HANA SPS07 App Function Library

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What´s New? SAP HANA SPS 07 - SAP HANA Application Function Library (AFL)

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  • Selecting (drag‘n‘drop) a AFL Procedurefromthecomponentspanel(here e.g. kmeans)+ Selecting (drag‘n‘drop) + connecting an inputtabletothedatasourcePlaceholderforappropriatetabletypesData sourcetable type areautomaticallyfilledandmapped
  • HANA SPS07 App Function Library

    1. 1. What´s New? SAP HANA SPS 07 SAP HANA Application Function Library (AFL) (Delta from SPS 06 to SPS 07) SAP HANA Product Management November, 2013
    2. 2. Contents  Overview  What’s New for SPS 07: Predictive Analysis Library  What’s New for SPS 07: Application Function Modeler © 2013 SAP AG. All rights reserved. Public 2
    3. 3. Overview
    4. 4. Application Function Library: General Overview – 1Application Function Library (AFL) – what is it? Pre-delivered commonly utilized business, predictive and other types of algorithms for use in projects or solutions that run on SAP HANA. The technology framework enabling the use of these algorithms is called the Application Function Library . What are it’s benefits? These algorithms can be leveraged directly in development projects, speeding up projects by avoiding writing custom complex algorithms from scratch. AFL operations also offer very fast performance, as AFL functions run in the core of SAP HANA in-memory DB. What are its primary libraries? The Predictive Analysis Library (PAL) is a set of functions in the AFL. It contains pre-built, parameterdriven, commonly used algorithms primarily related to predictive analysis and data mining. The Business Function Library (BFL) is a set of functions in the AFL. It contains pre-built, parameterdriven, commonly used algorithms primarily related to finance. © 2013 SAP AG. All rights reserved. Public 4
    5. 5. The Application Function Library Framework in SAP HANA AFL Technology includes HANA Clients (App Server, Analytics Technology, etc) Application Functions Written in C++ and delivered as AFL content by SAP Predictive Analysis and Business Function Library have been released in SPS 05 as AFL content AFM SAP HANA SQLScript Parameter Table AFL Framework On demand library loading framework for registered and supported libraries AFL are consumed for use from SqlScript via so-called wrapperprocedures. Consumption can be controlled via permissions. Beyond the initial script-based approach, the Application Function Modeler is released with SPS 06 as a graphical editor to facilitate the design-time process of creating the wrapper-procedures and can easily be re-used as part of development workflow. © 2013 SAP AG. All rights reserved. AFL Framework Application Functions (C++) Business Function Library Predictive Analysis Library … Public 5
    6. 6. Predictive Analysis Library – General Overview Predictive Analysis Library (PAL) • Compiled analytic function library for predictive analysis in HANA SPS 05 • Support multiple algorithms: K-Means, Association Analysis, C4.5 Decision Tree, Multiple Linear Regression, Exponential Smoothing… Help Customers To Know Your Business Decide with Confidence Compute Quickly Empower the business © 2013 SAP AG. All rights reserved. Uncover deep insights & patterns about the business: association rules, customer clustering, or sales prediction Drive more advanced analyses. Decision is made with support from analysis numbers Query and analyze data in real-time with high-performance computation in-memory Bring decision support capabilities to the business users through simplified experience and pre-built scenarios Public 6
    7. 7. The Predictive Analysis Library in SAP HANA Functional Overview as of SPS 06 The Predictive Analysis Library (PAL) is a built-in C++ library to perform in-database data mining and statistical calculations, designed to provide excellent performance on large data sets. Embedded in SAP HANA via the Application Function Library Classification Analysis C4.5 Decision Tree Analysis CHAID Decision Tree Analysis K Nearest Neighbour Multiple Linear Regression Polynomial Regression Exponential Regression Bi-Variate Geometric Regression Bi-Variate Logarithmic Regression Logistic Regression Naïve Bayes Data Preparation Sampling Binning Scaling Convert Categorical to Binary Outlier Detection Inter-Quartile Range Test (Tukey’s Test) Variance Test Anomaly Detection Cluster Analysis Association Analysis Apriori Apriori Lite © 2013 SAP AG. All rights reserved. ABC Classification DBSCAN K-Means Kohonen Self Organized Maps Status: SAP HANA SPS 06. Time Series Analysis Single Exponential Smoothing Double Exponential Smoothing Triple Exponential Smoothing Link Prediction Different Measurements: Common Neighbors; Jaccard’s Coefficient; Adamic/Adar; Katzβ Other Weighted Scores Table Y X Public Z 7
