Big data science & analytics: a hands-on approach
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
[Erscheinungsort nicht ermittelbar]
[Verlag nicht ermittelbar]
[2016]
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| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | 542 Seiten Illustrationen, Diagramme 27 cm |
| ISBN: | 9780996025539 0996025545 |
Staff View
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| 245 | 1 | 0 | |a Big data science & analytics |b a hands-on approach |c Arshdeep Bahga, Vijay Madisetti |
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| 300 | |a 542 Seiten |b Illustrationen, Diagramme |c 27 cm | ||
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| 505 | 8 | |a Includes bibliographical references (page [535]-538) and index | |
| 505 | 8 | |a Big data analytics concepts -- Big data analytics implementations -- Advanced topics | |
| 650 | 4 | |a Cooperating objects (Computer systems) | |
| 650 | 4 | |a Internet of things | |
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Record in the Search Index
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| adam_text | CONTENTS
I BIG DATA ANALYTICS CONCEPTS
19
1 INTRODUCTION TO BIG DATA 21
1.1 WHAT IS ANALYTICS? 22
1.1.1 DESCRIPTIVE ANALYTICS 22
1.1.2 DIAGNOSTIC ANALYTICS 24
1.1.3 PREDICTIVE ANALYTICS 24
1.1.4 PRESCRIPTIVE ANALYTICS 24
1.2 WHAT IS BIG DATA? 25
1.3 CHARACTERISTICS OF BIG DATA 26
1.3.1 VOLUME 26
1.3.2 VELOCITY 26
1.3.3 VARIETY . . 26
1.3.4 VERACITY 27
1.3.5 VALUE 27
1.4 DOMAIN SPECIFIC EXAMPLES OF BIG DATA 27
1.4.1 WEB 27
1.4.2 FINANCIAL 29
1.4.3 HEALTHCARE 29
1.4.4 INTERNET OF THINGS 30
1.4.5 ENVIRONMENT . 31
1.4.6 LOGISTICS & TRANSPORTATION .32
1.4.7 INDUSTRY 34
1.4.8 RETAIL 35
1.5 ANALYTICS FLOW FOR BIG DATA 35
1.5.1 DATA COLLECTION 36
1.5.2 DATA PREPARATION . 36
1.5.3 ANALYSIS TYPES 36
1.5.4 ANALYSIS MODES 36
1.5.5 VISUALIZATIONS 38
1.6 BIG DATA STACK 38
1.6.1 RAW DATA SOURCES 39
1.6.2 DATA ACCESS CONNECTORS 39
1.6.3 DATA STORAGE 41
1.6.4 BATCH ANALYTICS 41
1.6.5 REAL-TIME ANALYTICS 42
1.6.6 INTERACTIVE QUERYING 42
1.6.7 SERVING DATABASES, WEB & VISUALIZATION FRAMEWORKS 42
1.7 MAPPING ANALYTICS FLOW TO BIG DATA STACK
43
1.8 CASE STUDY: GENOME DATA ANALYSIS
46
52
1.9 CASE STUDY: WEATHER DATA ANALYSIS
55
1.10 ANALYTICS PATTERNS
G
2 SETTING UP BIG DATA STACK
2.1 HORTONWORKS DATA PLATFORM (HDP)
64
2.2 CLOUDERA CDH STACK
76
2.3 AMAZON ELASTIC MAPREDUCE (EMR) 83
2.4 AZURE HDINSIGHT
87
3 BIG DATA PATTERNS 89
3.1 ANALYTICS ARCHITECTURE COMPONENTS & DESIGN STYLES 90
3.1.1 LOAD LEVELING WITH QUEUES 90
3.1.2 LOAD BALANCING WITH MULTIPLE CONSUMERS 90
3.1.3 LEADER ELECTION 91
3.1.4 SHARDING 92
3.1.5 CONSISTENCY, AVAILABILITY & PARTITION TOLERANCE (CAP) 93
3.1.6 BLOOM FILTER 93
3.1.7 MATERIALIZED VIEWS 94
