Abstract
Modern scientific computing generates petabytes of data in billions of files that must be managed. These files are often organized, by name, in a hierarchical directory tree common to most file systems. As the scale of data has increased, this has proven to be a poor method of file organization. Recent tools have allowed for users to navigate files based on file metadata attributes to provide more meaningful organization. In order to search this metadata, it is often stored on separate metadata servers. This solution has drawbacks though due to the multi-tiered architecture of many large scale storage solutions. As data is moved between various tiers of storage and/or modified, the overhead incurred for maintaining consistency between these tiers and the metadata server becomes very large. As scientific systems continue to push towards exascale, this problem will become more pronounced. A simpler option is to bypass the overhead of the metadata server and use the metadata storage inherent to the file system. This approach currently has few tools to perform operations at a large scale though. This paper introduces the prototype for Pantheon, a file system search tool designed to use the metadata storage within the file system itself, bypassing the overhead from metadata servers. Pantheon is also designed with the scientific community's push towards exascale computing in mind. Pantheon combines hierarchical partitioning, query optimization, and indexing to perform efficient metadata searches over large scale file systems.
| Original language | English |
|---|---|
| Title of host publication | Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings |
| Pages | 461-469 |
| Number of pages | 9 |
| DOIs | |
| Publication status | Published - 11 Aug 2011 |
| Externally published | Yes |
| Event | 23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011 - Portland, OR, United States Duration: 20 Jul 2011 → 22 Jul 2011 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 6809 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011 |
|---|---|
| Country | United States |
| City | Portland, OR |
| Period | 20/7/11 → 22/7/11 |
Fingerprint
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Pantheon : Exascale file system search for scientific computing. / Naps, Joseph L.; Mokbel, Mohamed; Du, David H C.
Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings. 2011. p. 461-469 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6809 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Pantheon
T2 - Exascale file system search for scientific computing
AU - Naps, Joseph L.
AU - Mokbel, Mohamed
AU - Du, David H C
PY - 2011/8/11
Y1 - 2011/8/11
N2 - Modern scientific computing generates petabytes of data in billions of files that must be managed. These files are often organized, by name, in a hierarchical directory tree common to most file systems. As the scale of data has increased, this has proven to be a poor method of file organization. Recent tools have allowed for users to navigate files based on file metadata attributes to provide more meaningful organization. In order to search this metadata, it is often stored on separate metadata servers. This solution has drawbacks though due to the multi-tiered architecture of many large scale storage solutions. As data is moved between various tiers of storage and/or modified, the overhead incurred for maintaining consistency between these tiers and the metadata server becomes very large. As scientific systems continue to push towards exascale, this problem will become more pronounced. A simpler option is to bypass the overhead of the metadata server and use the metadata storage inherent to the file system. This approach currently has few tools to perform operations at a large scale though. This paper introduces the prototype for Pantheon, a file system search tool designed to use the metadata storage within the file system itself, bypassing the overhead from metadata servers. Pantheon is also designed with the scientific community's push towards exascale computing in mind. Pantheon combines hierarchical partitioning, query optimization, and indexing to perform efficient metadata searches over large scale file systems.
AB - Modern scientific computing generates petabytes of data in billions of files that must be managed. These files are often organized, by name, in a hierarchical directory tree common to most file systems. As the scale of data has increased, this has proven to be a poor method of file organization. Recent tools have allowed for users to navigate files based on file metadata attributes to provide more meaningful organization. In order to search this metadata, it is often stored on separate metadata servers. This solution has drawbacks though due to the multi-tiered architecture of many large scale storage solutions. As data is moved between various tiers of storage and/or modified, the overhead incurred for maintaining consistency between these tiers and the metadata server becomes very large. As scientific systems continue to push towards exascale, this problem will become more pronounced. A simpler option is to bypass the overhead of the metadata server and use the metadata storage inherent to the file system. This approach currently has few tools to perform operations at a large scale though. This paper introduces the prototype for Pantheon, a file system search tool designed to use the metadata storage within the file system itself, bypassing the overhead from metadata servers. Pantheon is also designed with the scientific community's push towards exascale computing in mind. Pantheon combines hierarchical partitioning, query optimization, and indexing to perform efficient metadata searches over large scale file systems.
UR - http://www.scopus.com/inward/record.url?scp=79961182850&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79961182850&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22351-8_29
DO - 10.1007/978-3-642-22351-8_29
M3 - Conference contribution
SN - 9783642223501
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 461
EP - 469
BT - Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings
ER -