hana to go presentation final with demo screen shots nov8

CONFIDENTIAL

SAP Hana Technical WorkshopHigh Performance Analytics October 6, 2011

SAP HANA Overview

AGENDA

HANA Overview & Roadmap HANA Architecture Introduction to SAP HANA Studio Loading Data into HANA Start hands on workshop

• Modeling Data – Attribute Views

• Modeling Data – Analytic Views

• Viewing Results – SAP Business Objects Clients

• Advanced Information Models

Wrap Up – Q & A

LUNCH IS SCHEDULED FOR 11:30

SAP in-memory innovations make the “New Way” a reality

In-Memory

Column Database

Massively Parallel

Processing

Calculation Engine

Columnar storage increases the amount of data that can be stored in limited memory

(compared to disk)

Column databases enable easier

parallelization of queries

Row database fast transactional processing

In-memory processing gives more time for

relatively slow updates to column data

In-memory allows sophisticated calculations

in real-time

MPP optimized software enables linear performance scaling

making sophisticated calculations like allocations

possible

Enabling IT AgilityHow Fast Can IT React on Change? – Empower Business People

How can In-Memory help? In-Database Analytics No aggregates No MOLAP cubes External hierarchies No re-alignment runs Virtual structures only Stable performance

traditional change management process

SAP HANA Proof-PointsEnabling Business Agility

SAP HANA

In-Memory AnalyticsSAP HANA real-time operational

analyticsComplete BI Suite with BI 4 runs

on SAP HANABegin delivery of Baseline

Reporting packages

One Store for Data and AnalyticsSAP HANA only persistence layer for

SAP Business SuiteSAP Business Suite optimized for in-

memory computing

Flexible real time analysis of operations at non-aggregated level

Real-Time operational planning and simulation capabilities: link to execution

Primary persistence and optimized for SAP BW

Reduced landscape complexityValue chain transformation

Next-gen ApplicationsSAP BW fully running on SAP HANASAP HANA platform for in-memory apps

■ Industry and LOB Analytic Apps ■ Other purpose built apps

Further optimization of BI 4 Suite for SAP HANA

SAP Business Suite begins move to SAP HANA

SAP HANA 1.0 sp3

VisionLonger-Term

SAP HANA Development RoadmapProduct Strategy and Plan

SAP HANA 1.0Dec 2010

SAP HANA 1.0 sp1, July 2011

sp2General

AvailabilityRTC

(Ramp-up)

Just Some of the New HANA-EnabledApplications for 2011

SAP Cash and Liquidity Management: Allows companies to predict inbound and outbound cash flows and risk management.

Sales and Operations Planning: This application will enable sales and marketing departments to collaborate with operations and finance in order to evaluate the impact of their strategies and make accurate predictions.

Intelligent Payment Broker: This application will calculate financing options on open invoices and will help determine which discounting terms should be offered on which invoices.

Smart Meter Analytics: The software for intelligent electricity meters: With this application utility companies can analyze smart meter readings to forecast demand and develop new products.

SAP Trade Promotion Management : Improves the planning process and helps develop accurate strategies for particular customers.

SAPCRM Rapid

Deployment Solution

SAP ERP rapid-deployment solution for operational reporting with SAP HANA™ software

Business Models and Reports included: Financial Reporting Sales Reporting Procurement Reporting Shipping Reporting Master Data Reporting

Solution to provide compelling SAP ERP operational analytics quickly and affordably

Description An essential reporting software with fixed scope, predefined services at a predictable price with the flexibility for future extension. It provides a set of reports from the business area of sales, financial, shipping, procurement, and master data.

Current situationReactive business model and lack of business transparency due to sub-optimal execution speed of the current ERP operational reporting solution

Value propositionProvide flexible real time analytics, improve business performance, strengthen competitive advantage, provide quick wins for business.

Outcome opportunity Sales people’s efficiency is increased, plans are more accurate and reporting is more timely.