3.1.8 LAMBDA ARCHITECTURE 95
3.1.9 SCHEDULER-AGENT-SUPERVISOR 96
3.1.10 PIPES & FILTERS ... 97
3.1.11 WEB SERVICE 98
3.1.12 CONSENSUS IN DISTRIBUTED SYSTEMS 99
3.2 MAPRECLUCE PATTERNS 101
3.2.1 NUMERICAL SUMMARIZATION 102
3.2.2 TOP-N 110
3.2.3 FILTER 113
3.2.4 DISTINCT 115
3.2.5 BINNING 117
3.2.6 INVERTED INDEX 119
3.2.7 SORTING 121
3.2.8 JOINS 123
4 NOSQL 129
4.1 KEY-VALUE DATABASES 130
4.1.1 AMAZON DYNARNODB 131
4.2 DOCUMENT DATABASES 135
4.2.1 MONGODB 135
4.3 COLUMN FAMILY DATABASES 139
4.3.1 HBASE 139
4.4 GRAPH DATABASES 147
4.4.1 NEO4J 147
II BIG DATA ANALYTICS IMPLEMENTATIONS 155
5 DATA ACQUISITION .157
5.1 DATA ACQUISITION CONSIDERATIONS 158
5.1.1 SOURCE TYPE 158
5.1.2 VELOCITY 158
5.1.3 INGESTION MECHANISM 158
5.2 PUBLISH - SUBSCRIBE MESSAGING FRAMEWORKS 159
5.2.1 APACHE KAFKA 160
5.2.2 AMAZON KINESIS 165
5.3 BIG DATA COLLECTION SYSTEMS 167
5.3.1 APACHE FLUME 167
5.3.2 APACHE SQOOP 180
5.3.3 IMPORTING DATA WITH SQOOP 181
5.3.4 SELECTING DATA TO IMPORT 182
5.3.5 CUSTOM CONNECTORS 182
5.3.6 IMPORTING DATA TO HIVE 182
5.3.7 IMPORTING DATA TO HBASE .183
5.3.8 INCREMENTAL IMPORTS -|83
5.3.9 IMPORTING ALL TABLES 183
5.3.10 EXPORTING DATA WITH SQOOP 183
5.4 MESSAGING QUEUES 184
5.4.1 RABBITMQ 184
5.4.2 ZEROMQ 186
5.4.3 RESTMQ 187
5.4.4 AMAZON SQS 189
5.5 CUSTOM CONNECTORS 191
5.5.1 REST-BASED CONNECTORS 191
5.5.2 WEBSOCKET-BASED CONNECTORS 194
5.5.3 MQTT-BASED CONNECTORS 195
5.5.4 AMAZON LOT 197
5.5.5 AZURE LOT HUB 205
6 BIG DATA STORAGE 213
6.1 HDFS 214
6.1.1 HDFS ARCHITECTURE 214
6.1.2 HDFS USAGE EXAMPLES 218
7 BATCH ANALYSIS 221
7.1 HADOOP AND MAPREDUCE 222
7.1.1 MAPREDUCE PROGRAMMING MODEL 222
7.1.2 HADOOP YARN 222
7.1.3 HADOOP SCHEDULERS 226
7.2 HADOOP - MAPREDUCE EXAMPLES 228
7.2.1 BATCH ANALYSIS OF SENSOR DATA 228
7.2.2 BATCH ANALYSIS OF N-GRAM DATASET 231
7.2.3 FIND TOP-N WORDS WITH MAPREDUCE 232
7.3 PIG 233
7.3.1 LOADING DATA 234
7.3.2 DATA TYPES IN PIG 234
7.3.3 DATA FILTERING & ANALYSIS 235
7.3.4 STORING RESULTS 236
7.3.5 DEBUGGING OPERATORS 236
7.3.6 PIG EXAMPLES 238
7.4 CASE STUDY: BATCH ANALYSIS OF NEWS ARTICLES 238
7.5 APACHE OOZIE 244
7.5.1 OOZIE WORKFLOWS FOR DATA ANALYSIS 244
7.6 APACHE SPARK 252
7.6.1 SPARK OPERATIONS 253
7.7 SEARCH 257
7.7.1 APACHE SOLR 257
8 REAL-TIME ANALYSIS 269
8.1 STREAM PROCESSING 270
8.1.1 APACHE STORM 270
3.2 STORM CASE STUDIES 274
8.2.1 REAL-TIME TWITTER SENTIMENT ANALYSIS 274
8.2.2 REAL-TIME WEATHER DATA ANALYSIS 286
8.3 IN-MEMORY PROCESSING 293
8.3.1 APACHE SPARK 293
8.4 SPARK CASE STUDIES 297
8.4.1 REAL-TIME SENSOR DATA ANALYSIS 298
8.4.2 REAL-TIME PARKING SENSOR DATA ANALYSIS FOR SMART PARKING SYSTEM
299
8.4.3 REAL-TIME TWITTER SENTIMENT ANALYSIS 305
8.4.4 WINDOWED ANALYSIS OF TWEETS 311
9 INTERACTIVE QUERYING 313
9.1 SPARK SQL 314
9.1.1 CASE STUDY: INTERACTIVE QUERYING OF WEATHER DATA 319
