Providing efficient, extensible and adaptive intra-query parallelism for advanced applications:
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
2000
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Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | München, Techn. Univ., Diss., 2000 |
Beschreibung: | IV, 193 S. graph. Darst. |
Internformat
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Datensatz im Suchindex
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adam_text |
TABLE OF CONTENTS
1. INTRODUCTION 1
1.1 PARALLEL DATABASES.1
1.2 COMPLEXITY ISSUES .2
1.3 OVERVIEW.4
2. BASIC CONCEPTS AND NOTATIONS 7
2.1 INTRODUCTION .7
2.2 MIDAS SYSTEM ARCHITECTURE . 8
2.3 QUERY PROCESSING IN MIDAS.10
2.4 THE MIDAS EXECUTION MODEL .11
3. EFFICIENTLY EXPLOITING
DATA RIVERS FOR INTRA-QUERY PARALLELISM 13
3.1 INTRODUCTION .13
3.2 ANATOMY OF THE DATA RIVER CONCEPT.14
3.3 IMPLEMENTATION CONCEPTS FOR DATA RIVERS.15
3.3.1 COMMUNICATION SEGMENTS AS A CONCEPT TO IMPLEMENT DATA RIVERS .15
3.3.2 CONTROL OF DATAFLOW .16
3.3.3 CONTROL OF DATA PARTITIONING .17
3.3.4 CONTROL OF DATA MERGING . 18
3.3.5 PERFORMANCE MEASUREMENTS .18
3.3.6 RECOMMENDATIONS FOR THE PARAMETRIZATION OF DATA RIVERS .21
3.4 DEADLOCK SITUATIONS CAUSED BY INTRA-OPERATOR PARALLELISM.23
3.4.1 DEADLOCK WITHIN A DATA RIVER .23
3.4.2 DEADLOCKS IN BETWEEN DATA RIVERS .24
3.4.3 DEADLOCKS CAUSED BY BINARY OPERATORS .25
3.5 REDUCING THE NUMBER AND SIZE OF DATA RIVERS.25
3.6 REDUCING THE NUMBER OF DATA STREAMS AND EXECUTION UNITS .26
3.7 RELATED WORK.28
3.8 SUMMARY .29
4. TOPAZ
A MULTI-PHASE PARALLELIZER 31
4.1 INTRODUCTION .31
4.2 RELATED WORK.32
4.2.1 SPECIALIZED PARALLELIZATION TECHNIQUES .33
4.2.2 PARALLELIZATION USING TRADITIONAL SEQUENTIAL OPTIMIZATION
TECHNIQUES .33
4.2.3 SUITABILITY OF TRADITIONAL PARALLELIZATION TECHNIQUES
1
BIBLIOGRAFISCHE INFORMATIONEN
HTTP://D-NB.INFO/960055428
FOR UPCOMING APPLICATION SCENARIOS .34
4.2.4 SUMMARY .36
4.3 THE CASCADES OPTIMIZER FRAMEWORK.37
4.3.1 ANATOMY OF THE CASCADES OPTIMIZER FRAMEWORK .38
4.4 TOPAZ STRATEGIES.42
4.4.1 CONTROL OF THE SEARCH SPACE .43
4.4.2 CONTROL OF THE GRANULARITY OF PARALLELISM .45
4.4.3 CONTROL OF PARTITIONING STRATEGIES .46
4.4.4 CONTROL OF THE DEGREES OF PARALLELISM .46
4.5 MULTI-PHASE PARALLELIZATION.48
4.5.1 PHASE 1: INTER-OPERATOR PARALLELISM AND REFINEMENT OF GLOBAL COSTS
.48
4.5.2 PHASE 2: INTRA-OPERATOR PARALLELISM APPLIED TO HIGH-COST OPERATORS
.49
4.5.3 PHASE 3: BLOCK EXPANSION AND TREATMENT OF LOW-COST OPERATORS .51
4.5.4 PHASE 4: BLOCK COMBINATION FURTHER DECREASING
PARALLELIZATION OVERHEAD .52
4.6 PREVENTING DEADLOCK SITUATIONS.53
4.6.1 DEADLOCK-A WARE PARALLELIZATION .53
4.6.2 ASSESSMENT OF THE APPROACH .55
4.7 PERFORMANCE INVESTIGATION.56
4.8 SUMMARY.59
5. THE TOPAZ COST MODEL 61
5.1 INTRODUCTION.61
5.2 RELATED WORK.62
5.3 DERIVING THE COST MEASURES.62
5.3.1 SEQUENTIAL EXECUTION .64
5.3.2 INDEPENDENT PARALLEL EXECUTION .64
5.3.3 DEPENDENT PARALLEL EXECUTION .65
5.3.4 BLOCK BUILDING .67
5.3.5 MULTIPLE EVALUATION OF THE INPUTS .70
5.3.6 MATERIALIZING SEND OPERATORS .71
5.3.7 EXAMPLE OF A COST CALCULATION .72
5.3.8 INTRA-OPERATOR PARALLELISM .75
5.4 THE COST FORMULAE.76
5.4.1 REGULAR OPERATORS .77
5.4.2 SEND OPERATORS .78
5.4.3 RECEIVE OPERATORS .79
5.4.4 THE OPERATORS RESTRICTION, PROJECTION, NESTED LOOPS AND CARTESIAN
PRODUCT .80
5.4.5 HASH JOINS .80
5.5 RESOURCES.81
5.5.1 RESOURCE USAGE MODEL .81
5.5.2 DEFINING THE PRUNING METRIC .83
5.6 THE PAR PRUNE STRATEGY .84
5.6.1 AVERAGE COST PER CPU .85
5.6.2 AVERAGE COST PER OPERATOR .86
5.6.3 MAXIMAL DEGREE OF PARALLELISM .87
5.7^ SUMMARY.