    8. 8. Application Function Modeler Application Function Modeler A graphical editor to facilitate a faster and easier design-time process of creating the wrapper-procedures AFL Models are stored as repository objects and can easily be re-used as part of development workflow. Model Editor Drag‘n drop of functions Template for table types Data source selection and automatic mappings to table types Sample SQL for procedure consumption © 2013 SAP AG. All rights reserved. Library Selection Function List and Search Parameters and specifications for table types Public 8
    9. 9. What’s New: Predictive Analysis Library
    10. 10. New Algorithms: Statistical Functions Univariate  Mean, median, variance, standard deviation  Kurtosis  Skewness Multivariate  Covariance matrix  Pearson correlations coefficient matrix  Chi-squared tests: – test of quality of fit – test of independence  Variance equal test (F-test) © 2013 SAP AG. All rights reserved. Public 10
    11. 11. New Algorithms: Substitute Missing Values; Partitioning Substitute missing values  Continuous variable: replace the ‘null’ value with ‘mean’ or ‘median’  Categorical variable: replace the ‘null’ value with ‘mode’ Partitioning  Splits an input table into 3 parts (training table, testing table and validation table). Union could be a subset of the input table and the validation part could be empty  Two partition methods are supported: – Random Partition – Stratified Partition (stratified sampling) © 2013 SAP AG. All rights reserved. Public 11
    12. 12. New Algorithms: Support Vector Machine; Forecast Smoothing Support Vector Machine  A family of supervised machine learning algorithms that analyze data and recognize patterns, typically used for classification and regression analysis  Holds advantages over other supervised learning models: SVM models can be either linear or non-linear Forecast Smoothing  Calculates a set of optimal parameters for PAL functions: Single Smoothing, Double Smoothing and Triple Smoothing  Outputs the forecasting result by using the best parameter  Parameter optimization is based on global and local search algorithms © 2013 SAP AG. All rights reserved. Public 12
    13. 13. New Clustering Algorithms: Agglomerate Hierarchical; Affinity Propagation Agglomerate Hierarchical Clustering  Widely used clustering method which can find natural groups within a set of data  Groups the data into a hierarchy or a binary tree of the subgroups  The PAL version follows the agglomerate approach: merges the clusters with a bottom-up strategy. Affinity Propagation Clustering  A relatively new clustering algorithm based on the concept of "message passing" between data points  Holds the advantage that the number of clusters does not necessarily have to be predetermined © 2013 SAP AG. All rights reserved. Public 13
    14. 14. Enhancements to Regression Algorithms Linear regression  Support p-value for each coefficient  Stepwise linear regression (forward and backward only) Logistic regression  Logistic regression with L1 regularization  Categorical support for input variable  p-value for coefficient © 2013 SAP AG. All rights reserved. Public 14
    15. 15. Enhancements to Other Algorithms Apriori  Output rules in relational format  Add lift as a filter for rules  Provide an option which controls the number of items in right hand side (1 or many) Decision Tree  Missing value handling in decision tree (mean/mode) © 2013 SAP AG. All rights reserved. Public 15
    16. 16. What’s New: Application Function Modeler
    17. 17. Application Function Modeler SPS 07 Features Overview Objectives Drive AFM achieve a more stable and usable solution  Better integrate with AFL Framework.  UI Improvement: more friendly and usable  Better support the E2E Development Scenarios: create, activation, calling, delivery etc.  Others: Performance AFL Framework improvement, Error Handling UI Improvement      Better support the table type editing  Better naming rule and icon  Better UI Text Update table type constrains and default parameter Support new function in PAL (11 new functions) Use new AFL API to generate wrapper procedure Refactor the data model E2E Development Scenarios Other       Performance improvement: creation, model consistence check  Error Message: in studio side and server side  Support open file offline but read-only  … View support Better undo/redo Calling parameter remove/add/restore/persistence Schema mapping … © 2013 SAP AG. All rights reserved. Public 17