9.2 HIVE 322
9.3 AMAZON REDS H IFT 326
9.4 GOOGLE BIG QUERY 335
10 SERVING DATABASES & WEB FRAMEWORKS 345
10.1 RELATIONAL (SQL) DATABASES 346
10.1.1 MYSQL 347
10.2 NON-RELATIONAL (NOSQL) DATABASES 350
10.2.1 AMAZON DYNAMODB 351
10.2.2 CASSANDRA 357
10.2.3 MONGODB 360
10.3 PYTHON WEB APPLICATION FRAMEWORK - DJANGO 362
10.3.1 DJANGO ARCHITECTURE 362
10.3.2 STARTING DEVELOPMENT WITH DJANGO 363
10.4 CASE STUDY: DJANGO APPLICATION FOR VIEWING WEATHER DATA 379
III ADVANCED TOPICS
387
11 ANALYTICS ALGORITHMS 389
11.1 FRAMEWORKS 390
11.1.1 SPARK MLLIB 390
11.1.2 H20 391
11.2 CLUSTERING 393
11.2.1 K-MEANS 393
11.3 CASE STUDY: SONG RECOMMENDATION SYSTEM 400
11.4 CLASSIFICATION & REGRESSION 406
11.4.1 PERFORMANCE EVALUATION METRICS 407
11.4.2 NAIVE BAYES 408
11.4.3 GENERALIZED LINEAR MODEL 420
11.4.4 DECISION TREES 435
11.4.5 RANDOM FOREST 438
11.4.6 GRADIENT BOOSTING MACHINE 447
11.4.7 SUPPORT VECTOR MACHINE 458
11.4.8 DEEP LEARNING 460
11.5 CASE STUDY: CLASSIFYING HANDWRITTEN DIGITS 471
11.5.1 DIGIT CLASSIFICATION WITH H2O 471
11.5.2 DIGIT CLASSIFICATION WITH SPARK 473
11.6 CASE STUDY: GENOME DATA ANALYSIS (IMPLEMENTATION) 475
11.7 RECOMMENDATION SYSTEMS 479
11.7.1 ALTERNATING LEAST SQUARES (ALS) 480
11.7.2 SINGULAR VALUE DECOMPOSITION (SVD) 484
11.7.3 CASE STUDY: MOVIE RECOMMENDATION SYSTEM 484
12 DATA VISUALIZATION 497
12.1 FRAMEWORKS & LIBRARIES 498
12.1.1 LIGHTNING 498
12.1.2 PYGAL 498
12.1.3 SEABORN 498
12.2 VISUALIZATION EXAMPLES 499
12.2.1 LINE CHART 499
12.2.2 SCATTER PLOT 501
12.2.3 BAR CHART 504
12.2.4 BOX PLOT 506
12.2.5 PIE CHART 508
12.2.6 DOT CHART 509
12.2.7 MAP CHART 510
12.2.8 GAUGE CHART 512
12.2.9 RADAR CHART 513
12.2.10 MATRIX CHART 514
12.2.11 FORCE-DIRECTED GRAPH 516
12.2.12 SPATIAL GRAPH 518
12.2.13 DISTRIBUTION PLOT 519
12.2.14 KERNEL DENSITY ESTIMATE (KDE) PLOT 520
12.2.15 REGRESSION PLOT 521
12.2.16 RESIDUAL PLOT 522
12.2.17 INTERACTION PLOT 523
12.2.18 VIOLIN PLOT 524
12.2.19 STRIP PLOT 525
12.2.20 POINT PLOT 526
12.2.21 COUNT PLOT 527
12.2.22 HEATMAP 528
12.2.23 CLUSTERED HEATMAP 529
12.2.24 JOINT PLOT 530
12.2.25 PAIR GRID 532
12.2.26 FACET GRID 533
BIBLIOGRAPHY 538
INDEX 539
|
| any_adam_object | 1 |
| author | Bahga, Arshdeep Madisetti, Vijay K. |
| author_GND | (DE-588)107489197X (DE-588)1089391153 |
| author_facet | Bahga, Arshdeep Madisetti, Vijay K. |
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| contents | Includes bibliographical references (page [535]-538) and index Big data analytics concepts -- Big data analytics implementations -- Advanced topics |
| ctrlnum | (OCoLC)968687534 (DE-599)BVBBV043848343 |
| discipline | Informatik Wirtschaftswissenschaften |
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| indexdate | 2024-07-10T07:36:39Z |