6. ENHANCING OPTIMIZATION FOR A SUBSEQUENT PARALLELIZATION:
THE QUASI-PARALLEL COST MODEL 89
6.1 INTRODUCTION.
11
6.2 THE MODEL-M OPTIMIZER.91
6.3 THE SEQUENTIAL COST MODEL .92
6.4 THE QUASI-PARALLEL COST MODEL.93
6.4.1 BLOCKING OPERATORS . 94
6.4.2 FAVORING INDEPENDENT PARALLELISM .95
6.4.3 DEGREES OF PARALLELISM .97
6.5 PERFORMANCE MEASUREMENTS .100
6.6 SUMMARY .106
7. SCHEDULING AND LOAD BALANCING 107
7.1 INTRODUCTION.107
7.2 RELATED WORK.109
7.3 QEC STRATEGIES.110
7.3.1 DISTRIBUTED APPROACH .110
7.3.2 QEC INPUT INFORMATION .111
7.3.3 TWO-PHASE SCHEDULING .112
7.3.4 MANAGEMENT OF NON-PREEMPTIVE RESOURCES .113
7.4 QEC PHASES. 114
7.4.1 PHASE 1: COARSE SCHEDULING .114
7.4.2 PHASE 2: FINE SCHEDULING .115
7.5 SUMMARY .117
8. PARALLELIZATION OF USER-DEFINED FUNCTIONALITY 119
8.1 INTRODUCTION.119
8.2 APPLICABILITY OF STREAMJOIN FOR THE EVALUATION OF FREQUENT
ITEMSETS.120
8.2.1 RELATED WORK .122
8.2.2 DATA MINING SCENARIO .122
8.2.3 THE STREAMJOIN OPERATOR .124
8.2.4 DEFINITION OF THE CANDIDATE ITEMSETS .126
8.2.5 BACKWARD EXPLORATION (BE) OF ITEMSETS .128
8.2.6 FORWARD EXPLORATION (FE) OF ITEMSETS .131
8.2.7 SUMMARY OF PRUNING TECHNIQUES .132
8.2.8 INTEGRATION WITH THE DBMS .133
8.2.9 PARALLELIZATION POTENTIAL .136
8.2.10 IMPLEMENTATION ASPECTS .138
8.2.11 PERFORMANCE EVALUATION .139
8.2.12SUMMARY .143
8.3 APPLICABILITY OF STREAMJOIN FOR UNIVERSAL QUANTIFICATION.144
8.3.1 RELATED WORK .144
8.3.2 EXAMPLE SCENARIO 1: THE UNIVERSITY DATABASE .145
8.3.3 EXAMPLE SCENARIO 2: DATA WAREHOUSE .146
8.3.4 PERFORMANCE EVALUATION .148
8.4 SEQUENCES.151
8.5 PATTERN DISCOVERY IN GENOMIC DATABASES.153
8.6 APPLICABILITY OF STREAMJOIN IN PROFILING SERVICES.154
8.6.1 THE BOOLEAN RETRIEVAL MODEL .155
8.6.2 THE PROFILING SERVICE .155
8.6.3 MAPPING TO THE DATABASE LAYER .156
8.6.4 PERFORMANCE EVALUATION .161
8.7 CONCLUSIONS . 162
III
9. CONCLUSIONS AND FUTURE WORK 165
9.1 SUMMARY OF CONTRIBUTIONS.165
9.1.1 DATA RIVERS .165
9.1.2 THE TOPAZ PARALLELIZER .166
9.1.3 MODEL-M OPTIMIZER .166
9.1.4 THE QEC COMPONENT .167
9.1.5 THE STREAMJOIN OPERATOR .167
9.2 FUTURE WORK.168
9.2.1 QUERY EXECUTION .168
9.2.2 QUERY OPTIMIZATION AND PARALLELIZATION .168
9.2.3 RESOURCE ALLOCATION, SCHEDULING AND LOAD BALANCING .169
A. REFERENCES 171
A. L REFERENCES.171
B. OPERATORS AND RULES 179
B. L SELECTED OPERATORS USED IN THE MIDAS EXECUTION ENGINE.179
B.2 SELECTED RULES USED BY THE TOPAZ PARALLELIZER.181
B.3 LOGICAL OPERATORS USED IN MODEL-M.183
B.4 PHYSICAL OPERATORS USED IN MODEL-M.183
B. 5 RULES USED BY THE MODEL-M OPTIMIZER.184
C. PROOFS AND ALGORITHMS 185
C. 1 PROOFS RELATED TO THE MFSSEARCH ALGORITHM.185
C.2 THE MFSSEARCH ALGORITHM FOR THE BACKWARD EXPLORATION
SCENARIO.187
C. 3 THE EXPAND PROCEDURE ADAPTED TO THE FORWARD EXPLORATION
SCENARIO.189
D. AUXILIARY LISTS 191
D. L LIST OF FIGURES.191
D.2 LIST OF TABLES. 193
IV |
any_adam_object | 1 |
author | Nippl, Clara 1969- |
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discipline | Informatik |
