Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Adam Silberstein"'
Publikováno v:
Encyclopedia of Database Systems ISBN: 9781489979933
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b58a372d2d86dce8099f0b0ee6ddd545
https://doi.org/10.1007/978-1-4614-8265-9_93
https://doi.org/10.1007/978-1-4614-8265-9_93
Autor:
B. McMillan, David Lomax, Raghu Ramakrishnan, Adam Silberstein, Russell Sears, Masood Mortazavi, Jianjun Chen, P. P. S. Narayan
Publikováno v:
IEEE Internet Computing. 16:13-23
Data management for stateful Web applications is extremely challenging. Applications must scale as they grow in popularity, serve their content with low latency on a global scale, and be highly available, even in the face of hardware failures. This n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c8b7945643f396e2ed033cf25afadcf
https://doi.org/10.1109/mic.2011.142
https://doi.org/10.1109/mic.2011.142
Publikováno v:
Proceedings of the VLDB Endowment. 2:682-693
We consider the problem of how to best parallelize range queries in a massive scale distributed database. In traditional systems the focus has been on maximizing parallelism, for example by laying out data to achieve the highest throughput. However,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3068100191de95277614da898175eaab
https://doi.org/10.14778/1687627.1687705
https://doi.org/10.14778/1687627.1687705
Autor:
Brian F. Cooper, Hans-Arno Jacobsen, Ramana Yerneni, Daniel Weaver, Adam Silberstein, Nick Puz, Philip Bohannon, Raghu Ramakrishnan, Utkarsh Srivastava
Publikováno v:
Proceedings of the VLDB Endowment. 1:1277-1288
We describe PNUTS, a massively parallel and geographically distributed database system for Yahoo!'s web applications. PNUTS provides data storage organized as hashed or ordered tables, low latency for large numbers of concurrent requests including up
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ba9bf2b0db54777557cebcac88ba64c
https://doi.org/10.14778/1454159.1454167
https://doi.org/10.14778/1454159.1454167
Publikováno v:
ACM SIGMOD Record. 42:53-55
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f0df63ace98134186882d4819561b1d
https://doi.org/10.1145/2481528.2481540
https://doi.org/10.1145/2481528.2481540
Publikováno v:
ICDE Workshops
Enterprises (such as, Yahoo!, LinkedIn, Facebook) operate their own compute/storage infrastructure, which is effectively a “private cloud”. The private cloud consists of multiple clusters, each of which is managed independently. With HDFS, whenev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1514b3cbe54095c320b3e414e9da24cd
https://doi.org/10.1109/icdew.2013.6547458
https://doi.org/10.1109/icdew.2013.6547458
Publikováno v:
CIKM
Several social networking applications enable users to view the events generated by other users, typically friends in the social network, in the form of ``news feeds''. Friends and events are typically maintained per user and cached in memory to enab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27586e12a4c8054fde72a64f0eb336e6
https://doi.org/10.1145/2505515.2505742
https://doi.org/10.1145/2505515.2505742
Autor:
Cooper Brian F, Adwait Tumbde, Adam Silberstein, Jianjun Chen, Masood Mortazavi, Sahaya Andrews Albert, P. P. S. Narayan, Markus Klems
Publikováno v:
CloudDB@CIKM
Sherpa is a large-scale distributed and globally replicated multi-tenant cloud data storage system. Sherpa scales by horizontally partitioning data into tablets and distributing these tablets across multiple servers. While Sherpa scales for increasin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2dc856326e7cb1ef042099b05ea7cee5
https://doi.org/10.1145/2390021.2390028
https://doi.org/10.1145/2390021.2390028
Publikováno v:
CIKM
The fifth ACM international workshop on cloud data management is held in San Francisco, California, USA on October 28, 2013 and co-located with the ACM 22nd Conference on Information and Knowledge Management (CIKM). The main objective of the workshop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25dffe7d1df057b484daf4ce6cc76382
https://doi.org/10.1145/2396761.2398752
https://doi.org/10.1145/2396761.2398752
Publikováno v:
SoCC
In this paper, we present Sailfish, a new Map-Reduce framework for large scale data processing. The Sailfish design is centered around aggregating intermediate data, specifically data produced by map tasks and consumed later by reduce tasks, to impro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b9e9f525e47940ebc8ab3bc207ac17d
https://doi.org/10.1145/2391229.2391233
https://doi.org/10.1145/2391229.2391233