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SAP HANA Advanced Data Modeling (SAP Press)

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en Limba Engleză Carte Hardback – 2016
If you're looking to move past the SAP HANA basics and get knee-deep into some real data model design, you've come to the right place. With step-by-step instructions and sample coding, this book will teach you how to build and design predictive, simulation, and optimization models. From information views to AFL models, you'll learn to scale for large datasets and performance tune your models to perfection. Highlights Include: Analytic, attribute, and calculation views; Application Function Library models; PA; SQL; R procedures; Basic and advanced predictive modelling; Simulations and Optimization Performance tuning; Complex business logic; SAP HANA Database Engine; SAP HANA modeling paradigms.
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Specificații

ISBN-13: 9781493212361
ISBN-10: 1493212362
Pagini: 392
Dimensiuni: 182 x 236 x 30 mm
Greutate: 0.88 kg
Editura: Rheinwerk Verlag GmbH
Seria SAP Press


Cuprins



1 ... SAP HANA Data Models ... 21



1.1 ... SAP HANA Database Architecture Overview ... 21

1.2 ... SAP HANA Modeling Paradigms ... 22

1.3 ... Information Views ... 26

1.4 ... Analytic Privileges ... 67

1.5 ... Stored Procedures ... 75

1.6 ... Application Function Library ... 86

1.7 ... Summary ... 90



2 ... Modeling Complex Logic ... 93



2.1 ... Achieving Recursive Logic with Hierarchies ... 93

2.2 ... Transposing Columns and Rows ... 110

2.3 ... Using cube() with Hierarchies ... 123

2.4 ... Calculating Running Total ... 127

2.5 ... Calculating Cumulative Sum ... 131

2.6 ... Filtering Data Based on Ranking ... 134

2.7 ... Controlling Join Paths via Filters ... 138

2.8 ... Full Outer Join in a Calculation View ... 143

2.9 ... Making Dynamic Queries in a Stored Procedure ... 148

2.10 ... Showing History Records Side By Side ... 153

2.11 ... Sample Data ... 158

2.12 ... Using a Vertical Union to Join Tables ... 161

2.13 ... Sorting Records ... 163

2.14 ... Finding Missing Values ... 168

2.15 ... Using Window Functions for Complex Grouping ... 172

2.16 ... Joining Based on a Date Sequence ... 178

2.17 ... Using a Nested Calculation View ... 185

2.18 ... Summary ... 191



3 ... Scaling for Large Datasets ... 193



3.1 ... Partitioning ... 193

3.2 ... Using Input Parameters to Enforce Pruning ... 198

3.3 ... Creating an Index ... 201

3.4 ... Analyzing Query Performance with Tools ... 205

3.5 ... Enforcing Execution Paths ... 214

3.6 ... Using a Union with Constant Values Instead of a Join ... 218

3.7 ... Manipulating Joins in an Analytic View ... 224

3.8 ... Time Traveling ... 236

3.9 ... Storing Temporary Data ... 243

3.10 ... Calculating Count Distinct ... 247

3.11 ... Using Cached Views ... 250

3.12 ... Summary ... 258



4 ... Basic Predictive Modeling ... 259



4.1 ... Predictive Analytics Lifecycle in SAP HANA ... 259

4.2 ... Data Exploration ... 270

4.3 ... Data Preparation ... 291

4.4 ... Modeling ... 297

4.5 ... Creating Models Using SAP Applications on SAP HANA ... 308

4.6 ... Summary ... 318



5 ... Advanced Predictive Modeling ... 319


5.1 ... R Script Modeling and Design ... 319

5.2 ... PAL Model Consumption ... 326

5.3 ... Real-Time Model Consumption vs. Batch Predictive Modeling ... 329

5.4 ... Impact of Data Partitions in Predictive Modeling ... 332

5.5 ... Using Multiple R Servers and Data Partitions ... 333

5.6 ... Modeling Using R and PAL Simultaneously ... 337

5.7 ... Summary ... 340



6 ... Simulations and Optimizations ... 341



6.1 ... Case Study ... 341

6.2 ... Monte Carlo Simulation of Value-at-Risk ... 342

6.3 ... Portfolio Optimization ... 363

6.4 ... Summary ... 380



The Authors ... 381