In-memory data management: technology and applications
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin [u.a.]
Springer
2012
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XXXIV, 267 S. Ill., graph. Darst. 235 mm x 155 mm |
| ISBN: | 9783642295744 3642295746 |
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Datensatz im Suchindex
| _version_ | 1805146728625602560 |
|---|---|
| adam_text |
IMAGE 1
CONTENTS
PART I AN INFLECTION POINT FOR ENTERPRISE APPLICATIONS
1 DESIRABILITY, FEASIBILITY, VIABILITY: THE IMPACT O F IN-MEMORY . . . .
3
1.1 INFORMATION IN REAL TIME: ANYTHING, ANYTIME, ANYWHERE . . . . 3
1.1.1 RESPONSE TIME AT THE SPEED OF THOUGHT 4
1.1.2 REAL-TIME ANALYTICS AND COMPUTATION ON THE FLY . . . . 6
1.2 THE IMPACT OF RECENT HARDWARE TRENDS 6
1.2.1 DATABASE MANAGEMENT SYSTEMS FOR ENTERPRISE APPLICATIONS 7
1.2.2 MAIN MEMORY IS THE NEW DISK 10
1.2.3 FROM MAXIMIZING CPU SPEED TO MULTI-CORE PROCESSORS 11
1.2.4 INCREASED BANDWIDTH BETWEEN CPU AND MAIN MEMORY 13
1.3 REDUCING COST THROUGH IN-MEMORY DATA MANAGEMENT 16
1.3.1 TOTAL COST OF OWNERSHIP 16
1.3.2 COST FACTORS IN ENTERPRISE SYSTEMS 17
1.3.3 IN-MEMORY PERFORMANCE BOOSTS COST REDUCTION 18
1.4 CONCLUSION 19
2 WHY ARE ENTERPRISE APPLICATIONS SO DIVERSE? 21
2.1 CURRENT ENTERPRISE APPLICATIONS 22
2.2 EXAMPLES O F ENTERPRISE APPLICATIONS 23
2.3 ENTERPRISE APPLICATION ARCHITECTURE 25
2.4 DATA PROCESSING IN ENTERPRISE APPLICATIONS 26
2.5 DATA ACCESS PATTERNS IN ENTERPRISE APPLICATIONS 27
2.6 CONCLUSION 27
X X M
HTTP://D-NB.INFO/102076144X
IMAGE 2
X X I V
C O N T E N T S
3 SANSSOUCIDB: BLUEPRINT FOR AN IN-MEMORY ENTERPRISE
DATABASE SYSTEM 29
3.1 TARGETING MULTI-CORE AND MAIN MEMORY 30
3.2 DESIGNING AN IN-MEMORY DATABASE SYSTEM 31
3.3 ORGANIZING AND ACCESSING DATA IN SANSSOUCIDB 33
3.4 CONCLUSION 35
PART II SANSSOUCIDB: A SINGLE SOURCE OF TRUTH THROUGH IN-MEMORY
4 THE TECHNICAL FOUNDATIONS O F SANSSOUCIDB 39
4.1 UNDERSTANDING MEMORY HIERARCHIES 4 0
4.1.1 INTRODUCTION TO MAIN MEMORY 4 0
4.1.2 ORGANIZATION OF THE MEMORY HIERARCHY 44
4.1.3 TRENDS IN MEMORY HIERARCHIES 45
4.1.4 MEMORY FROM A PROGRAMMER'S POINT OF VIEW 4 6
4.2 PARALLEL DATA PROCESSING USING MULTI-CORE AND ACROSS SERVERS 53
4.2.1 INCREASING CAPACITY BY ADDING RESOURCES 54
4.2.2 PARALLEL SYSTEM ARCHITECTURES 56
4.2.3 PARALLELIZATION IN DATABASES FOR ENTERPRISE APPLICATIONS 58
4.2.4 PARALLEL DATA PROCESSING IN SANSSOUCIDB 60
4.3 COMPRESSION FOR SPEED AND MEMORY CONSUMPTION 64
4.3.1 LIGHT-WEIGHT COMPRESSION 65
4.3.2 HEAVY-WEIGHT COMPRESSION 69
4.3.3 DATA-DEPENDENT OPTIMIZATION 70
