├── .reuse
└── dep5
├── CONTRIBUTING.md
├── LICENSE
├── LICENSES
└── Apache-2.0.txt
├── README.md
└── exercises
├── ex0
├── README.md
├── images
│ ├── 01-InstallTemplates.png
│ ├── 02-DownloadRawFile.png
│ └── 03-RawDownload.png
└── sources
│ └── analytical_templates.xml
├── ex1
├── README.md
└── images
│ ├── 01-EmbeddedAnalyticsInABAPCloud.png
│ ├── 02-HandsOnScope.png
│ └── 03-ADTDemoFlight.png
├── ex2
├── README.md
├── images
│ └── 01-RelationExplorer.png
└── sources
│ ├── ZDT187v_XX_Airline_Dim
│ ├── ZDT187v_XX_Airport_Dim
│ ├── ZDT187v_XX_Connection_Dim
│ └── ZDT187v_XX_Flight_Cube
└── ex3
├── README.MD
├── images
├── 01-MultiDimensionalPreview.png
└── 231018_Embedded-Analytics-for-TechEd_Ext.pdf
└── sources
└── ZDT187v_XX_Flight_Query
/.reuse/dep5:
--------------------------------------------------------------------------------
1 | Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
2 | Upstream-Name: teched2023-DT187v
3 | Upstream-Contact: ospo@sap.com
4 | Source: https://github.com/sap-samples/teched2023-DT187v
5 | Disclaimer: The code in this project may include calls to APIs (“API Calls”) of
6 | SAP or third-party products or services developed outside of this project
7 | (“External Products”).
8 | “APIs” means application programming interfaces, as well as their respective
9 | specifications and implementing code that allows software to communicate with
10 | other software.
11 | API Calls to External Products are not licensed under the open source license
12 | that governs this project. The use of such API Calls and related External
13 | Products are subject to applicable additional agreements with the relevant
14 | provider of the External Products. In no event shall the open source license
15 | that governs this project grant any rights in or to any External Products,or
16 | alter, expand or supersede any terms of the applicable additional agreements.
17 | If you have a valid license agreement with SAP for the use of a particular SAP
18 | External Product, then you may make use of any API Calls included in this
19 | project’s code for that SAP External Product, subject to the terms of such
20 | license agreement. If you do not have a valid license agreement for the use of
21 | a particular SAP External Product, then you may only make use of any API Calls
22 | in this project for that SAP External Product for your internal, non-productive
23 | and non-commercial test and evaluation of such API Calls. Nothing herein grants
24 | you any rights to use or access any SAP External Product, or provide any third
25 | parties the right to use of access any SAP External Product, through API Calls.
26 |
27 | Files: *
28 | Copyright: 2023 SAP SE or an SAP affiliate company and teched2023-DT187v contributors
29 | License: Apache-2.0
30 |
--------------------------------------------------------------------------------
/CONTRIBUTING.md:
--------------------------------------------------------------------------------
1 | # Contributing
2 |
3 | ## Code of Conduct
4 |
5 | All members of the project community must abide by the [SAP Open Source Code of Conduct](https://github.com/SAP/.github/blob/main/CODE_OF_CONDUCT.md).
6 | Only by respecting each other we can develop a productive, collaborative community.
7 | Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting [a project maintainer](.reuse/dep5).
8 |
9 | ## Engaging in Our Project
10 |
11 | We use GitHub to manage reviews of pull requests.
12 |
13 | * If you are a new contributor, see: [Steps to Contribute](#steps-to-contribute)
14 |
15 | * Before implementing your change, create an issue that describes the problem you would like to solve or the code that should be enhanced. Please note that you are willing to work on that issue.
16 |
17 | * The team will review the issue and decide whether it should be implemented as a pull request. In that case, they will assign the issue to you. If the team decides against picking up the issue, the team will post a comment with an explanation.
18 |
19 | ## Steps to Contribute
20 |
21 | Should you wish to work on an issue, please claim it first by commenting on the GitHub issue that you want to work on. This is to prevent duplicated efforts from other contributors on the same issue.
