D_HANAIMP_11 sample Questions

ABAP Programming for SAP HANA

PARTIC IPANT HANDBOOKINSTRUCTOR-LED TRAINING

Course Version: 11 Course Duration: 4 Day(s) Material Number: 50124104

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Contents

ix Course Overview

1 Unitl: Introduction

3 Lesson: SAP HANA Basics and Technical Concepts

15 Exercise 1: Log on to ABAP Systems and Create Packages

22 Lesson: Introducing the SAP HANA Studio

29 Exercise 2: Log on to SAP HANA

34 Lesson: Introducing the ABAP Development Tools (ADT)

43 Exercise 3: Create a Project in ABAP Development Tools

47 Lesson: Introducing the EPM Sample Application

51 Unit 2: Taking ABAP to SAP HANA

52 Lesson: SAP HANA as Secondary Database- Access via Open SQL

57 Exercise 4: Access SAP HANA Via a Secondary Database

Connection

66 Lesson: Preparing for SAP HANA

75 Exercise 5: Improve Open SQL Using ABAP Test Cockpit

86 Lesson: Guided Performance Analysis

95 Exercise 6: Use the SQL Performance Tuning Worklist to

Analyze Static and Runtime Check Results

101 Exercise 7: Improve Open SQL Statements Using The SQL

Trace (ST05)

110 Lesson: Performance Rules and Guidelines for SAP HANA

113 Unit 3: Code-to-Data with SAP HANA as Secondary Database

115 Lesson: Classical Open SQL and Its Limitations

120 Lesson: ABAP Database Connectivity (ADBC)

123 Lesson: Native SQL Syntax

127 Exercise 8: Issue a Native SQL Join via ADBC

135 Exercise 9: (Optional) Use Native SQL to Access SAP HANA-

Specific Functionality

143 Lesson: Working with Views in SAP HANA Studio

151 Lesson: Consuming SAP HANA Views using Native SQL

155 Exercise 10: Analyze a SAP HANA View and Use it in Native SQL

164 Lesson: Working with Database Procedures in SAP HANA Studio

169 Lesson: Calling SAP HANA Procedures in ABAP

173 Exercise 11: Analyze a SAP HANA Database Procedure and Call

it with Native SQL

201213

Lesson: New Open SQL

Exercise 12: Apply New Features in OpenSQL

Lesson: Core Data Services in ABAP

Exercise 13: Core Data Services in ABAP

Lesson: Associations in Core Data Services

Exercise 14: Use Associations in Core Data Services in ABAP

Lesson: Core Data Services with Input Parameters

Exercise 15: Core Data Services View with Input Parameter

Lesson: Incorporating Authorization Checks with CDS

Unit 5: Code-to-Data with SAP HANA as Primary Database

Lesson: ABAP-Managed Database Procedures

Exercise 16: Create and Call an AMDP

Lesson: Debugging ABAP-Managed Database Procedures

Exercise 17: Debug an ABAP-managed Database Procedure

Unit 6: SAP HANA Proxy Objects

Lesson: Accessing SAP HANA Views via ABAP Dictionary External

Exercise 18: Create an External View for SAP HANA View and

Use it in an Open SQL SELECT

Lesson: Calling SAP HANA Procedures via ABAP Database

Procedure Proxies

Exercise 19: Call a Database Procedure Proxy for a SAP HANA

Procedure in an ABAP Program

Lesson: Transport of SAP HANA Objects

Exercise 20: Create a SAP HANA Transport Container for a

Delivery Unit

Unit 7: Advanced Topics

Lesson: Using SAP HANA Full Text Search

Exercise 21: Implement a Fuzzy Search

Exercise 22: Implement Type-Ahead with Fuzzy Search

Lesson: ABAP List Viewer (ALV) with Integrated Access to SAP

Exercise 23: Use ALV Optimized for SAP HANA

Unit 8: Case Study: Optimize a Report on Flight Customer Revenue

Lesson: Creating an Analytic View

Exercise 24: Case Study Part 1: Create a SAP HANA Analytic

Exercise 25: Case Study Part 2: Use ALV Optimized for SAP

Lesson: Exercises Based on Flight DataModel

Exercise 26: Log on to ABAP Systems and Create Packages

Exercise 27: Create a Project in ABAP Development Tools

Exercise 28: Access SAP HANA Via a Secondary Database

Connection

Exercise 29: Improve Open SQL by Using Code Inspector (SCI)