4.3.4 COMPRESSION-AWARE QUERY EXECUTION 70
4.3.5 COMPRESSION ANALYSIS ON REAL DATA 71
4.4 COLUMN, ROW, HYBRID: OPTIMIZING THE DATA LAYOUT 72
4.4.1 VERTICAL PARTITIONING 72
4.4.2 FINDING THE BEST LAYOUT 76
4.4.3 CHALLENGES FOR HYBRID DATABASES 78
4.4.4 APPLICATION SCENARIOS 79
4.5 THE IMPACT OF VIRTUALIZATION 79
4.5.1 VIRTUALIZING ANALYTICAL WORKLOADS 80
4.5.2 DATA MODEL AND BENCHMARKING ENVIRONMENT 80
4.5.3 VIRTUAL VERSUS NATIVE EXECUTION 81
4.5.4 RESPONSE TIME DEGRADATION WITH CONCURRENT VMS . . . 82
4.6 SUMMARIZING THE TECHNICAL CONCEPTS 84
4.7 CONCLUSION 95
IMAGE 3
CONTENTS XXV
5 ORGANIZING AND ACCESSING DATA IN SANSSOUCIDB 97
5.1 SQL FOR ACCESSING IN-MEMORY DATA 98
5.1.1 THE ROLE O F SQL 98
5.1.2 THE LIFECYCLE OF A QUERY 99
5.1.3 STORED PROCEDURES 99
5.1.4 DATA ORGANIZATION AND INDICES 100
5.1.5 ANY ATTRIBUTES AS INDEX 101
5.2 INCREASING PERFORMANCE WITH DATA AGING 103
5.2.1 ACTIVE AND PASSIVE DATA 104
5.2.2 IMPLEMENTATION CONSIDERATIONS FOR AN AGING PROCESS 105
5.2.3 THE USE CASE FOR HORIZONTAL PARTITIONING OF LEADS . . . 106
5.3 EFFICIENT RETRIEVAL O F BUSINESS OBJECTS 108
5.3.1 RETRIEVING BUSINESS DATA FROM A DATABASE 109
5.3.2 OBJECT DATA GUIDE 109
5.4 EFFICIENT EXECUTION O F BUSINESS FUNCTIONS I L L
5.4.1 SEPARATING BUSINESS FUNCTIONS FROM APPLICATION FUNCTIONS I L L
5.4.2 COMPARING BUSINESS FUNCTIONS 112
5.5 HANDLING DATA CHANGES IN READ-OPTIMIZED DATABASES 114
5.5.1 THE IMPACT ON SANSSOUCIDB 115
5.5.2 THE MERGE PROCESS 116
5.5.3 IMPROVING PERFORMANCE WITH SINGLE COLUMN MERGE. . . 120 5.6
APPEND, NEVER DELETE, TO KEEP THE HISTORY COMPLETE 123
5.6.1 INSERT-ONLY IMPLEMENTATION STRATEGIES 123
5.6.2 MINIMIZING LOCKING THROUGH INSERT-ONLY 125
5.6.3 THE IMPACT ON ENTERPRISE APPLICATIONS 128
5.6.4 FEASIBILITY OF THE INSERT-ONLY APPROACH 130
5.7 ENABLING ANALYTICS ON TRANSACTIONAL DATA 132
5.7.1 AGGREGATION ON THE FLY 133
5.7.2 ANALYTICAL QUERIES WITHOUT A STAR SCHEMA 142
5.8 EXTENDING DATA LAYOUT WITHOUT DOWNTIME 149
5.8.1 REORGANIZATION IN A ROW STORE 149
5.8.2 ON-THE-FLY ADDITION IN A COLUMN STORE 150
5.9 BUSINESS RESILIENCE THROUGH ADVANCED LOGGING TECHNIQUES 151
5.9.1 RECOVERY IN COLUMN STORES 152
5.9.2 DIFFERENTIAL LOGGING FOR ROW-ORIENTED DATABASES . . . . 154 5.9.3
PROVIDING HIGH AVAILABILITY 155
5.10 THE IMPORTANCE OF OPTIMAL SCHEDULING FOR MIXED WORKLOADS 156
5.10.1 INTRODUCTION TO SCHEDULING 156
5.10.2 CHARACTERISTICS OF A MIXED WORKLOAD 159
IMAGE 4
XXVI C O N T E N T S
5.10.3 SCHEDULING SHORT AND LONG RUNNING TASKS 160
5.11 CONCLUSION 163
PART III HOW IN-MEMORY CHANGES THE GAME
6 APPLICATION DEVELOPMENT 167