22 |
23 | If you have questions about one of the issues, please comment on them, and one of the maintainers will clarify.
24 |
25 | ## Contributing Code or Documentation
26 |
27 | You are welcome to contribute code in order to fix a bug or to implement a new feature that is logged as an issue.
28 |
29 | The following rule governs code contributions:
30 |
31 | * Contributions must be licensed under the [Apache 2.0 License](./LICENSE)
32 | * Due to legal reasons, contributors will be asked to accept a Developer Certificate of Origin (DCO) when they create the first pull request to this project. This happens in an automated fashion during the submission process. SAP uses [the standard DCO text of the Linux Foundation](https://developercertificate.org/).
33 |
34 | ## Issues and Planning
35 |
36 | * We use GitHub issues to track bugs and enhancement requests.
37 |
38 | * Please provide as much context as possible when you open an issue. The information you provide must be comprehensive enough to reproduce that issue for the assignee.
39 |
--------------------------------------------------------------------------------
/LICENSE:
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1 | Apache License
2 | Version 2.0, January 2004
3 | http://www.apache.org/licenses/
4 |
5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
6 |
7 | 1. Definitions.
8 |
9 | "License" shall mean the terms and conditions for use, reproduction,
10 | and distribution as defined by Sections 1 through 9 of this document.
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/README.md:
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1 | [](https://api.reuse.software/info/github.com/SAP-samples/teched2023-DT187v)
2 |
3 | # DT187v - Build Analytical Applications with ABAP Cloud
4 |
5 | ## Description
6 |
7 | This repository contains the material for the SAP TechEd 2023 session called DT187v - Build Analytical Applications with ABAP Cloud.
8 | Watch the recording of the [Jump-Start Session: Build Analytical Applications with ABAP Cloud](https://go3.events.sap.com/sapteched/virtual/2023/reg/flow/sap/sapteched23/catalog/page/catalog/session/1693019886304001sNN4) to get an introduction ([slides of the Jump-Start Session](/exercises/ex3/images/231018_Embedded-Analytics-for-TechEd_Ext.pdf)).
9 |
10 |
11 | ## Overview
12 |
13 | This hands-on tutorial introduces attendees to building an analytical data model with ABAP Cloud that can be consumed by analytical applications like e.g., SAP Analytics Cloud. You will learn how to build analytical applications with the ABAP Cloud programming language using ABAP core data services, analytical providers and business services in the ABAP development tools.
14 |
15 | Specifically, you will build an analytical application, that uses SAP's Flight Demo Model. You will design the data model and the application in order to analyze the occupation of flights from different perspectives.
16 |
17 | While building the data model, you will be introduced to analytical terms like measures, dimensions, cubes and queries as well as to the general idea of analytical data modelling with the star schema.
18 | Previewing the analytical application and exploring its features will deepen this understanding.
19 |
20 | ## Requirements
21 |
22 | Experience in ABAP, ABAP CDS and working with the Eclipse based ABAP Development Tools (ADT) is recommended, but not strictly necessary. If you are in a hurry or find it hard to follow the instructions, intermediate and final solutions of the exercises are available ready to be copied & pasted (with low naming adaption effort).