SAP HANA Architecture

SAP HANA

In-Memory Computing Engine

Admin and Data Modeling

Real–Time Replication Services

Data Integration Services

In-MemoryRow/ColumnData Store

Calculation and Planning

Engine

SAP NetWeaver BW

3rd Party

SAP Business Suite

CustomApplications

SAP BusinessObjects

MDX SQL Optimized

Data Management Service

SAP HANA – Complete SolutionPreconfigured Analytical

Appliance■ In-Memory software + hardware

(Cisco, Dell, HP, IBM, Hitachi and Fujitsu)

In-Memory Computing Engine Software

■ Data Modeling and Data Management

■ Real-time Data replication for SAP ECC

■ Data Integration for 3rd Party Systems

Capabilities Enabled■ Analyze information in real-time at

unprecedented speeds on large volumes of non-aggregated data

■ Create flexible analytic models based on real-time and historic business data

■ Foundation for new category of applications (e.g., planning, simulation) to significantly outperform current applications in category

■ Minimizes data duplication

Architecture OverviewIn-Memory Computing Engine and Surroundings

Clients (planned, e.g.) BI4 Explorer

Dashboard Design

SAP BI4 universes (WebI,...)

Request Processing / Execution Control

MS Excel

BI4 Analysis

SQL Parser MDX

SQL Script Calc Engine

Transaction Manager

Session Management

Relational EnginesRow Store Column Store

Persistence LayerPage Management Logger

Disk StorageLog VolumesData Volumes

Authorization Manager

Metadata Manager

In-Memory Computing Studio

Administration Modeling

ERP DB

System Landscape

Transformation

SAP Business Objects BI4

Data Services Designer

SBO BI4 servers ( program for client)

SBO BI4 Information

Design Tool

Other Source Systems

SAP NetWeaver

BW3rd Party

Data Services

Architecture OverviewIn-Memory Computing Engine and Surroundings

ERP DB

Dashboard Design

Request Processing / Execution Control

MS Excel

BI4 Analysis

SQL Parser MDX

Transaction Manager

Session Management

Metadata Manager

System Landscape

Transformation

SAP Business Objects BI4

SBO BI4 Information

Design Tool

SAP NetWeaver

BW3rd Party

Data Services

Request Processing / Execution ControlSQL Parser MDX

Transaction Manager

Session Management

Relational Engines

Row Store Column Store

Metadata Manager

ERP DB

System Landscape

Transformation

Architecture OverviewLoading Data into SAP HANA

Transaction Manager

Session Management

Metadata Manager

Business Objects Enterprise

SBO Information

Design Tool

SAP NetWeaver

BW3rd Party

Data Services

Dashboard Design

MS Excel

BI4 Analysis

Architecture OverviewData Modeling

Transaction Manager

Session Management

Metadata Manager

SBO Information

Design Tool

SAP NetWeaver

BW3rd Party

Data Services

Dashboard Design

MS Excel

BI4 Analysis

ERP DB

System Landscape

Transformation

Clients (planned, e.g.)

Architecture OverviewReporting

Transaction Manager

Session Management

Metadata Manager

SBO Information

Design Tool

SAP NetWeaver

BW3rd Party

Data Services

BI4 Explorer

Dashboard Design

MS Excel

BI4 Analysis

ERP DB

System Landscape

Transformation

Architecture OverviewAdministration

Transaction Manager

Session Management

Metadata Manager

SBO Information

Design Tool

SAP NetWeaver

BW3rd Party

Data Services

Dashboard Design

MS Excel

BI4 Analysis

ERP DB

System Landscape

Transformation

HANA Modeling Process Flow

Import Source System metadata•Physical tables are created dynamically (1:1 schema definition of source system tables)

Provision Data•Physical tables are loaded with content.

Create Information Models•Database Views are created•Attribute Views•Analytic Views•Calculation Views

Deploy•Column views are created and activated

Consume•Consume with choice of client tools

•BICS, SQL, MDX

HANA Information Models

Attribute Views – Think Master data or single dimension view of data

Analytic Views – Think data cube or Star Schema model / merged facts and dimension table

Calculation View – Think extended functionality or complex calculation capabilities.

Introduction to SAP HANA Studio

Framework for Modeling within HANA

Analyze Data in Hana

Information in single

Base Tables Only Joins and

calculated expressions

Access Base Tables/ Attr

Use Attribute Views

Star Schema or Aggregation

Use Analytic Views

Try Graphical Calc View

not enough

Use Graphical

Calc Views

Use Scripted Calc Views

not enough

Attribute views

Analytic Views

Calc Views

Welcome to the SAP HANA Studio

Starting the Modeling Environment

• Find the Modeler short cut on the desktop and double click to open it.

