Top-k semantic caching:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
2015
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| Schlagworte: | |
| Online-Zugang: | kostenfrei Volltext Inhaltsverzeichnis |
| Beschreibung: | 257 S. graph. Darst. |
Internformat
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Datensatz im Suchindex
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| adam_text | Contents
Abstract i
Contents iii
J. Fundamentals 1
1. Introduction and Motivation 3
1.1. Semantic Caching..................................................... 3
1.2. Running Example ..................................................... 5
1.2.1. Three Queries................................................. 6
1.2.2. Database Instance............................................. 7
1.2.3. A Motivation for Top-k Semantic Caching ...................... 7
1.3. Problem Description..................................................13
1.4. Approach.............................................................13
1.5. Assumptions..........................................................14
1.6. Contributions........................................................15
1.7. Overview.............................................................16
2. Related Work of Semantic Caching 19
2.1. Semantic Caching of SQL Queries.................................... 19
2.2. Semantic Caching of Non-SQL Queries..................................22
2.2.1. XML Databases .............................................. ■ 22
2.2.2. Web Queries and Information Retrieval ........................23
2.2.3. Spatial Data................................................ 23
2.3. Other Related Caching Techniques.....................................23
2.3.1. Logical Caching ..............................................24
2.3.2. Table Caching ................................................24
2.3.3. Answering Queries Using Views ................................25
2.3.4. Caching of Top-k Queries with Linear Score Functions..........25
3. Satisfiability 27
3.1. Satisfiablity and Domains............................................27
3.1.1. Variables and Domains ........................................28
Contents
3.1.2. The Varchar Domain..............................................28
3.1.3. From SAT to SMT ................................................30
3.2. SMT Solver..............................................................31
3.2.1. Solver Selection............................................... 31
3.2.2. Hybrid Solver....................................................33
3.3. Three-valued Logic and SQL..............................................41
3.3.1. Conjunction, Disjunction, Negation............................. 41
3.3.2. Isunknown .....................................................41
3.3.3. Partial Equivalence..............................................44
3.4. Satisfiability and Three-valued Logic...................................46
3.4.1. Overlaps ........................................................46
3.4.2. Subsumptions ....................................................47
II. Top-k Semantic Cache Design 51
4. Segments 53
4.1. Segment Definition......................................................53
4.1.1. Definition.......................................................53
4.1.2. Conditions ......................................................56
4.1.3. Order By Condition of Lexicographical Orderings..................60
4.1.4. Orderings Using Arbitrary Score Functions........................63
4.2. Set Operations on Segments..............................................67
4.2.1. Creation of a New Segment........................................67
4.2.2. Difference of Two Segments ......................................78
4.2.3. Intersection of Two Segments.................................. . 92
4.2.4. Union of Two Segments............................................96
4.2.4.1. The General Case.........................................96
4.2.4.2. A Special Case .........................................101
5. Pipelining 107
5.1. Multidimensional Histograms ......................................... 107
5.1.1. Definition.................................................... . 108
5.2. Histograms for the Estimation of Query Bounds..........................109
5.2.1. Properties of Histograms for the Estimation of Query Bounds . . .109
5.2.2. NP-Completeness of Optimal Histogram Selection .................112
5.3. Estimating Query Bounds with Histograms................................117
5.3.1. The Idea .......................................................117
5.3.2. A Sample Multidimensional Histogram.............................120
5.3.3. The Algorithm ..................................................123
5.3.4. Two Examples....................................................130
IV
Contents
5.3.5. Generalization of Supported Orderings