Exercise 30: Improve Open SQL Statements Using The SQL

Trace (ST05)

Exercise 31: Issue a Native SQL Join via ADBC

Exercise 32: (Optional) Use Native SQL to Access SAP HANA

Specific Functionality

Exercise 33: Analyze a SAP HANA View and Use it in Native SQL

Exercise 34: Analyze a SAP HANA Database Procedure and Call

it with Native SQL

Exercise 35: Use New Open SQL Syntax

Exercise 36: Core Data Services in ABAP

Exercise 37: Use Associations in Core Data Services in ABAP

Exercise 38: Core Data Services View with Input Parameter

Exercise 39: Create and Call an ABAP Managed Database

Procedure

Exercise 40: Debug an ABAP-Managed Database Procedure

Exercise 41: Create an External View for SAP HANA View and

Use it in an Open SQL SELECT

Exercise 42: Create a Database Procedure Proxy for a SAP

HANA Procedure and Call it in an ABAP Program

Exercise 43: Use ALV Optimized for SAP HANA to Display an

External View

Unit 10: Appendix: Other New ABAP Language Elements

Lesson: Additional ABAP Language Enhancements

Exercise 44: Use ABAP Expressions and Inline Data

Declarations to Simplify Native SQL Calls

Exercise 45: Use Table Expressions to Simplify Native SQL Calls

Course Overview

TARGET AUDIENCEThis course is intended for the following audiences:

• Developer

• Development Consultant

UNIT 1 Introduction

Lesson 1

SAP HANA Basics and Technical Concepts

Exercise 1: Log on to ABAP Systems and Create Packages

Lesson 2

Introducing the SAP HANA Studio 22

Exercise 2: Log on to SAP HANA 29

Lesson 3

Introducing the ABAP Development Tools (ADT) 34

Exercise 3: Create a Project in ABAP Development Tools 43

Lesson 4

Introducing the EPM Sample Application 47

UNIT OBJECTIVES

• Describe SAP HANA goals, technical innovations and challenges

• Understand the fundamental technical concepts of SAP HANA

• Explain the SAP HANA and ABAP evolution, architecture, and direction

• Determine if HANA’s row store or column store is used for an ABAP transparent table, and which indices are used on HANA

• Explain the central functions of HANA Studio

• Switch between different perspectives in the SAP HANA Studio

• Set up a connection to a SAP HANA database

• Understand schemata and tables in SAP HANA Studio

• Analyze the definition of tables in SAP HANA Studio

• Use the ABAP Development Tools in Eclipse

• Describe the Enterprise Procurement Model business example

• Describe the Open Item Analytics sample applications and which computations it involves

Unit 1 Lesson 1

SAP HANA Basics and Technical Concepts

LESSON OVERVIEWIn this lesson, you learn how to describe SAP HANA goals, technical innovations, and challenges; understand the fundamental technical concepts of SAP HANA; explain the SAP HANA and ABAP evolution, architecture, and direction; and determine if SAP HANA's row store or column store is used for an ABAP transparent table and which indices are used on SAP HANA.

Business Example

Your company has recognized SAP HANA as an important strategic topic and has asked you to refresh your ABAP skills, paying particular attention to those required to develop or review code that leverages the strengths of SAP HANA.

LESSON OBJECTIVESAfter completing this lesson, you will be able to:

• Describe SAP HANA goals, technical innovations and challenges

• Understand the fundamental technical concepts of SAP HANA

• Explain the SAP HANA and ABAP evolution, architecture, and direction

• Determine if HANA’s row store or column store is used for an ABAP transparent table, and which indices are used on HANA

SAP HANA Goals

BroadBig Data,

many data types

DeepComplex & interactive

questions on granilar data

Real-TimeRecent data,

preferably real-time

High-SpeedFast response

time,interactivity

SimpleNo data preparation, no pre-aggregation

BroadBig Data,

many data types

questions on granular data

wHigh-SpeedFast response

time,interactivity

SimpleNo data preparation, no pre-aggregation

Figure 1: Today's Technology Requires Tradeoff Decisions

Developing applications using technology that pre-dates SAP HANA typically required making several trade-off decisions.