Information Modeler – SAP HANA Studio

Tour of the UI:

• Based on Eclipse

• Consistent with other SAP Modeling/Developer tools

• Navigation

• Perspectives

• Information Panel

Check System Status

It is possible to check the status of the HANA system from the Modeler

• Select the IM2 system

• Click on the Wrench

Check System Status

From the Status Window Navigate the tabs

• Landscape

• Alerts

• Performance• Load

Navigating HANA

The Navigator view is the main way to access content in the HANA system.

Top level nodes are System Instances.

Each instance contains:

Catalog Authorizations/Security Schemas/Data Tables

Content Virtual Information Models

Instance

Security

Schemas/Data

Information Models

Navigating HANA

Schemas provide a way to organize and work with the assets in your database.

Here we can view and modify the various objects that are part of a schema

For example, you can look at the Definition of a Table by Right clicking on the Table name and selecting Open Definition.

Navigating HANA

While in the Definition view of the Table, you can see:• Names, data types, etc. of

the Table

• Indexes defined for the Table

• Runtime Information• Shows Table type (Column

or Row Store)

• Main/Delta Size

Navigating HANA

Other actions that are available on a Table include:

•Open Content• Displays the Top

1000 records

Navigating HANA

•Open Content• Displays the Top

1000 records

• Open Data Preview• Displays data in

table form

• Allows for basic profiling of the data.

Navigating HANA

•Open Content• Displays the Top 1000

records

• Open Data Preview• Displays data in table

• Allows for basic profiling of the data.

• Generate SQL• Insert Statement

• Select Statement

• Visual SQL

• Use Table as Template

Navigating HANA

A SQL Editor is available for free hand SQL

Navigating HANA

Information Models are organized under the Content folder in the Navigator view.

Create/Modify/View

• Attribute Views

• Analytic Views

• Calculations Views

• Analytic Privileges

• Procedures

Navigating HANA

Select Data Preview for the Analytic View ORDER_WAREHOUSE

Interact with the virtual views directly in the HANA Modeler

Loading Data into HANA

Populating HANA with Data

Currently there are three primary ways for transporting data in to HANA:

• Direct import from within HANA• System Landscape Transformation (SLT)

• Move data directly from ECC to HANA

• Supports near real-time replication from ECC

• SAP BusinessObjects Data Services Can be used on a broad array of data source including SAP ECC and SAP BW. Can source directly from SAP BW extractors Can support transformation logic in the data flow

SAP BusinessObjects DataServicesExtractor Support

Use extractors in a data flow like a regular source

LT Replication Concept: Trigger-Based ApproachConfiguration of LT Replication Server

RFC Connection

Table space (optional)

Replication mode

Connection to HANA

Number of jobs

A schema defines the configuration ofthe data replication for a source system

Loading Data into HANA

In the following section we will load data into HANA using SAP BusinessObjects Data Services. We will perform the following steps:

1. Prepare the HANA system for the load

2. Perform the load from SAP Business Objects Data Services

3. Verify that the data was loaded correctly

The Data Model

For our Exercise we are using the TPC-H database.

The data was generated with the publicly available utility used to generate data for this benchmark. The default data set was generated with roughly 6 million records in the main fact table.

Preparing to Load Data

• Navigate to the ORDERS table in the HANA_TPCH Schema.

• Right clink on the ORDERS table and select “Generate”/”Select Statement”

Execute the SQL statement generated.

Switch back to the SQL tab and change the SQL statement to the one belwo and execute the statement. There should br 1.5 million records in the table.

Prepare to Load Data

Delete the data in the table.

Input the SQL below and execute it.

Load Data

Start the SAP BusinessObjects Data Services client ( in a production system this would be an automated process).

Load Data

Log into the SAP BusinessObjectes Data Services Client:

• User name: dsuser

• Password: abc123

• Select the “Log On” button

• Select the “Local Repo” Repository

• Select the “OK” button

Load Data

Data Services Designer.

Load Data

Open the “TPCH_Data_Load” project by double clicking on the folder in the lower left of the UI.

Load Data

Expand the TPCH_Job_Runner node until it looks like this.

Load Data

Double Click on the Query Icon to see the data mappings from input table to HANA table.

