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- research-articleJune 2016
Low-Overhead Asynchronous Checkpointing in Main-Memory Database Systems
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1539–1551https://doi.org/10.1145/2882903.2915966As it becomes increasingly common for transaction processing systems to operate on datasets that fit within the main memory of a single machine or a cluster of commodity machines, traditional mechanisms for guaranteeing transaction durability---which ...
- research-articleJune 2016
Microblogs Data Management Systems: Querying, Analysis, and Visualization
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 2219–2222https://doi.org/10.1145/2882903.2912570Microblogs data, e.g., tweets, reviews, news comments, and social media comments, has gained considerable attention in recent years due to its popularity and rich contents. Nowadays, microblogs applications span a wide spectrum of interests, including ...
- research-articleJune 2016
Provenance: On and Behind the Screens
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 2213–2217https://doi.org/10.1145/2882903.2912568Collecting and processing provenance, i.e., information describing the production process of some end product, is important in various applications, e.g., to assess quality, to ensure reproducibility, or to reinforce trust in the end product. In the ...
- research-articleJune 2016
SnappyData: A Hybrid Transactional Analytical Store Built On Spark
- Jags Ramnarayan,
- Barzan Mozafari,
- Sumedh Wale,
- Sudhir Menon,
- Neeraj Kumar,
- Hemant Bhanawat,
- Soubhik Chakraborty,
- Yogesh Mahajan,
- Rishitesh Mishra,
- Kishor Bachhav
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 2153–2156https://doi.org/10.1145/2882903.2899408In recent years, our customers have expressed frustration in the traditional approach of using a combination of disparate products to handle their streaming, transactional and analytical needs. The common practice of stitching heterogeneous environments ...
- research-articleJune 2016
FERARI: A Prototype for Complex Event Processing over Streaming Multi-cloud Platforms
- Ioannis Flouris,
- Vasiliki Manikaki,
- Nikos Giatrakos,
- Antonios Deligiannakis,
- Minos Garofalakis,
- Michael Mock,
- Sebastian Bothe,
- Inna Skarbovsky,
- Fabiana Fournier,
- Marko Stajcer,
- Tomislav Krizan,
- Jonathan Yom-Tov,
- Taji Curin
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 2093–2096https://doi.org/10.1145/2882903.2899395In this demo, we present FERARI, a prototype that enables real-time Complex Event Processing (CEP) for large volume event data streams over distributed topologies. Our prototype constitutes, to our knowledge, the first complete, multi-cloud based end-to-...
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- research-articleJune 2016
CLAMS: Bringing Quality to Data Lakes
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 2089–2092https://doi.org/10.1145/2882903.2899391With the increasing incentive of enterprises to ingest as much data as they can in what is commonly referred to as "data lakes", and with the recent development of multiple technologies to support this "load-first" paradigm, the new environment presents ...
- research-articleJune 2016
QFix: Demonstrating Error Diagnosis in Query Histories
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 2177–2180https://doi.org/10.1145/2882903.2899388An increasing number of applications in all aspects of society rely on data. Despite the long line of research in data cleaning and repairs, data correctness has been an elusive goal. Errors in the data can be extremely disruptive, and are detrimental ...
- research-articleJune 2016
SQL Schema Design: Foundations, Normal Forms, and Normalization
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 267–279https://doi.org/10.1145/2882903.2915239Normalization helps us find a database schema at design time that can process the most frequent updates efficiently at run time. Unfortunately, relational normalization only works for idealized database instances in which duplicates and null markers are ...
- research-articleJune 2016
Sequential Data Cleaning: A Statistical Approach
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 909–924https://doi.org/10.1145/2882903.2915233Errors are prevalent in data sequences, such as GPS trajectories or sensor readings. Existing methods on cleaning sequential data employ a constraint on value changing speeds and perform constraint-based repairing. While such speed constraints are ...
- research-articleJune 2016
Matrix Sketching Over Sliding Windows
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1465–1480https://doi.org/10.1145/2882903.2915228Large-scale matrix computation becomes essential for many data data applications, and hence the problem of sketching matrix with small space and high precision has received extensive study for the past few years. This problem is often considered in the ...
- research-articleJune 2016
Distributed Set Reachability
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1247–1261https://doi.org/10.1145/2882903.2915226In this paper, we focus on the efficient and scalable processing of set-reachability queries over a distributed, directed data graph. A "set-reachability query" is a generalized form of a reachability query, in which we consider two sets S and T of ...
- research-articleJune 2016
Scalable Approximate Query Tracking over Highly Distributed Data Streams
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1497–1512https://doi.org/10.1145/2882903.2915225The recently-proposed Geometric Monitoring (GM) method has provided a general tool for the distributed monitoring of arbitrary non-linear queries over streaming data observed by a collection of remote sites, with numerous practical applications. ...
- research-articleJune 2016
Graph Stream Summarization: From Big Bang to Big Crunch
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1481–1496https://doi.org/10.1145/2882903.2915223A graph stream, which refers to the graph with edges being updated sequentially in a form of a stream, has important applications in cyber security and social networks. Due to the sheer volume and highly dynamic nature of graph streams, the practical ...
- research-articleJune 2016
Efficient and Progressive Group Steiner Tree Search
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 91–106https://doi.org/10.1145/2882903.2915217The Group Steiner Tree (GST) problem is a fundamental problem in database area that has been successfully applied to keyword search in relational databases and team search in social networks. The state-of-the-art algorithm for the GST problem is a ...
- research-articleJune 2016
Expressive Query Construction through Direct Manipulation of Nested Relational Results
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 1377–1392https://doi.org/10.1145/2882903.2915210Despite extensive research on visual query systems, the standard way to interact with relational databases remains to be through SQL queries and tailored form interfaces. We consider three requirements to be essential to a successful alternative: (1) ...
- research-articleJune 2016
A Hybrid Approach to Functional Dependency Discovery
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 821–833https://doi.org/10.1145/2882903.2915203Functional dependencies are structural metadata that can be used for schema normalization, data integration, data cleansing, and many other data management tasks. Despite their importance, the functional dependencies of a specific dataset are usually ...
- research-articleJune 2016
ParTime: Parallel Temporal Aggregation
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 999–1010https://doi.org/10.1145/2882903.2903732This paper presents ParTime, a parallel algorithm for temporal aggregation. Temporal aggregation is one of the most important, yet most complex temporal query operators. It has been extensively studied in the past, but so far there has only been one ...
- research-articleJune 2016
SQLShare: Results from a Multi-Year SQL-as-a-Service Experiment
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 281–293https://doi.org/10.1145/2882903.2882957We analyze the workload from a multi-year deployment of a database-as-a-service platform targeting scientists and data scientists with minimal database experience. Our hypothesis was that relatively minor changes to the way databases are delivered can ...
- research-articleJune 2016
Ontological Pathfinding
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 835–846https://doi.org/10.1145/2882903.2882954Recent years have seen a drastic rise in the construction of web-scale knowledge bases (e.g., Freebase, YAGO, DBPedia). These knowledge bases store structured information about real-world people, places, organizations, etc. However, due to limitations ...
- research-articleJune 2016
Tornado: A System For Real-Time Iterative Analysis Over Evolving Data
SIGMOD '16: Proceedings of the 2016 International Conference on Management of DataJune 2016, Pages 417–430https://doi.org/10.1145/2882903.2882950There is an increasing demand for real-time iterative analysis over evolving data. In this paper, we propose a novel execution model to obtain timely results at given instants. We notice that a loop starting from a good initial guess usually converges ...