The Snapshot Index: An I/O-Optimal access method for timeslice queries
We present an access method for timeslice queries that reconstructs a past state s( t) of a time-evolving collection of objects, in O ( sol log bn + ¦s(t)¦ b ) I/O's, where ¦s(t)¦ denotes the size of the collection at time t, n is the total number of changes in the collection's evolution a...
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| Veröffentlicht in: | Information systems (Oxford) 1995, Vol.20 (3), p.237-260 |
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| container_title | Information systems (Oxford) |
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| creator | Tsotras, Vassilis J. Kangelaris, Nickolas |
| description | We present an access method for timeslice queries that reconstructs a past state
s(
t) of a time-evolving collection of objects, in
O
(
sol
log
bn + ¦s(t)¦
b
) I/O's, where ¦s(t)¦ denotes the size of the collection at time
t,
n is the total number of changes in the collection's evolution and
b is the size of an I/O transfer. Changes include the addition, deletion or attribute modification of objects; they are assumed to occur in increasing time order and always affect the most current state of the collection (thus our index supports transaction-time.) The space used is
O
(
n
b
) while the update processing is constant per change, i.e., independent of
n. This is the first I/O-optimal access method for this problem using
O
(
n
b
) space and
O
(1) updating (in the expected amortized sense due to the use of hashing.) This performance is also achieved for interval intersection temporal queries. An advantage of our approach is that its performance can be tuned to match particular application needs (trading space for query time and vice versa). In addition, the Snapshot Index can naturally migrate data on a write-once optical medium while maintaining the same performance bounds. |
| doi_str_mv | 10.1016/0306-4379(95)00011-R |
| format | Article |
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s(
t) of a time-evolving collection of objects, in
O
(
sol
log
bn + ¦s(t)¦
b
) I/O's, where ¦s(t)¦ denotes the size of the collection at time
t,
n is the total number of changes in the collection's evolution and
b is the size of an I/O transfer. Changes include the addition, deletion or attribute modification of objects; they are assumed to occur in increasing time order and always affect the most current state of the collection (thus our index supports transaction-time.) The space used is
O
(
n
b
) while the update processing is constant per change, i.e., independent of
n. This is the first I/O-optimal access method for this problem using
O
(
n
b
) space and
O
(1) updating (in the expected amortized sense due to the use of hashing.) This performance is also achieved for interval intersection temporal queries. An advantage of our approach is that its performance can be tuned to match particular application needs (trading space for query time and vice versa). In addition, the Snapshot Index can naturally migrate data on a write-once optical medium while maintaining the same performance bounds.</description><identifier>ISSN: 0306-4379</identifier><identifier>EISSN: 1873-6076</identifier><identifier>DOI: 10.1016/0306-4379(95)00011-R</identifier><identifier>CODEN: INSYD6</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Access Methods ; Access to Information ; Applied sciences ; Computer science; control theory; systems ; Data Structures ; Exact sciences and technology ; Indexes ; Information systems. Data bases ; Mathematical Formulas ; Memory organisation. Data processing ; Optical Data Disks ; Optimal I/O ; Query Processing ; Software ; Time Oriented Data ; Transaction-time Databases</subject><ispartof>Information systems (Oxford), 1995, Vol.20 (3), p.237-260</ispartof><rights>1995</rights><rights>1995 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-58163c82566072f3c6f6242f98a96d0c04f433e9089cbc5834f28b2a12ff83b43</citedby><cites>FETCH-LOGICAL-c431t-58163c82566072f3c6f6242f98a96d0c04f433e9089cbc5834f28b2a12ff83b43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/0306-4379(95)00011-R$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://eric.ed.gov/ERICWebPortal/detail?accno=EJ505403$$DView record in ERIC$$Hfree_for_read</backlink><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=3538264$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Tsotras, Vassilis J.</creatorcontrib><creatorcontrib>Kangelaris, Nickolas</creatorcontrib><title>The Snapshot Index: An I/O-Optimal access method for timeslice queries</title><title>Information systems (Oxford)</title><description>We present an access method for timeslice queries that reconstructs a past state
s(
t) of a time-evolving collection of objects, in
O
(
sol
log
bn + ¦s(t)¦
b
) I/O's, where ¦s(t)¦ denotes the size of the collection at time
t,
n is the total number of changes in the collection's evolution and
b is the size of an I/O transfer. Changes include the addition, deletion or attribute modification of objects; they are assumed to occur in increasing time order and always affect the most current state of the collection (thus our index supports transaction-time.) The space used is
O
(
n
b
) while the update processing is constant per change, i.e., independent of
n. This is the first I/O-optimal access method for this problem using
O
(
n
b
) space and
O
(1) updating (in the expected amortized sense due to the use of hashing.) This performance is also achieved for interval intersection temporal queries. An advantage of our approach is that its performance can be tuned to match particular application needs (trading space for query time and vice versa). In addition, the Snapshot Index can naturally migrate data on a write-once optical medium while maintaining the same performance bounds.</description><subject>Access Methods</subject><subject>Access to Information</subject><subject>Applied sciences</subject><subject>Computer science; control theory; systems</subject><subject>Data Structures</subject><subject>Exact sciences and technology</subject><subject>Indexes</subject><subject>Information systems. Data bases</subject><subject>Mathematical Formulas</subject><subject>Memory organisation. 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Data bases</topic><topic>Mathematical Formulas</topic><topic>Memory organisation. 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s(
t) of a time-evolving collection of objects, in
O
(
sol
log
bn + ¦s(t)¦
b
) I/O's, where ¦s(t)¦ denotes the size of the collection at time
t,
n is the total number of changes in the collection's evolution and
b is the size of an I/O transfer. Changes include the addition, deletion or attribute modification of objects; they are assumed to occur in increasing time order and always affect the most current state of the collection (thus our index supports transaction-time.) The space used is
O
(
n
b
) while the update processing is constant per change, i.e., independent of
n. This is the first I/O-optimal access method for this problem using
O
(
n
b
) space and
O
(1) updating (in the expected amortized sense due to the use of hashing.) This performance is also achieved for interval intersection temporal queries. An advantage of our approach is that its performance can be tuned to match particular application needs (trading space for query time and vice versa). In addition, the Snapshot Index can naturally migrate data on a write-once optical medium while maintaining the same performance bounds.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/0306-4379(95)00011-R</doi><tpages>24</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0306-4379 |
| ispartof | Information systems (Oxford), 1995, Vol.20 (3), p.237-260 |
| issn | 0306-4379 1873-6076 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_25982977 |
| source | Access via ScienceDirect (Elsevier) |
| subjects | Access Methods Access to Information Applied sciences Computer science control theory systems Data Structures Exact sciences and technology Indexes Information systems. Data bases Mathematical Formulas Memory organisation. Data processing Optical Data Disks Optimal I/O Query Processing Software Time Oriented Data Transaction-time Databases |
| title | The Snapshot Index: An I/O-Optimal access method for timeslice queries |
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