The figure shows the five dimensions of requirements that are typical for business applications. These dimensions have been conflicting so far.

For example, you had to make trade-off decisions between providing a high-speed application and developing an application that doesn’t require preparing the data in a special way first, for example, by calculating aggregations beforehand and by storing the results in addition to the base data. Another example is that it was not possible to develop an application which is both real-time and able to analyze a large amount of data, maybe even unstructured data, at the same time.

questions on granular data

BroadBig Data, many

data types

SAP HANA(

High-SpeedFast response time,

interactivity

• SimpleNo data preparation, no pre-aggregation

Figure 2: SAP HANA: Delivers Across Five Dimensions

SAP HANA tries to deliver across all these five dimensions, so that you no longer have to make so many trade-off decisions. In other words, the ambition is to enable the development of applications that combine Online Transaction Processing and Online Analytical Processing usage patterns. This leads to certain goals HANA has to meet.

Enable New Applications and Optimize Existing Applications

• High Performance and Scalability

• Hybrid Data Management System

• Compatibility and Standard DBMS Features

• Support For Text Analysis, Indexing and Search

• Cloud Support and Application Isolation

• Support for Temporal Tables

• Executing Application Logic inside the Data Layer

Figure 3: SAP HANA Goals

SAP HANA has the following goals:

Enable new applications and optimize existing applications

SAP HANA is an In-memory data platform that is deployable as an appliance or in the cloud and makes full use of the capabilities of current hardware to increase application performance, reduce cost of ownership, and enable new scenarios and applications that were not possible before.

High performance and scalability

SAP HANA is designed to make full use of multi-core CPUs by parallelization of execution. It can be distributed across multiple servers to achieve good scalability in terms of both data volume and concurrent requests.

Hybrid data management system - combining different paradigms in one system

SAP HANA architecture integrates different in-memory storages (column-based, row- based, and object-based), traditional disk-based tables, text analysis and search, and built-in support for planning. Combining all these capabilities in a single product not only improves performance but reduces overall complexity and cost.

Compatibility and standard DBMS features

An important goal is the possibility to use the SAP HANA database system as a replacement for any standard relational database management system. The SAP HANA database system is a full relational database management system with SQL interface, transactional isolation and recovery (ACID properties) and high availability. SAP applications that use Open SQL should run on SAP HANA without changes.

Support For text analysis, indexing and search

An important goal of SAP HANA is to provide powerful analysis, and text indexing and search capabilities that support a state-of-the-art search experience. This includes full text search with advanced features, such as free style search (without knowing the name of attributes in the database), linguistic search, and fault-tolerant fuzzy search.

Cloud support and application isolation

In cloud deployments, it is required that a system be shared - including physical servers and installed software - between multiple customers. SAP HANA will support this in the future, with the planned ability to host multiple isolated databases within a single SAP HANA system. The databases inside one system will have their own data, metadata, and users, but will share the same hardware, the same SAP HANA software installation, and the system administration. This feature helps to support cloud scenarios - but it can also be used in an on-premise deployment, for example, for running multiple unrelated applications in one SAP HANA system with effective isolation and resource management.

Support for temporal tables

SAP applications that use Open SQL should run on SAP HANA without changes. In temporal tables, update operations do not modify the existing records. Instead, new versions of the data records are inserted. Applications may use temporal tables, for example, for time-based reporting and analysis or for versioning and change recording purposes.

Executing application logic inside the data layer

To benefit from the parallelization and optimization capabilities of SAP HANA, applications must execute data intensive operations on the database level. Pushing calculations to the database layer can also significantly reduce the amount of data that needs to be transferred between the database and application server. SAP HANA allows application developers to define application-specific functions that are executed inside the database layer.

SAP HANA Application Architectures

SAP HANA can be used in different architectural scenarios, which in turn provide thetechnological base for the different application areas.