Load Data

• Right click on the “TPCH_Job_Runner” node in the Project Area panel and select “Execute…”

• You will be prompted to “Save all changes and execute”. Select the “Yes” button.

Load Data

• You will see an “Execution Properties Dialog.

• Do not alter the default values and select the “OK” button.

Load Data

• Select the “Monitor” button in the top of the main window dialog to watch the data load into HANA.

• 1,500,000 million rows should load in just under a minute.

• You can now Exit SAP Business Objects Data Services and return the the SAP HANA Studio.

Verify the Data

From the SAP HANA Studio Return to your SQL window and execute the command below.

BEGIN HANDS-ON EXERCISE!

Modeling Data – Attribute Views

The Data Model

For our Exercise we are using the TPC-H database.

The data was generated with the publicly available utility used to generate data for this benchmark. The default data set was generated with roughly 6 million records in the main fact table.

Use Attribute Views

Use Analytic Views

not enough

Use Graphical

Calc Views

not enough

Attribute views

Analytic Views

Calc ViewsW

Modeling Data – Analytic Views

Use Attribute Views

Use Analytic Views

not enough

Use Graphical

Calc Views

not enough

Attribute views

Analytic Views

Calc Views

Viewing Results

• SAP BusinessObjects Explorer

• SAP BusinessObjects Web Intelligence

More Complex Information Models

Use Attribute Views

Use Analytic Views

not enough

Use Graphical

Calc Views

not enough

Attribute views

Analytic Views

Calc Views

Calculation ViewGraphical

JOINUNION

No SQL coding required Union, Join, Projection nodes provided Join Column Tables (Analytical Views)

Calculation ViewSQLScript (Script-based)

SQL or SQLScript required to create Script based Calculation Views Write SQL Select statements against existing raw tables or Column Stores

(preferred) Define output structure, activation creates column store based on Script

Output

Creating a Calculation ViewGraphical

A new Analytic View was created (Customer_Order) to support this exercise.

This Analytic View combines the Order Fact table with the Customer Attribute View. Two Calculated Attributes were created to capture Year and Month.

This is the completed Calculation View that we will be creating.

The goal of this Calc View is to Union the Current Year and Prior Year Sales together along with some desired Attributes.

The new Customer_Order Analytic View is the source for this Calc View. In the Projection you specify the Attributes and Measures you want to include from the Analytic Views, as well as two calculated columns.

Each Projection will also filter the data for a specific Year.

A Union is configured to define the mapping to combine the 2 datasets.

Lastly the Output dataset is defined.

Calc View Creation Right click on the

Calculation View Folder and select New => Calculation View

Provide a Name and Description

Leave the View Type as Graphical as click “Next”

Calc View Creation The next dialog window

allows you to choose tables, but we’re going to use an Analytic View so just click “Next”

Expand the Analytic Views Folder, Add Customer_Order, and Click “Finish”

Calc View Creation

The Initial View is defined with the “Customer_Orders” Analytic View and the Output component. Add a “Projection”

Component Link the Customer_Order AV

with the Projection Component

Select the Projection Component and add the desired fields to the Output (R_NAME, N_NAME,C_MKTSEGMENT, C_NAME, O_YEAR, O_MONTH, O_TOTALPRICE)

Apply a Filter to the O_YEAR so that Year = 1998 (Most recent year in this dataset is 1998)

Calc View Creation Create a Calculated Column

for Current Year (The Expression is just the O_TOTALPRICE field because the filter returns the current year)

Create a Calculated Column for the PriorYear with the Expression defined as 0. We need this field so that the Union will function properly (All Queries in a Union need the same number of fields.)

Calc View Creation

The Prior Year dataflow needs to be added to the Calculation View. Drag the CUSTOMER_ORDER

Analytic View onto the pallet Add a “Projection” Component Link the Customer_Order AV with

the Projection Component Select the Projection Component

and add the desired fields to the Output

Apply a Filter to the O_YEAR so that Year = 1997

Create a Calculated Column for Current Year (The Expression is 0)

Create a Calculated Column for the PriorYear with the Expression defined as O_TOTALPRICE.

NOTE: The Output fields and the Calculated Columns for the Prior Year Projection must be in the same order as the Current Year Projection.

