Annotating web tables through ontology matching
Vasilis Efthymiou, Oktie Hassanzadeh, et al.
OM 2016
The limitations of traditional general-purpose processors have motivated the use of specialized hardware solutions (e.g., FPGAs) to achieve higher performance in stream processing. However, state-of-the-art hardware-only solutions have limited support to adapt to changes in the query workload. In this work, we present a reconfigurable hardware-based streaming architecture that offers the flexibility to accept new queries and to change existing ones without the need for expensive hardware reconfiguration. We introduce the Online Programmable Block (OP-Block), a "Lego-like" connectable stream processing element, for constructing a custom Flexible Query Processor (FQP), suitable to a wide range of data streaming applications, including real-time data analytics, information filtering, intrusion detection, algorithmic trading, targeted advertising, and complex event processing. Through evaluations, we conclude that updating OP-Blocks to support new queries takes on the order of nano to micro-seconds (e.g., 40 ns to realize a join operator on an OP-Block), a feature critical to support of streaming applications on FPGAs.
Vasilis Efthymiou, Oktie Hassanzadeh, et al.
OM 2016
Mohammad Sadoghi, Souvik Bhattacherjee, et al.
EDBT 2018
Martin Jergler, Mohammad Sadoghi, et al.
SIGMOD 2015
Mohammad Sadoghi, Martin Jergler, et al.
IEEE TKDE