Types of SAP HANA-Based Applications

Data marts based on SAP HANA New or native SAP HANA applications

Business Intelligence Tools, Microsoft Excel,Web Browser...

Figure 4: Architectural Scenarios

SAP HANA can be used in different architectural scenarios, which in turn provide the technological base for the different application areas.

From an ABAP programmer’s point of view, there are two groups of scenarios, as follows:

• Scenarios in which SAP HANA functions as the database for an Application Server ABAP.

• Scenarios based on a standalone SAP HANA Server.

Although the non-ABAP scenarios are mentioned here, they are not the focus of this course.

The first type are data warehouses, in which data is typically replicated from existing applications into a separate SAP HANA database, on top of which analytical content is developed and then consumed using business intelligence tools or simply Microsoft Excel.

A second type of HANA-based application consists of the newly-built, native applications developed using SAP HANA extended application services.

ABAP applications on SAP SAP HANA as AcceleratorHANA as primary database

SAP GUI, browser-based GUI

SAP NetWeaver Application Server

E.g., SAP CRM on SAP HANA

ABAP Schema Database Tables

0- 5s i

SAP GUI, browser-based GUI

SAP NetWeaver Application Server

Aggregation Levels

Figure 5: SAP HANA as Database for ABAP Applications

The primary concern of this course is to learn how to optimize ABAP applications directly running on SAP HANA, that is, applications using SAP HANA as the primary database

underneath the ABAP stack. A typical example of this kind of application is SAP CRM powered by SAP HANA, or the Business Suite powered by SAP HANA.

The course also covers type of applications shown on the right part of the figure: using SAP HANA to accelerate ABAP applications by using a separate HANA server besides the ABAP stack, replicating some of the ABAP system's data into HANA, and calling HANA remotely from ABAP to speed up selected reports or transactions.

SAP HANA Innovations and Challenges

HW Technology Innovations

Multi-core architecture (8 CPU x 10 cores per blade)

Massive parallel scaling with many blades

64bit address space - 1TB V on current servers

Dramatic decline in price/performance

SAP SW Technology Innovations

— + l[ ]Row and column store

** 0 * Compression

Partitioning

No aggregate tables

m Insert-only on delta+ +-1

Figure 6: What Made SAP HANA Possible?

Dramatically improved hardware economics and technology innovations in software made it possible for SAP to deliver on its vision of the real-time enterprise with in-memory business applications. Understanding them is important to an understanding of SAP HANA’s performance characteristics.

In-Memory Computing and the Shift of Performance Bottlenecks

Historically, database systems were designed to perform well on computer systems with limited RAM. This had the effect that slow disk I/O was the main bottleneck in data throughput. Consequently, the architecture of those systems was designed with a focus on optimizing disk access, for example, by minimizing the number of disk blocks (or pages) to be read into the main memory when processing a query. In addition, CPUs had a single core and networks were far slower.

Computer architecture has changed in recent years. Multi-core CPUs (multiple CPUs on one chip or in one package) are now standard, with fast communication between processor cores enabling parallel processing. Main memory is no longer a limited resource, and modern servers can have 2TB of system memory, which allows complete databases to be held in RAM.

Currently, server processors have up to 64 cores, and 128 cores will soon be available. With the increasing number of cores, CPUs are able to process increased data per time interval.

This shifts the performance bottleneck from disk I/O to the data transfer between CPU cache and main memory.

Figure 8: New Bottlenecks Become Important - How To Avoid Them

Two Challenges

1. Optimize loading data into the CPU cache

-> Introduce columnar data storage

-> Use compression for database tables

2. Avoid CPU idle time - make use of parallelism

-> Process one request on several cores in parallel

-> Distribute table contents across blades (partitioning)

To get the best performance from current hardware, the new bottlenecks have to be avoided by addressing the challenges as follows:

• Avoid CPU cache misses and expensive data transfer from main memory into the CPU - optimize loading the data into the CPU.

• Avoid idling CPU cores - make use of parallelism by using all the cores of a CPU, and several CPUs.

Column Store Versus Row Store

Data in table ... organized in rows

Order Country Product Sales

456 France corn 1000

457 Italy wheat 900

458 Italy corn 600

459 Spain rice 800

-------------SELECT *

WHERE ORDER = 457________ _

Works fine in row store

SELECT SUM(Sales)...

