Petrov, Carsten Binnig:
Robust Performance of Main Memory Data Structures by Configuration. 1651-1666 - Mayuresh Kunjir, Shivnath Babu:
Black or White? How to Develop an AutoTuner for Memory-based Analytics. 1667-1683
Research 19: Machine Learning Systems and Applications
- Supun Nakandala, Arun Kumar:
Vista: Optimized System for Declarative Feature Transfer from Deep CNNs at Scale. 1685-1700 - Behrouz Derakhshan, Alireza Rezaei Mahdiraji, Ziawasch Abedjan, Tilmann Rabl, Volker Markl:
Optimizing Machine Learning Workloads in Collaborative Environments. 1701-1716 - Nilaksh Das, Sanya Chaba, Renzhi Wu, Sakshi Gandhi, Duen Horng Chau, Xu Chu:
GOGGLES: Automatic Image Labeling with Affinity Coding. 1717-1732