6.1 OPTIMIZING APPLICATION DEVELOPMENT FOR SANSSOUCIDB 167
6.1.1 AN IN-MEMORY APPLICATION PROGRAMMING MODEL 168
6.1.2 APPLICATION ARCHITECTURE 172
6.1.3 MOVING BUSINESS LOGIC INTO THE DATABASE 173
6.1.4 BEST PRACTICES 175
6.1.5 GRAPHICAL CREATION O F VIEWS 176
6.2 INNOVATIVE ENTERPRISE APPLICATIONS 178
6.2.1 NEW ANALYTICAL APPLICATIONS 179
6.2.2 OPERATIONAL PROCESSING TO SIMPLIFY DAILY BUSINESS . . . 182 6.2.3
INFORMATION AT YOUR FINGERTIPS WITH INNOVATIVE USER-INTERFACES 185
6.2.4 COMBINING ANALYTICS AND TEXTSEARCH 190
6.2.5 BASIC TYPES O F SEARCH 191
6.2.6 FEATURES FOR ENTERPRISE SEARCH 191
6.3 CONCLUSION 194
7 FINALLY, A REAL BUSINESS INTELLIGENCE SYSTEM IS AT HAND 195
7.1 ANALYTICS ON OPERATIONAL DATA 195
7.1.1 YESTERDAY'S BUSINESS INTELLIGENCE 196
7.1.2 TODAY'S BUSINESS INTELLIGENCE 199
7.1.3 DRAWBACKS O F SEPARATING ANALYTICS FROM DAILY OPERATIONS 201
7.1.4 DEDICATED DATABASE DESIGNS FOR ANALYTICAL SYSTEMS. . . 202 7.1.5
ANALYTICS AND QUERY LANGUAGES 205
7.1.6 ENABLERS FOR CHANGING BUSINESS INTELLIGENCE 206
7.1.7 TOMORROW'S BUSINESS INTELLIGENCE 208
7.2 HOW TO EVALUATE DATABASES AFTER THE GAME HAS CHANGED 209
7.2.1 BENCHMARKS IN ENTERPRISE COMPUTING 210
7.2.2 CHANGED BENCHMARK REQUIREMENTS FOR A MIXED WORKLOAD 211
7.2.3 A NEW BENCHMARK FOR DAILY OPERATIONS AND ANALYTICS 213
7.3 CONCLUSION 216
8 SCALING SANSSOUCIDB IN THE CLOUD 219
8.1 WHAT IS CLOUD COMPUTING? 220
8.2 TYPES OF CLOUD APPLICATIONS 221
IMAGE 5
CONTENTS XXVII
8.3 CLOUD COMPUTING FROM THE PROVIDER PERSPECTIVE 223
8.3.1 MULTI-TENANCY 223
8.3.2 LOW-END VERSUS HIGH-END HARDWARE 228
8.3.3 REPLICATION 229
8.3.4 ENERGY EFFICIENCY BY EMPLOYING IN-MEMORY TECHNOLOGY 230
8.4 CONCLUSION 231
9 IN-MEMORY REVOLUTION HAS BEGUN 233
9.1 RISK-FREE TRANSITION TO IN-MEMORY DATA MANAGEMENT 233
9.1.1 OPERATING IN-MEMORY AND TRADITIONAL SYSTEMS SIDE BY SIDE 234
9.1.2 SYSTEM CONSOLIDATION AND EXTENSIBILITY 235
9.2 CUSTOMER PROOF POINTS 236
9.2.1 CHARITE-UNIVERSITATSMEDIZIN BERLIN 237
9.2.2 HILTI 239
9.3 CONCLUSION 241
ABOUT THE AUTHORS 243
GLOSSARY 245
REFERENCES 255
INDEX 263 |
| any_adam_object | 1 |
| author | Plattner, Hasso 1944- Zeier, Alexander 1969- |
| author_GND | (DE-588)121975193 (DE-588)124322719 |
| author_facet | Plattner, Hasso 1944- Zeier, Alexander 1969- |
| author_role | aut aut |
| author_sort | Plattner, Hasso 1944- |
| author_variant | h p hp a z az |
| building | Verbundindex |
| bvnumber | BV040233300 |
| classification_rvk | QP 345 ST 270 ST 530 |
| ctrlnum | (OCoLC)798259010 (DE-599)DNB102076144X |
| dewey-full | 658.40380285574 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 658 - General management |