Row store not optimal

Figure 9: Row Store

By accessing data in column-store order, you benefit immensely from simplified table scan and data pre-caching. This can make all the difference in performance.

Data in table ... ... organized in columns

457 Italy wheat 900

458 Italy corn 600

459 Spain rice 800

SELECT * ....WHERE ORDER = 457

\ ________ f \ \ f \456 France corn 1000

1 457 | 1 Italy | I wheat 900

458 Italy corn 600

\ JSpain

\ J{ rice

800v J

/ > SELECT SUM(Sales)... _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

Very expensive on column store Ideal for column store

A Figure 10: Column Store

Data Compression

SAP HANA uses a dictionary per column:Operates directly on compressed data, using integers More in-cache, less main memory access

Log ica l Table

457 Italy wheat 900

458 Spain rice 600

459 Italy rice 800

[ 460 Denmark corn 5001

461 Denmark rice 600

462 Belgium rice 600

463 Italy rice 1100

k. ... J

Compressed InvertedDictionary column index

1 Belgium 1 3 1 7

2 Denmark* *" _ A 2 5,6

3 France 3 1

4 Italy 4 ^ *C 4 2,4,8

5 Spain f i " 2 | 5 3

5 entries -> 6 2 Which orders

3 bits to encode 7 1 in Italy?

Where was order 460?

| Figure 11: Columnar Dictionary Compression

SAP HANA uses different, efficient compression methods, such as dictionary encoding, run- length encoding, and more. This has the following benefits:

• Reduces the amount of memory required.

• Speeds up operations on columns because the columns can be loaded into the CPU caches faster and with fewer loading cycles.

• Speeds up operations on columns because many comparisons become integer value comparisons. These are faster than string comparisons, for example.

Partitioning and Parallel Processing

processed by processed by

ColumnOrder

ColumnProduct

ColumnSales

456 corn 1000

457 wheat 1050

458 corn 600459 rice 800

460 wheat 2000

461 barley 300462 rye 900463 wheat 1200

processed

Figure 12: Parallel Processing

On SAP HANA and with column storage, data is only partially blocked. This makes parallel processing possible. Even the same column can be split up and processed by different cores at the same time.

D is tr ib u tin g d a ta a c ro s s s e v e ra l b la d e s a llo w s w o rk in g on s m a lle r

cla ta s e ts in p a ra lle l

Table 1 Table 2 Table 3 Table ...Table 1 | | | ^ 0 Year A Year A Year A

% / <&>

■■■

■■m

l Table 2 Table 1 Table 2 Table 3 Table ...

—̂ BHQI Year B Year B Year B

______ < £ * >

Table $•■■

■■■

Table 1 Table 2 Table 3 Table ...

— O H O

< < **>

Figure 13: Using Partitioning to Further Leverage Parallelism

The use of parallelism can be taken a step further by creating different partitions of the data to be stored and processed on different blades. This allows for the management and processing of huge amounts of data.

ABAP Programming for SAP HANA: Evolution and Opportunities

Step 3

ABAP can access SAP HANA

Side-by-Side Scenarios with AS ABAP 7.x

HANA DB

Step 2

ABAP can run on SAP HANA

SAP NetWeaver BW on SAP HANA

NetWeaver 7.31

HANA DB (SPS05)

Optimized ABAP on SAP HANA

Primary DB for AS ABAP

NetWeaver 7.40

HANA DB (SPS06)

Figure 14: SAP HANA Evolution

What's in it for ABAP Programmers?

The new capabilities of SAP HANA offer a huge variety of opportunities for ABAP Developers:

Accelerate Reduce time of background jobs

Extend Reach more usersTurn background jobs into interactive applications

Innovate New processes and applications

*| Figure 15: What's in it for ABAP Programmers

Accelerate

By optimizing the coding of long-running background jobs for SAP HANA, the runtime for these jobs can be reduced. More jobs can be executed in the same time, and particularly costly tasks are possible in one go, rather than splitting them up.

