Linear Road implementation on PC
This work was funded by ASTRON and VINNOVA.
SCSQ
(pronounced
'sisque', Supercomputer Stream Query processor) is a Data Stream
Management System (DSMS) that enables queries over high-volume
distributed streams.It enables high level specification of distributed
stream queries that filter, transform, and join data from different
kinds of distributed streaming data sources. The SCSQ prototype that
runs on a variety of hardware platforms, from Windows to IBM BlueGene
massively parallel computers.
The performance of the SCSQ prototype has been
evaluated using the Linear
Road
Benchmark for data stream management systems. Linear Road
simulates an expressway system with dynamically varying toll rates
producing data streams to be processed by a DSMS. The performance of a
DSMS is measured as its L-rating,
which
is the number of expressways the system can process in real-time.
It is endorsed by
several universities, including Brandeis, Brown, MIT, and
Stanford.
New: The highly scalable
parallel implementation of Linear Road SCSQ-PLR
now achieves L=64, which is substantially improved scalability over
previously published results for the Linear Road Benchmark:
E. Zeitler and T.Risch: Scalable Splitting
of Massive Data
Streams, to be presented at Proc. 15th
Conf. on Database Systems for Advanced Application, DASFAA
2010., Tokyo, Japan, 1-4 April, 2010 (abstract).
Addendum:
Algebraic
derivation
of Maxtree
The downloadable and ready-to-run SCSQ-LR
implements Linear
Road with SCSQ on a single PC running Windows. It passes the Linear
Road benchmark for L=1.5, i.e. SCSQ-LR can process data from 1.5
expressways in real-time on a stationary PC (Fujitsu-Siemens 2.21 GHz
AMD64 4200+ with 2.87 GB of RAM) or a laptop PC (LG, 1.73
GHz, 1 GB RAM). It handles L=1.0 on a Thinkpad
notebook X40 (1.2GHz Pentium M, 760MB RAM).
Download SCSQ-LR here.
The
SCSQ-LR implementation is described in the MSc Thesis report:
Benchmarking
the
performance
of a data stream management system.
Read more about SCSQ in:
G.Gidofalvi, T.B. Pedersen, T.Risch, and
E.Zeitler: Highly
Scalable
Trip
Grouping for Large Scale Collective Transportation
Systems, Proc. 11th
International
Conference on Extending Database Technology, EDBT 2008 ,
Nantes, France, March 2008.
E.Zeitler and
T.Risch: Using stream queries to measure communication performance of
a parallel computing environment. First International
Workshop on Distributed Event Processing, Systems and Applications
(DEPSA), Toronto, Canada, June 29, 2007.
© 2007 Uppsala
Universitet, Department
of Information Technology, Box 337, 751 05 Uppsala, Seden | This page
is maintained by Tore
Risch |