144
6. Top-k Semantic Caching
6.1. Organization .....................
6.2. Query Processing .................
6.2.1. Find Overlapping Segments
6.2.2. Load Missing Attributes . .
6.2.3. Load More Tuples...........
6.2.4. Answer Query ..............
6.2.5. Coalescing Strategies . . .
6.2.5.1. Full coalescing . .
6.2.5.2. No coalescing . .
149
149
153
153
153
155
155
160
160
162
III. Prototype IQCache, Evaluation and Discussion 165
7. Implementation 167
7.1. Overview ...................................................167
7.2. Best Cache Replacement Strategy.............................170
7.3. Best Flistograms for the Estimation of Query Bounds.........170
8. Evaluation 171
8.1. Benchmark Selection ........................................171
8.2. Caches......................................................174
8.3. Set-up.................................................... 175
8.4. Twitter Benchmark ............................... 179
8.4.1. Description.......................................... 179
8.4.2. Evaluation ......................................... 179
8.4.2.1. Cacho Size and I lit Rate .................. 179
8.4.2.2. Cache Size and Execution Tirno...............180
8.4.2.3. Server I .atency and Execution Time..........180
8.4.2.4. Throughput and Execution Time .............. 182
8.4.2.5. Satisfiability Checks and Execution Tirno ......... 182
8.4.2.6. Estimation Performance and Execution Time ....... 183
8.4.2.7. Scale and Hit Rate........................ 186
8.4.2.8. Scale and Execution Time .....................186
8.4.2.9. Scale and Number of Considered Segments.......186
8.4.2.10. Scale and Number of Used Segments............188
8.5. Yahoo! Cloud Serving Benchmark .............................190
8.5.1. Description...........................................190
v
Contents
8.5.2. Evaluation.....................................................190
8.5.2.1. Cache Size and Hit Rate..............................190
8.5.2.2. Cache Size and Execution Time........................191
8.5.2.3. Server Latency and Execution Time....................191
8.5.2.4. Throughput and Execution Time........................193
8.5.2.5. Satisfiability Checks and Execution Time...............193
8.5.2.6. Estimation Performance and Execution Time...........195
8.5.2.7. Scale and Hit Rate................................197
8.5.2.8. Scale and Execution Time .....................199
8.5.2.9. Scale and Number of Considered Segments..............199
8.5.2.10. Scale and Number of Used Segments.....................201
8.6. MonArch 3 ...........................................................203
8.6.1. Description....................................................203
8.6.2. Evaluation.....................................................204
8.6.2.1. Cache Size and Hit Rate...............................204
8.6.2.2. Cache Size and Execution Time.........................205
8.7. Discussion and Comparison of Results..............................207
9. Conclusion 209
9.1. Future Work............................................................209
9.1.1. Prefetching....................................................209
9.1.2. Context...................................................... 210
9.1.3. The Mobile Use Case............................................211
9.2. Conclusion...........................................................214
A. Histogram Creation with Window Functions 217
Bibliography 221
List of Figures 243
List of Tables 247
List of Algorithms 249
List of Listings 251
List of Examples 253
List of Definitions 255
List of Propositions, Theorems and Corollaries 257
vi
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| spelling | Ehlers, Christoph Verfasser aut Top-k semantic caching Christoph Ehlers 2015 257 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Passau, Univ., Diss., 2015 Abfrageverarbeitung (DE-588)4378490-2 gnd rswk-swf Semantisches Caching (DE-588)4820029-3 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Semantisches Caching (DE-588)4820029-3 s Abfrageverarbeitung (DE-588)4378490-2 s DE-604 Erscheint auch als Online-Ausgabe urn:nbn:de:bvb:739-opus4-3055 https://opus4.kobv.de/opus4-uni-passau/frontdoor/index/index/docId/305 kostenfrei Volltext https://nbn-resolving.org/urn:nbn:de:bvb:739-opus4-3055 Resolving-System Volltext Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028141851&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Top-k semantic caching |
| title_auth | Top-k semantic caching |
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| title_full | Top-k semantic caching Christoph Ehlers |
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| title_full_unstemmed | Top-k semantic caching Christoph Ehlers |
| title_short | Top-k semantic caching |
| title_sort | top k semantic caching |
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