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Yosef Shatsky

dblp:13/6898 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Storage systems · 71% Cloud and datacenter computing · 29%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › data reduction
data deduplication
0.822020
Sketching Volume Capacities in Deduplicated Storage · ACM Trans. Storage 2020
Sketching Volume Capacities in Deduplicated Storage · FAST 2019
Cloud and datacenter computing › resource prediction
capacity estimation
0.412020
Sketching Volume Capacities in Deduplicated Storage · ACM Trans. Storage 2020
Storage systems › flash and SSD
SSD array
0.112020
Sketching Volume Capacities in Deduplicated Storage · ACM Trans. Storage 2020
Storage systems
storage reliability
0.112019
Sketching Volume Capacities in Deduplicated Storage · FAST 2019

Methods — techniques the papers use, named apart from their topics

sketching · 0.8analytical accuracy guarantees · 0.4
YearPublicationVenuePosition
2020 Sketching Volume Capacities in Deduplicated Storage
abstract
The adoption of deduplication in storage systems has introduced significant new challenges for storage management. Specifically, the physical capacities associated with volumes are no longer readily available. In this work, we introduce a new approach to analyzing capacities in deduplicated storage environments. We provide sketch-based estimations of fundamental capacity measures required for managing a storage system: How much physical space would be reclaimed if a volume or group of volumes were to be removed from a system (the reclaimable capacity) and how much of the physical space should be attributed to each of the volumes in the system (the attributed capacity). Our methods also support capacity queries for volume groups across multiple storage systems, e.g., how much capacity would a volume group consume after being migrated to another storage system? We provide analytical accuracy guarantees for our estimations as well as empirical evaluations. Our technology is integrated into a prominent all-flash storage array and exhibits high performance even for very large systems. We also demonstrate how this method opens the door for performing placement decisions at the data-center level and obtaining insights on deduplication in the field.
Danny Harnik, Moshe Hershcovitch, Yosef Shatsky, Amir Epstein, Ronen I. Kat
ACM Trans. Storage3
2019 Sketching Volume Capacities in Deduplicated Storage
Danny Harnik, Moshe Hershcovitch, Yosef Shatsky, Amir Epstein, Ronen I. Kat
FAST3