Paper Info
Title
Demonstration of VerdictDB, the Platform-Independent AQP System.
Abstract
We demonstrate VerdictDB, the first platform-independent approximate query processing (AQP) system. Unlike existing AQP systems that are tightly-integrated into a specific database, VerdictDB operates at the driver-level, acting as a middleware between users and off-the-shelf database systems. In other words, VerdictDB requires no modifications to the database internals; it simply relies on rewriting incoming queries such that the standard execution of the rewritten queries under relational semantics yields approximate answers to the original queries. VerdictDB exploits a novel technique for error estimation called variational subsampling, which is amenable to efficient computation via SQL. In this demonstration, we showcase VerdictDB's performance benefits (up to two orders of magnitude) compared to the queries that are issued directly to existing query engines. We also illustrate that the approximate answers returned by VerdictDB are nearly identical to the exact answers. We use Apache Spark SQL and Amazon Redshift as two examples of modern distributed query platforms. We allow the audience to explore VerdictDB using a web-based interface (e.g., Hue or Apache Zeppelin) to issue queries and visualize their answers. VerdictDB is currently open-sourced and available under Apache License (V2).
Year
DOI
Venue
2018
10.1145/3183713.3193538
SIGMOD/PODS '18: International Conference on Management of Data Houston TX USA June, 2018
Keywords
Field
DocType
Approximate query processing,data analytics
Middleware,SQL,Data mining,Spark (mathematics),Information retrieval,Kripke semantics,Data analysis,Computer science,Exploit,Rewriting,Computation
Conference
ISSN
ISBN
Citations 
0730-8078
978-1-4503-4703-7
1
PageRank 
References 
Authors
0.35
22
5
Name
Order
Citations
PageRank
Wen He110.68
Yongjoo Park2995.93
Idris Hanafi310.35
Jacob Yatvitskiy410.35
Barzan Mozafari581938.21