Calc View Creation

The next step is to “Union” the two Projections together. Add a Union component Add links from the two Projections

to the Union component. Select the Union component and

add the desired fields from the first Projection to the Target panel (all fields with the exception of O_YEAR and O_TOTALPRICE)

Map the fields from the second Projection to the appropriate Target field.

Calc View Creation

The next step is to link the Union component to the Output Component and specify the Output fields. Add a link from the Union

component to the Output component.

Add the Attribute fields. Select the Output component and add the desired fields as Attributes

Add the Measure fields using the same process.

Save the Calc View Activate the Calc View Preview the Data

Calculation ViewScript

Calc View

This Calc View accomplishes the same thing but is defined using the Script technique instead of the Graphical approach.

SQLScript / R / BFL (Business Function Library)Three ways to implement in-memory data mining and statistical analysis

SQLScript SQLScript is a set of SQL extensions which allow developers to push data-

intensive logic into the database in order to avoid massive data copies to the application server and to leverage sophisticated parallel execution strategies of the database.

R Through the R integration solution, developers can leverage open source R’s

3000+ external packages to perform wide-range data mining and statistical analysis.

BFL (Business Function Library) BFL is the calculation library for the applications built on top of the SAP HANA

database. The business functions are written in C++ and executed in database calculation engine. BFL has a roadmap for data mining and statistical algorithms.

SQLScript

The set of SQL extensions for the SAP HANA database which allow developers to push data intensive logic into the database is called SQLScript.

These extensions are keys to avoiding massive data copies to the application server and to leverage sophisticated parallel execution strategies of the database.

SQLScript V2 supports stored procedures, which provides enhanced control flow capabilities and is positioned to be more suitable for pushing complex parts of application logic to the database.

It can meet some simple requirement for reporting, like join, aggregation, etc. When it comes to data mining and statistic analysis, SQLScript is not suitable for implementing complex algorithms.

Calculation View (Scripting)

Calculation View Define Table Output Structure Write SQL Statement.

Ensure that the selected fields corresponds to previously defined Output table structure of the function.

Example : SQL_A = SELECT MATNR, KUNNR, …. FROM

<COPA_ACTUAL_ANALYTICAL VIEW 1>

SQL_P = SELECT MATTNR_KUNNR, … FROM

<COPA_PROJECTED_ANALYTICAL VIEW 2>

TABLE_OUTPUT_STRUCTURE =

SELECT * FROM <SQL_A> UNION

SELECT * FROM <SQL_P>;

R Integration with the SAP HANA database – Scenario 1

Join OP

OLAP OP

Calc. Engine

R External Packages

(Forecasting, Parallelism,

statistics, etc.)

RClient

SAP RHANA Package

Send data and R script

NewDB Space OpenSource R Space

NewDBR

IntegrationOpen Source

2 Run the R scripts

Get back the result from R to SAP HANA

Usage Scenario 1 Utilize Open Source R as the data mining calculation engine. Application developer can embedded R scripts in the

SQLScript.CREATE FUNCTION LR( IN input1 SUCC_PREC_TYPE, OUT output0 R_COEF_TYPE) LANGUAGE RLANG AS''' CHANGE_FREQ<-input1$CHANGE_FREQ; SUCC_PREC<-input1$SUCC_PREC; coefs<-coef(glm(SUCC_PREC ~

CHANGE_FREQ, family = poisson )); INTERCEPT<-coefs["(Intercept)"]; CHANGEFREQ<-coefs["CHANGE_FREQ"]; result<-as.data.frame(cbind(INTERCEPT,CHANGEFREQ))''';

TRUNCATE TABLE r_coef_tab; CALL LR(SUCC_PREC_tab,r_coef_tab );SELECT * FROM r_coef_tab;

Sample Codes in SAP HANA SQLScript

Business Function Library

Business Function Library (BFL) is the calculation library for Applications built on top of the SAP HANA database. It resides in the Calculation Engine and consists of many Business Functions executing at the database layer and is written in C++.

Significant performance improvements for SAP apps

1. Utilizing new hardware i.e. multi core, built in vector engine

2. Massive parallel main memory processing

3. Changing the boundaries between application server and data management layer

Simplification of application programming model

4. Usage of extended SQL(SQLScript) 5. Rich functionalities in the Calculation

Engine6. Fast apps delivery

Design GoalsBFL Wiki

Thank You!

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