23 |
24 | The hard [prerequisites](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex0/README.md) to follow the exercises in this repository are that you:
25 | 1) get a new trial account for the BTP ABAP environment (please make sure to get a new one if your account is older than 2023-10-15)
26 | 2) have the latest version of the ABAP development tools installed
27 | 3) have downloaded and installed the templates for analytical CDS views
28 |
29 | ## Exercises
30 |
31 | - [Prerequisites](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex0/README.md)
32 | - [Get a SAP BTP Trial Account](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex0/README.md#sap-btp-trial-account)
33 | - [Get the BTP ABAP Environment Trial](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex0/README.md#abap-environment-in-sap-btp-trial)
34 | - [Install Analytical CDS Templates](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex0/README.md#download-and-install-analytical-abap-cds-templates)
35 |
36 | - [Exercise 1 - Introduction to Analytics in ABAP Cloud](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex1/README.md)
37 | - [Exercise 1.1 - Read: Scope of the Tutorial](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex1/README.md#exercise-11---read-scope-of-the-tutorial)
38 | - [Exercise 1.2 - Read: Embedded Analytics in ABAP Cloud](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex1/README.md#exercise-12---read-embedded-analytics-in-abap-cloud)
39 | - [Exercise 1.3 - Hands-On: Use the FLIGHT Data Model for Analytics](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex1/README.md#exercise-13---hands-on-use-the-flight-data-model-for-analytics)
40 | - [Exercise 1 - Summary](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex1/README.md#summary)
41 |
42 | - [Exercise 2 - Build a Cube with Dimensions](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md)
43 | - [Exercise 2.1 - Build the basic Cube](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md#exercise-21---build-the-basic-cube)
44 | - [Exercise 2.2 - Prepare the Measures](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md#exercise-22---prepare-the-measures)
45 | - [Exercise 2.3 - Prepare the Dimensions](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md#exercise-23---prepare-the-dimensions)
46 | - [Exercise 2.4 - Use the Dimensions](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md#exercise-24---use-the-dimensions)
47 | - [Exercise 2.5 - Optional - Add and use additional Dimensions](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md#exercise-25---optional-add-and-use-additional-dimensions)
48 | - [Exercise 2 - Summary](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex2/README.md#summary)
49 |
50 | - [Exercise 3 - Build the analytical Query](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex3/README.MD)
51 | - [Exercise 3.1 - Build the initial query](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex3/README.MD#exercise-31---build-the-initial-query)
52 | - [Exercise 3.2 - Prepare the Measures](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex3/README.MD#exercise-32---prepare-the-measures)
53 | - [Exercise 3.3 - Working Multi-Dimensional](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex3/README.MD#exercise-33---working-with-the-multi-dimensional-analysis)
54 | - [Exercise 3 - Summary](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex3/README.MD#summary)
55 |
56 |
57 | **IMPORTANT**
58 |
59 | ## Contributing
60 | Please read the [CONTRIBUTING.md](./CONTRIBUTING.md) to understand the contribution guidelines.
61 |
62 | ## Code of Conduct
63 | Please read the [SAP Open Source Code of Conduct](https://github.com/SAP-samples/.github/blob/main/CODE_OF_CONDUCT.md).
64 |
65 | ## How to obtain support
66 | Support for the content in this repository is available during the respective [Jump-Start Session: Build Analytical Applications with ABAP Cloud](https://go3.events.sap.com/sapteched/virtual/2023/reg/flow/sap/sapteched23/catalog/page/catalog/session/1693019886304001sNN4) at Friday, November 3, 2023, 7pm CET, for which this content has been designed.
67 | Otherwise, you may request support via the [Issues](../../issues) tab.
68 | A [SAP Help page for Embedded Analytics in ABAP Cloud](https://help.sap.com/docs/abap-cloud/abap-analytics/abap-analytics) is available as well.
69 |
70 | ## License
71 | Copyright (c) 2023 SAP SE or an SAP affiliate company. All rights reserved. This project is licensed under the Apache Software License, version 2.0 except as noted otherwise in the [LICENSE](LICENSES/Apache-2.0.txt) file.
72 |
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/exercises/ex0/README.md:
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1 | # Get Started
2 |
3 | In this exercise, you will create a trial user in the SAP BTP, ABAP Environment.
4 |
5 | ## SAP BTP Trial Account
6 |
7 | If you have not already done so you have first to register for the SAP BTP Trial [here](https://developers.sap.com/tutorials/abap-environment-trial-onboarding.html).
8 |
9 | ## ABAP Environment in SAP BTP Trial
10 |
11 | The steps to activate the ABAP Environment in the SAP BTP trial by creating an appropriate user are described in the following tutorial.
12 |
13 | If you already have an ABAP Environment Trial, please make sure to get a new one as the trial systgems have been updated for the TechEd 2023 sessions!
