Front cover Enabling Real-time Analytics on IBM z Systems Platform Lydia Parziale Oliver Benke Willie Favero Ravi Kumar Steven LaFalce Cedrine Madera Sebastian Muszytowski Redbooks International Technical Support Organization Enabling Real-time Analytics on IBM z Systems Platform August 2016 SG24-8272-00 Note: Before using this information and the product it supports, read the information in “Notices” on page vii. First Edition (August 2016) This edition applies to IBM DB2 Analytics Accelerator for z/OS v5.1. © Copyright International Business Machines Corporation 2016. All rights reserved. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Notices . vii Trademarks . viii IBM Redbooks promotions . ix Preface . xi Authors. xii Now you can become a published author, too! . xiii Comments welcome. xiii Stay connected to IBM Redbooks . xiv Chapter 1. Executive overview. 1 1.1 Introduction . 2 1.2 Real-time analytics . 4 1.2.1 Business advantages . 5 1.2.2 IT advantages . 5 1.3 In-database analytics . 5 1.3.1 Accelerated in-database transformation . 6 1.3.2 Accelerated in-database predictive modeling . 6 1.4 Enabling applications with machine learning capability . 6 1.5 Value propositions. 7 1.6 Related products . 7 1.7 Use cases . 8 1.7.1 Countering payment fraud and financial crimes . 8 1.7.2 Insurance claims in-process payment analytics . 9 1.7.3 Predictive customer intelligence . 10 Chapter 2. Analytics implementation on z Systems platform. 11 2.1 Adding analytics to a mainframe data sharing environment . 12 2.1.1 SPSS Modeler . 15 2.1.2 DB2 Analytics Accelerator wrapper stored procedure . 16 2.1.3 Using accelerator-only tables . 18 2.2 Installation and customization . 19 2.2.1 DB2 and DB2 Analytics Accelerator setup and installation. 20 2.2.2 Required DB2 privileges for SPSS users . 24 2.2.3 SPSS Modeler client . 25 2.2.4 SPSS Modeler server . 32 2.2.5 Data sources in SPSS . 33 2.2.6 AQT_ANALYTICS_DATABASE variable . 33 2.2.7 User management in the SPSS Modeler server . 33 2.2.8 Installing SPSS Modeler scoring adapter for DB2 z/OS . 34 2.3 Real-time analytics lifecycle . 34 2.3.1 Swim lane diagram of in-database analytics lifecycle. 37 2.3.2 Interaction between a DB2 DBA and a data scientist . 37 2.3.3 Key strengths of various components. 38 Chapter 3. Data integration using IBM DB2 Analytics Accelerator Loader for z/OS . 41 3.1 Functional overview . 42 3.1.1 Loader v2.1 enhancements . 43 © Copyright IBM Corp. 2016. All rights reserved. iii 3.1.2 Loader methods to move data . 44 3.1.3 Components and interfaces . 44 3.2 Getting started. 46 3.2.1 Installation. 46 3.2.2 Customization . 46 3.2.3 Workload Management (WLM) performance goals . 47 3.2.4 IBM z Systems Integrated Information Processor (zIIP) . 53 3.2.5 z Systems advantage . 56 3.2.6 Parallelism . 57 3.3 Scenarios . 57 3.3.1 ACCEL_LOAD_TASKS . 58 3.3.2 Sequential Input IDAA_ONLY and IDAA_DUAL. 58 3.3.3 Load RESUME . 64 3.3.4 IBM DB2 Analytics Accelerator Loader image copy input. 67 3.3.5 VSAM . 68 3.4 System Management Facility (SMF) . 77 Chapter 4. Data transformation . 83 4.1 Introduction . 84 4.1.1 Accelerator-only table (AOT). 85 4.1.2 Enabling in-database processing on SPSS Modeler client. 86 4.2 SQL pushback in SPSS Modeler . 86 4.2.1 How SQL generation works . 86 4.2.2 Where improvements can occur with IDT using Accelerator . 87 4.3 Nodes supporting SQL generation for DB2 Accelerator . 88 4.3.1 Source palette tab. 88 4.3.2 Record Ops palette tab . 89 4.3.3 Field Ops palette tab. 90 4.3.4 Graphs palette tab . 92 4.3.5 Database Modeling (Nuggets) palette tab. 93 4.3.6 Output palette tab . 94 4.3.7 Export palette tab . 94 4.4 In-database analytics Processing effort by components. ..