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4th USENIX Conference on File and Storage Technologies—Abstract
Pp. 59–72 of the Proceedings
Awarded Best Paper!
Ursa Minor: versatile cluster-based storage
Michael Abd-El-Malek, William V. Courtright II, Chuck Cranor, Gregory R. Ganger,
James Hendricks, Andrew J. Klosterman, Michael Mesnier, Manish Prasad,
Brandon Salmon, Raja R. Sambasivan, Shafeeq Sinnamohideen,
John D. Strunk, Eno Thereska, Matthew Wachs, Jay J. Wylie, Carnegie Mellon University
Abstract
No single encoding scheme or fault model is optimal
for all data. A versatile storage system allows them to
be matched to access patterns, reliability requirements,
and cost goals on a per-data item basis. Ursa Minor is
a cluster-based storage system that allows data-specific
selection of, and on-line changes to, encoding schemes
and fault models. Thus, different data types can share a
scalable storage infrastructure and still enjoy specialized
choices, rather than suffering from "one size fits all." Experiments
with Ursa Minor show performance benefits
of 2–3x when using specialized choices as opposed to
a single, more general, configuration. Experiments also
show that a single cluster supporting multiple workloads
simultaneously is much more efficient when the choices
are specialized for each distribution rather than forced
to use a "one size fits all" configuration. When using
the specialized distributions, aggregate cluster throughput
nearly doubled.
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