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spelling | Nippl, Clara 1969- Verfasser (DE-588)122420225 aut Providing efficient, extensible and adaptive intra-query parallelism for advanced applications Clara Nippl 2000 IV, 193 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier München, Techn. Univ., Diss., 2000 Parallelverarbeitung (DE-588)4075860-6 gnd rswk-swf Abfrageverarbeitung (DE-588)4378490-2 gnd rswk-swf Datenbanksystem (DE-588)4113276-2 gnd rswk-swf Objektrelationales Datenbanksystem (DE-588)4534774-8 gnd rswk-swf Paralleles Datenbanksystem (DE-588)4624365-3 gnd rswk-swf Paralleler Algorithmus (DE-588)4193615-2 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Datenbanksystem (DE-588)4113276-2 s Abfrageverarbeitung (DE-588)4378490-2 s Paralleler Algorithmus (DE-588)4193615-2 s DE-604 Objektrelationales Datenbanksystem (DE-588)4534774-8 s Paralleles Datenbanksystem (DE-588)4624365-3 s Parallelverarbeitung (DE-588)4075860-6 s DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009138972&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Nippl, Clara 1969- Providing efficient, extensible and adaptive intra-query parallelism for advanced applications Parallelverarbeitung (DE-588)4075860-6 gnd Abfrageverarbeitung (DE-588)4378490-2 gnd Datenbanksystem (DE-588)4113276-2 gnd Objektrelationales Datenbanksystem (DE-588)4534774-8 gnd Paralleles Datenbanksystem (DE-588)4624365-3 gnd Paralleler Algorithmus (DE-588)4193615-2 gnd |
subject_GND | (DE-588)4075860-6 (DE-588)4378490-2 (DE-588)4113276-2 (DE-588)4534774-8 (DE-588)4624365-3 (DE-588)4193615-2 (DE-588)4113937-9 |
title | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications |
title_auth | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications |
title_exact_search | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications |
title_full | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications Clara Nippl |
title_fullStr | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications Clara Nippl |
title_full_unstemmed | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications Clara Nippl |
title_short | Providing efficient, extensible and adaptive intra-query parallelism for advanced applications |
title_sort | providing efficient extensible and adaptive intra query parallelism for advanced applications |
topic | Parallelverarbeitung (DE-588)4075860-6 gnd Abfrageverarbeitung (DE-588)4378490-2 gnd Datenbanksystem (DE-588)4113276-2 gnd Objektrelationales Datenbanksystem (DE-588)4534774-8 gnd Paralleles Datenbanksystem (DE-588)4624365-3 gnd Paralleler Algorithmus (DE-588)4193615-2 gnd |
topic_facet | Parallelverarbeitung Abfrageverarbeitung Datenbanksystem Objektrelationales Datenbanksystem Paralleles Datenbanksystem Paralleler Algorithmus Hochschulschrift |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009138972&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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