Filters








18 Hits in 5.8 sec

DuckDB

Mark Raasveldt, Hannes Mühleisen
2019 Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19  
The immense popularity of SQLite shows that there is a need for unobtrusive in-process data management solutions. However, there is no such system yet geared towards analytical workloads.  ...  In our demonstration, we pit DuckDB against other data management solutions to showcase its performance in the embedded analytics scenario.  ...  We are also particularly indebted to the TUM database group for their papers on query optimization, window functions, storage and concurrency control that we used to implement DuckDB.  ... 
doi:10.1145/3299869.3320212 dblp:conf/sigmod/RaasveldtM19 fatcat:nzgaso2nwzgtbh2dejdebq3rpq

Query-Driven Learning for Next Generation Predictive Modeling & Analytics

Fotis Savva
2019 Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19  
As data-size is increasing exponentially, new paradigm shifts have to emerge allowing fast exploitation of data by everybody.  ...  Our query-driven approach will learn and adapt on-the-fly machine learning models, based solely on query-answer interactions, which can be used for answering analytical queries.  ...  SIGMOD '19, June 30-July 5, 2019, Amsterdam, Netherlands © 2019 Copyright held by the owner/author(s).  ... 
doi:10.1145/3299869.3300101 dblp:conf/sigmod/Savva19 fatcat:qcqacdeqpfajfkb2optxpv2lca

Estimating Cardinalities with Deep Sketches

Andreas Kipf, Dimitri Vorona, Jonas Müller, Thomas Kipf, Bernhard Radke, Viktor Leis, Peter Boncz, Thomas Neumann, Alfons Kemper
2019 Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19  
We introduce Deep Sketches, which are compact models of databases that allow us to estimate the result sizes of SQL queries.  ...  Our demonstration allows users to define such sketches on the TPC-H and IMDb datasets, monitor the training process, and run ad-hoc queries against trained sketches.  ...  The query results Demonstration SIGMOD '19, June 30-July 5, 2019, Amsterdam, Netherlands are displayed with different overlays as they arrive.  ... 
doi:10.1145/3299869.3320218 dblp:conf/sigmod/KipfVMKRLB0K19 fatcat:5tofirwi6fhpderqyzgqepdpse

Query Processing in Blockchain Systems: Current State and Future Challenges

Dennis Przytarski, Christoph Stach, Clémentine Gritti, Bernhard Mitschang
2021 Future Internet  
When, in 2008, Satoshi Nakamoto envisioned the first distributed database management system that relied on cryptographically secured chain of blocks to store data in an immutable and tamper-resistant manner  ...  Owing to this use case, the blockchain system was geared towards efficient storage of data, whereas the processing of complex queries, such as provenance analyses of data history, is out of focus.  ...  In Proceedings of the 2019 International Conference on Management of Data, SIGMOD ’19, Amsterdam, The Netherlands, 30 June5 July 2019; pp. 141–158. 116.  ... 
doi:10.3390/fi14010001 fatcat:axmnkcheyjegjbbhgr4gv5345i

[Demo] Low-latency Spark Queries on Updatable Data

Alexandru Uta, Bogdan Ghit, Ankur Dave, Peter Boncz
2019 Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19  
In this demo, we show the design, implementation and performance of a new indexing abstraction in Apache Spark, called the Indexed DataFrame.  ...  We demonstrate the Indexed Dataframe on a social network dataset using microbenchmarks and real-world graph processing queries, in datasets that are continuously growing.  ...  Notice that online analytics on changing graphs is a challenging use case for Spark as graph navigation is very join-intensive, while Demonstration SIGMOD '19, June 30-July 5, 2019, Amsterdam, Netherlands  ... 
doi:10.1145/3299869.3320227 dblp:conf/sigmod/UtaGDB19 fatcat:fti376bzczcolibfj543jbptye

ANMAT

Abdulhakim Qahtan, Nan Tang, Mourad Ouzzani, Yang Cao, Michael Stonebraker
2019 Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19  
Moreover, a key application of PFDs is to use them to identify erroneous data; tuples that violate some PFDs.  ...  We propose a new type of meta-knowledge, namely pattern functional dependencies (PFDs), that combine patterns (or regex-like rules) and integrity constraints (ICs) to model the dependencies (or meta-knowledge  ...  SIGMOD'19, June 30 -July 5, 2019, Amsterdam, The Netherlands © 2019 Association for Computing Machinery.  ... 
doi:10.1145/3299869.3320209 dblp:conf/sigmod/Qahtan0OCS19 fatcat:7eenwjqjunepbnv4xds6acok6y

Design Trade-offs for a Robust Dynamic Hybrid Hash Join (Extended Version) [article]

Shiva Jahangiri, Michael J. Carey, Johann-Christoph Freytag
2021 arXiv   pre-print
The Join operator, as one of the most expensive and commonly used operators in database systems, plays a substantial role in Database Management System (DBMS) performance.  ...  We explore the impact of the number of partitions on the performance of HHJ and propose a lower bound and a default value for the number of partitions.  ...  In Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019, Peter A.  ... 
arXiv:2112.02480v1 fatcat:edxylscxrzgwlbxcmy3ku33s7m

A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios [article]

Michael A. Hedderich, Lukas Lange, Heike Adel, Jannik Strötgen, Dietrich Klakow
2021 arXiv   pre-print
After a discussion about the different dimensions of data availability, we give a structured overview of methods that enable learning when training data is sparse.  ...  As they are known for requiring large amounts of training data, there is a growing body of work to improve the performance in low-resource settings.  ...  In Pro- ceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 -July 5, 2019, pages 362-375. ACM. N. Banik, M. H.  ... 
arXiv:2010.12309v3 fatcat:26dwmlkmn5auha2ob2qdlrvla4