14 |
15 | [Create an SAP BTP ABAP Environment Trial User](https://developers.sap.com/tutorials/abap-environment-trial-onboarding.html)
16 |
17 | [Install ABAP Development Tools](https://developers.sap.com/tutorials/abap-install-adt.html)
18 |
19 | [Create ABAP Cloud Project](https://developers.sap.com/tutorials/abap-environment-create-abap-cloud-project.html)
20 |
21 | ## Download and install analytical ABAP CDS Templates
22 |
23 | As a first task we will start to import templates that we will use in this workshop to create Analytical CDS views such as dimension views, cubes and queries.
24 |
25 | **Step 1)** Click on the following link to display the file [analytical_templates.xml](https://github.com/SAP-samples/teched2023-DT187v/blob/main/exercises/ex0/sources/analytical_templates.xml)
26 | Then click the 'Download raw file'  button in the right upper corner to download **analytical_templates.xml**.
27 |
28 | Click to expand!
29 |
30 | 
31 |
32 |
33 |
34 | **Step 2)** In ABAP Development Tools, open the preferences and search for 'templates'.
35 |
36 | **Step 3)** In Data Definition Templates choose 'Import', then choose your file analytical_templates.xml.
37 | Click to expand!
38 |
39 | 
40 |
41 |
42 |
43 | ## Summary
44 |
45 | Now that you have onboarded to the SAP BTP Trial, ABAP Environment and saved the analytical CDS templates, you can continue to - [Exercise 1 - Introduction to Analytics in ABAP Cloud](../ex1/README.md)
46 |
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1 | @AccessControl.authorizationCheck: #CHECK
2 | @EndUserText.label: '${ddl_source_description}'
3 | @Metadata.ignorePropagatedAnnotations: true
4 | @Analytics.dataCategory: #CUBE
5 | @Analytics.internalName: #LOCAL
6 |
7 | define view entity ${ddl_source_name_editable} as select from ${data_source_name} {
8 | ${data_source_elements}${cursor}
9 | }
10 |
11 | @AccessControl.authorizationCheck: #CHECK
12 | @EndUserText.label: '${ddl_source_description}'
13 | @Metadata.ignorePropagatedAnnotations: true
14 | @Analytics.dataCategory: #DIMENSION
15 | @Analytics.internalName: #LOCAL
16 | @ObjectModel.representativeKey: '${representativeKey}'
17 |
18 | define view entity ${ddl_source_name_editable} as select from ${data_source_name} {
19 | @ObjectModel.text.element: ['${textElement}']
20 | ${data_source_elements}${cursor}
21 | }
22 |
23 | @AccessControl.authorizationCheck: #NOT_ALLOWED
24 | @EndUserText.label: '${ddl_source_description}'
25 |
26 | define transient view entity ${ddl_source_name_editable}
27 | provider contract analytical_query
28 | as projection on ${data_source_name} {
29 | //remove key attributes!
30 | ${data_source_elements}${cursor}
31 | }
32 |
33 |
34 |
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/exercises/ex1/README.md:
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1 | # Exercise 1 - Introduction to Analytics in ABAP Cloud
2 |
3 | In this exercise, you will understand what embedded analytics in ABAP Cloud is all about.
4 | Also, you will get to know the FLIGHT data model you will be working with.
5 |
6 | ## Prerequisites
7 |
8 | Make sure you have completed the prerequisites from [Exercise 0 - Get an ABAP Environment Trial](../ex0/README.md).
9 |
10 | Even if you already have an ABAP Environment Trial, **please get a new instance** as the trial systems have been updated for the TechEd 2023 sessions!