Extend

In the past, some reports had to be executed in the background, simply because their runtime was too long for dialog processing. Consequently, users worked on snapshots or pre-aggregated data sets. By optimizing these reports with SAP HANA, they can be offered as online reports again, displaying real-time data with full drill-down capability.

Innovate

With SAP HANA's analysis and calculation capabilities, ABAP developers can design new applications that would not have been possible in the past.

The arrival of in-memory technology on the database layer also requires a change in the way we design and implement applications.

Classical Approach

APPLICATION

DATABASE

Future Approach

-> MOVE calculations to database

-> Only transfer RESULTS

Figure 16: New Programming Approach

The basic approach of classic ABAP programming was as follows:

Keep the load from the database.Get all the data you need on the application server.Do your processing in ABAP.

In order to benefit the most from SAP HANA's capabilities, it is better to do expensive calculations and aggregations on the database itself, rather than transferring huge amounts of data onto the ABAP application server. This is a fundamental change to the ABAP programming paradigm. Now it becomes “ logic to data", rather than “data to logic” .

ABAP development guidelines

Improved tools for performance analysis

Extensions to ABAP language

Creating and consuming SAP HANA content with ABAP

Re-use components optimized for SAP HANA

Transparent optimizations

ABAPapplications using SAP HANA

Transparent Optimizations

SAP NetWeaver AS ABAP 7.4

Figure 17: Highlights of SAP NetWeaver AS ABAP 7.4 - Overview

ABAP 7.4 provides support for optimizing ABAP applications running on SAP HANA.

There are transparent optimizations you do not see as an application developer, but which you benefit from because they happen under the hood. An example is the s e l e c t ... f o r

a l l e n t r i e s ... statement in Open SQL, the implementation of which has been improved.

The ABAP language and the Open SQL language have been extended. For example, OpenSQL now supports more complicated joins and sub-queries, and there are ways to integrate SAP HANA stored procedures in ABAP code.

The use of SAP HANA artifacts has been simplified. For example, you can access SAP HANA column views through the ABAP Dictionary using Open SQL.

In addition, performance analysis tools, such as static code checks and the runtime analysis, have been improved. The ABAP Profiler perspective in the ABAP Development Tools in Eclipse has also been enhanced.

Some re-use components have been extended or optimized for SAP HANA, such as the SAP List Viewer (ALV).

In addition, the ABAP platform team provides guidelines for optimizing ABAP code running on HANA.

An example of an ABAP Dictionary extension in ABAP 7.4 is the ability to control which store a table of the ABAP system should live in.

A new tab has been added to the Maintain Technical Settings form for database tables. The new tab is called DB-Specific Properties, and allows for switching between three storage types when running on a SAP HANA database.

• Storage type Column Store creates the database table in the SAP HANA column store, or moves it there.

• Storage type Row Store creates the database table in the SAP HANA row store, or moves it there.

• This setting can be changed after the table has been created, and the table will be moved into the other store. Use this with caution, however, since it may involve reorganizing table contents, should such content exist already.

Unit 1 Exercise 1

Log on to ABAP Systems and Create Packages

Business Example

Your company has recognized SAP HANA as an important strategic topic and has asked you to refresh your ABAP skills, paying particular attention to those required to develop or review code that leverages the strengths of SAP HANA.

Log on to Application Server ABAP with SAP HANA as the Primary DatabaseUsing SAP Logon, log on to the Application Server ABAP that uses SAP HANA as a primary database — system NW740 on HANA with system ID T85. Create development package ZHA40CL##, where ## stands for your group ID.

Note:As a preliminary step, fill out the missing details below, as given by the instructor, and use this information for all exercises during this course:

Remote Desktop alias

Remote Desktop user name

Remote Desktop password

ABAP system using SAP HANA as primary database

NW740 on HANA. System ID T85

User name in ABAP system T85

Password in ABAP system T85

ABAP system using Sybase ASE as primary database

ZME on Sybase, System ID ZME

User name in ABAP system ZME

Password in ABAP system ZME

SAP HANA system host

SAP HANA system instance

SAP HANA user name

SAP HANA system password

1. Log on to the system labelled NW740 on HANA.

2. Open system status and check the system's release and database.

3. Create ABAP package ZHA400_##.

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