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| dewey-search | 658.40380285574 |
| dewey-sort | 3658.40380285574 |
| dewey-tens | 650 - Management and auxiliary services |
| discipline | Informatik Wirtschaftswissenschaften |
| edition | 2. ed. |
| format | Book |
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| indexdate | 2024-07-21T00:34:30Z |
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| spelling | Plattner, Hasso 1944- Verfasser (DE-588)121975193 aut In-memory data management technology and applications Hasso Plattner ; Alexander Zeier 2. ed. Berlin [u.a.] Springer 2012 XXXIV, 267 S. Ill., graph. Darst. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier In-Memory-Datenbank (DE-588)7744803-0 gnd rswk-swf Betriebliches Informationssystem (DE-588)4069386-7 gnd rswk-swf Datenmanagement (DE-588)4213132-7 gnd rswk-swf Betriebliches Informationssystem (DE-588)4069386-7 s Datenmanagement (DE-588)4213132-7 s In-Memory-Datenbank (DE-588)7744803-0 s DE-604 Zeier, Alexander 1969- Verfasser (DE-588)124322719 aut X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=3994291&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=025089672&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Plattner, Hasso 1944- Zeier, Alexander 1969- In-memory data management technology and applications In-Memory-Datenbank (DE-588)7744803-0 gnd Betriebliches Informationssystem (DE-588)4069386-7 gnd Datenmanagement (DE-588)4213132-7 gnd |
| subject_GND | (DE-588)7744803-0 (DE-588)4069386-7 (DE-588)4213132-7 |
| title | In-memory data management technology and applications |
| title_auth | In-memory data management technology and applications |
| title_exact_search | In-memory data management technology and applications |
| title_full | In-memory data management technology and applications Hasso Plattner ; Alexander Zeier |
| title_fullStr | In-memory data management technology and applications Hasso Plattner ; Alexander Zeier |
| title_full_unstemmed | In-memory data management technology and applications Hasso Plattner ; Alexander Zeier |
| title_short | In-memory data management |
| title_sort | in memory data management technology and applications |
| title_sub | technology and applications |
| topic | In-Memory-Datenbank (DE-588)7744803-0 gnd Betriebliches Informationssystem (DE-588)4069386-7 gnd Datenmanagement (DE-588)4213132-7 gnd |
| topic_facet | In-Memory-Datenbank Betriebliches Informationssystem Datenmanagement |
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