    18. 18. AFM: New Functions  11 new functions will be supported New Algorithm in AFM in SPS 07 Description DBSCAN DBSCAN LINKPREDICTION Link Prediction Convert category Type to CONV2BINARYVECTOR Binary Vector SLIGHTSILHOUETTE Slight Silhouette NBCTRAIN NBCTRAIN NBCPREDICT NBCPREDICT HCAGGLOMERATE Hierarchical Clustering Train with Support Vector SVMTRAIN Machines Predict with Support Vector SVMPREDICT Machines PARTITION Data Partition SUBSTITUTE_MISS Substitute Missing Values …. © 2013 SAP AG. All rights reserved. Category Clustering Social network analysis AFM SPS 07 SPS 07 PAL SPS 06 SPS 06 Preprocessing SPS 07 SPS 06 Clustering Classification Classification Clustering SPS 07 SPS 07 SPS 07 SPS 07 SPS 06 SPS 06 SPS 06 SPS 07 Classification SPS 07 SPS 07 Classification SPS 07 SPS 07 Preprocessing Preprocessing SPS 07 SPS 07 SPS 07 SPS 07 Public 18
    19. 19. AFM: Updated Generated Procedure Definition  New AFL Generator API in Runtime Plugin   SPS 06: CREATE PROCEDURE ... LANGUAGE LLANG AS BEGIN ... SPS 07: CREATE PROCEDURE ... LANGUAGE AFLLANG SQL SECURITY INVOKER READS SQL DATA AS BEGIN .. © 2013 SAP AG. All rights reserved. Public 19
    20. 20. AFM: Table Type Editor & Parameter Editing  Table Type Editor  Parameter Editing  Support user add/remove parameter  Provide restore defaults action © 2013 SAP AG. All rights reserved. Public 20
    21. 21. AFM: New Error Messages  Provide better error messages and provide the possible next step Case No required permission Table Type Configuration Error Calling with activation … No schema sleeted No Function Selected Table Type has not been initialized File corrupt … © 2013 SAP AG. All rights reserved. Error Message (Client Side) User does not have the AFL__SYS_AFL_AFLBFL_EXECUTE role. Assign the role first. Table column setting does not match function specification AFL Model (.aflpmml) file has not been activated. Activate the file before calling it. … (Server side Activation) Repository: Error in repository runtime extension. No schema selected. Select a schema. Repository: Error in repository runtime extension. No function in the model. Select a function. Repository: Error in repository runtime extension. Add columns to the Dataset table. Repository: Error in repository runtime extension. Invalid file. Check the file or create the file again. … Public 21
    22. 22. Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP’s strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2013 SAP AG. All rights reserved. Public 22
    23. 23. Thank you Contact information Ron Silberstein SAP HANA Product Management AskSAPHANA@sap.com To get the best overview of what’s new in SAP HANA SPS 07, read this blog.
    24. 24. © 2013 SAP AG. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP AG. The information contained herein may be changed without prior notice. Some software products marketed by SAP AG and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP AG and its affiliated companies ("SAP Group") for informational purposes only, without representation or warranty of any kind, and SAP Group shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP Group products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and other countries. Please see http://www.sap.com/corporate-en/legal/copyright/index.epx#trademark for additional trademark information and notices. © 2013 SAP AG. All rights reserved. Public 24
    25. 25. © 2013 SAP AG. Alle Rechte vorbehalten. Weitergabe und Vervielfältigung dieser Publikation oder von Teilen daraus sind, zu welchem Zweck und in welcher Form auch immer, ohne die ausdrückliche schriftliche Genehmigung durch SAP AG nicht gestattet. In dieser Publikation enthaltene Informationen können ohne vorherige Ankündigung geändert werden. Einige der von der SAP AG und ihren Distributoren vermarkteten Softwareprodukte enthalten proprietäre Softwarekomponenten anderer Softwareanbieter. Produkte können länderspezifische Unterschiede aufweisen. Die vorliegenden Unterlagen werden von der SAP AG und ihren Konzernunternehmen („SAP-Konzern“) bereitgestellt und dienen ausschließlich zu Informationszwecken. Der SAP-Konzern übernimmt keinerlei Haftung oder Gewährleistung für Fehler oder Unvollständigkeiten in dieser Publikation. Der SAP-Konzern steht lediglich für Produkte und Dienstleistungen nach der Maßgabe ein, die in der Vereinbarung über die jeweiligen Produkte und Dienstleistungen ausdrücklich geregelt ist. Keine der hierin enthaltenen Informationen ist als zusätzliche Garantie zu interpretieren. SAP und andere in diesem Dokument erwähnte Produkte und Dienstleistungen von SAP sowie die dazugehörigen Logos sind Marken oder eingetragene Marken der SAP AG in Deutschland und verschiedenen anderen Ländern weltweit. Weitere Hinweise und Informationen zum Markenrecht finden Sie unter http://www.sap.com/corporateen/legal/copyright/index.epx#trademark. © 2013 SAP AG. All rights reserved. Public 25

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