A Survey of Deep Active Learning [article]

Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Brij B. Gupta, Xiaojiang Chen, Xin Wang
2021 arXiv   pre-print
Deep learning (DL) is greedy for data and requires a large amount of data supply to optimize massive parameters, so that the model learns how to extract high-quality features.  ...  In recent years, due to the rapid development of internet technology, we are in an era of information torrents and we have massive amounts of data.  ...  In Proceedings of the 2018 International Conference on Management of Data, SIGMOD Conference 2018, Houston, TX, USA, June 10-15, 2018.  ... 
arXiv:2009.00236v2 fatcat:zuk2doushzhlfaufcyhoktxj7e

A Survey from Real-Time to Near Real-Time Applications in Fog Computing Environments

Eliza Gomes, Felipe Costa, Carlos De Rolt, Patricia Plentz, Mario Dantas
2021 Telecom  
This variability of concept has been due to the growing requirements for fast data communication and processing.  ...  Finally, we conduct an analytical discussion of the characteristics and proposal of articles.  ...  In Proceedings of the 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshop (DSN-W), Toulouse, France, 28 June–1 July 2016; pp. 162–167. 106.  ... 
doi:10.3390/telecom2040028 fatcat:wb3s6sjwwzhpjios7x5diotcfu

Large-Scale Remote Sensing Image Retrieval Based on Semi-Supervised Adversarial Hashing

Xu Tang, Chao Liu, Jingjing Ma, Xiangrong Zhang, Fang Liu, Licheng Jiao
2019 Remote Sensing  
The effectiveness of the hash codes learned by our SDAH model was proved by the positive experimental results counted on three public RS image archives.  ...  Through the minimax learning, the class variable would be a one-hot-like vector while the hash code would be the binary-like vector.  ...  In Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, Scottsdale, AZ, USA, 20–24 May 2012; pp. 541–552. 25.  ... 
doi:10.3390/rs11172055 fatcat:cy3ehjr2ejf7dezr4j4idc4jra

Logic2Text: High-Fidelity Natural Language Generation from Logical Forms [article]

Zhiyu Chen, Wenhu Chen, Hanwen Zha, Xiyou Zhou, Yunkai Zhang, Sairam Sundaresan, William Yang Wang
2020 arXiv   pre-print
Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences.  ...  The logical forms show diversified graph structure of free schema, which poses great challenges on the model's ability to understand the semantics.  ...  The authors are solely responsible for the contents of the paper and the opinions expressed in this publication do not reflect those of the funding agencies.  ... 
arXiv:2004.14579v2 fatcat:q7hv27p3pjfmxkvtwz7en74hpa

GPU-based Graph Traversal on Compressed Graphs

Mo Sha, Yuchen Li, Kian-Lee Tan
2019 Proceedings of the 2019 International Conference on Management of Data - SIGMOD '19  
However, the high-bandwidth device memory on GPUs has limited capacity that constrains the size of the graph to be loaded on chip.  ...  In this paper, we introduce GPU-based graph traversal on compressed graphs, so as to enable the processing of graphs having a larger size than the device memory.  ...  SIGMOD '19, June 30-July 5, 2019, Amsterdam, Netherlands © 2019 Copyright held by the owner/author(s). Publication rights licensed to ACM.  ... 
doi:10.1145/3299869.3319871 dblp:conf/sigmod/ShaLT19 fatcat:uiqk5lypujbktczpcuuyiopp5q

Lux: Always-on Visualization Recommendations for Exploratory Dataframe Workflows [article]

Doris Jung-Lin Lee, Dixin Tang, Kunal Agarwal, Thyne Boonmark, Caitlyn Chen, Jake Kang, Ujjaini Mukhopadhyay, Jerry Song, Micah Yong, Marti A. Hearst, Aditya G. Parameswaran
2021 arXiv   pre-print
We demonstrate that through the use of a careful design and three system optimizations, Lux adds no more than two seconds of overhead on top of pandas for over 98% of datasets in the UCI repository.  ...  We evaluate Lux in terms of usability via a controlled first-use study and interviews with early adopters, finding that Lux helps fulfill the needs of data scientists for visualization support within their  ...  Show Me: Automatic presentation Conference 2019, Amsterdam, The Netherlands, June 30 - July 5, 2019, pages 1277– for visual analysis.  ... 
arXiv:2105.00121v2 fatcat:gphjm3jqdzevbc4f6yvfyjod7i

Table2Charts: Learning Shared Representations for Recommending Charts on Multi-dimensional Data [article]

Mengyu Zhou, Qingtao Li, Yuejiang Li, Xinyi He, Yibo Liu, Shi Han, Dongmei Zhang
2021 arXiv   pre-print
However, to build a real-world intelligent assistant that recommends commonly composed charts, it should take the challenges of efficiency, imbalanced data hungry and table context into consideration.  ...  On a large spreadsheet corpus with 167k tables and 271k charts, we show that Table2Charts could learn a shared representation of table fields so that tasks on different chart types could mutually enhance  ...  ., Proceedings of the 2019 International Conference on Management of Data, SIGMOD Conference 2019, Amsterdam, The Netherlands, June 30 -July 5, 2019, 317-332. ACM.  ... 
arXiv:2008.11015v2 fatcat:lcypsvhvajd4bbyk46p354uik4
« Previous Showing results 1 — 15 out of 18 results