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| isbn | 9780996025539 0996025545 |
| language | English |
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| physical | 542 Seiten Illustrationen, Diagramme 27 cm |
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| spelling | Bahga, Arshdeep (DE-588)107489197X aut Big data science & analytics a hands-on approach Arshdeep Bahga, Vijay Madisetti [Erscheinungsort nicht ermittelbar] [Verlag nicht ermittelbar] [2016] © 2016 542 Seiten Illustrationen, Diagramme 27 cm txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references (page [535]-538) and index Big data analytics concepts -- Big data analytics implementations -- Advanced topics Cooperating objects (Computer systems) Internet of things Cooperating objects (Computer systems) fast Internet of things fast Datenauswertung (DE-588)4131193-0 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Big Data (DE-588)4802620-7 s Datenauswertung (DE-588)4131193-0 s DE-604 Madisetti, Vijay K. (DE-588)1089391153 aut SWB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029258724&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bahga, Arshdeep Madisetti, Vijay K. Big data science & analytics a hands-on approach Includes bibliographical references (page [535]-538) and index Big data analytics concepts -- Big data analytics implementations -- Advanced topics Cooperating objects (Computer systems) Internet of things Cooperating objects (Computer systems) fast Internet of things fast Datenauswertung (DE-588)4131193-0 gnd Big Data (DE-588)4802620-7 gnd |
| subject_GND | (DE-588)4131193-0 (DE-588)4802620-7 |
| title | Big data science & analytics a hands-on approach |
| title_auth | Big data science & analytics a hands-on approach |
| title_exact_search | Big data science & analytics a hands-on approach |
| title_full | Big data science & analytics a hands-on approach Arshdeep Bahga, Vijay Madisetti |
| title_fullStr | Big data science & analytics a hands-on approach Arshdeep Bahga, Vijay Madisetti |
| title_full_unstemmed | Big data science & analytics a hands-on approach Arshdeep Bahga, Vijay Madisetti |
| title_short | Big data science & analytics |
| title_sort | big data science analytics a hands on approach |
| title_sub | a hands-on approach |
| topic | Cooperating objects (Computer systems) Internet of things Cooperating objects (Computer systems) fast Internet of things fast Datenauswertung (DE-588)4131193-0 gnd Big Data (DE-588)4802620-7 gnd |
| topic_facet | Cooperating objects (Computer systems) Internet of things Datenauswertung Big Data |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029258724&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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