11 |
12 | ## Exercise 1.1 - Read: Scope of the Tutorial
13 |
14 | TL;DR [Skip the reading and start the hands-on](#exercise-13---hands-on-use-the-flight-data-model-for-analytics)
15 |
16 | What you will do in the course of this Hands-On session is focussed on the lower level of this diagram:
17 |
18 | 
19 |
20 | **ABAP CDS:** In this hands-on, you will mainly build an analytical data model on top of the transactional model that consists of a multi-dimensional cube view, according analytical dimension views as well as an analytical query that reads from the cube. You will enhance the model step by step wit additional features. This will introduce you to
21 | - basic analytical ideas and terms (measures & dimensions, cubes & queries)
22 | - analytical data modelling principles (the star schema)
23 | - the meaning of “multi-dimensional” analytics
24 |
25 | **INA SERVICE:** In contrary to the transactional-focussed OData protocol, the InA protocol is tailored to the needs of analytical applications, communicating with the analytical engine. The service exposure as such works in the same way as for transactional services and can theoretically also be done in the trial systems, but as we do not (yet) have multi-dimensional end-user clients
26 | available as part of the trial experience, the service exposure part is not needed in the hands-on.
27 | You may want to check the Tutorial [Develop and Consume Queries on SAP Analytics Cloud](https://developers.sap.com/tutorials/abap-environment-analytics.html) (starts with step 10) or the Devtoberfest 2023 Session [Introduction to Embedded Analytics in ABAP Cloud](https://www.youtube.com/watch?v=2dIqQNnYKjY&list=PLBoQ2iTAoalS9Urg3jcyVjGtxb15Gudfq) (starts at 28:30) on how to expose the query.
28 |
29 |
30 | **CLIENTS:** As there are no multi-dimensional analytical end user clients available in trial, we enabled the multi-dimensional Fiori preview on the query in the trial system. We will use this preview to visualise the model. It works in the same way as an analytical end user application. In the hands-on, you will start the preview and will be introduced to its features. This will deepen the understanding you gained during the modeling exercise.
31 | To see, how the SAC client would look like, you can also check the [Tutorial](https://developers.sap.com/tutorials/abap-environment-analytics.html) (starts with step 16) or the [Devtoberfest Session](https://www.youtube.com/watch?v=2dIqQNnYKjY&list=PLBoQ2iTAoalS9Urg3jcyVjGtxb15Gudfq) (around minute 38).
32 |
33 |
34 | ## Exercise 1.2 - Read: Embedded Analytics in ABAP Cloud
35 |
36 | TL;DR [Skip the reading and start the hands-on](#exercise-13---hands-on-use-the-flight-data-model-for-analytics)
37 |
38 | Let's understand how Analytics is ***embedded*** in ABAP Cloud.
39 |

40 | 1. SAP HANAs column store is vital for analytical data processing
41 | 2. Analytical data modelling is done ABAP Cloud style via ABAP CDS entities
42 | 3. Service Exposure via the multi-dimensional InA protocol is included in ABAP Cloud and so is the analytical engine, the according multi-dimensional runtime
43 | 5. The developer tooling needed for Analytics is included in the ABAP development tools
44 | 6. Analytical Fiori UIs that are part of ABAP Cloud are in preparation
45 | 7. SAP Analytics Cloud "SAC" can be used as client with multi-dimensional capabilities
46 |
47 | So everything that is needed to build real analytical applications end-to-end is ***embedded*** in the ABAP Cloud programming model as well as in every ABAP Cloud based system
48 |
49 |
50 | ## Exercise 1.3 - Hands-On: Use the FLIGHT Data Model for Analytics
51 |
52 | In the hands-on, we will use the SAP Flight Model. The mission will be to analyse the occupation rate of flights.
53 | After completing these steps you will have an understanding about how you can use the FLIGHT model as the basis for an analytical data model.
54 |
55 | **Step 1)** Open ABAP Development Tools and open your trial project.
56 |
57 | **Step 2)** Use the "Open Development Object" button to open the /DMO/I_Flight CDS View. Hint: How it looks like in ADT

58 |
59 | **Step 3)** Analytics is about measuring, so we first need to decide what to measure. This figure is called a ***measure*** in analytical terms. It has to be numerical. Typical measures are amounts or quantities, but can also be counts of something. Have a look at the "/DMO/I_Flight" CDS View, find suitable measures & note them down.
60 | Solution
61 |
62 | ```abap
63 | @AccessControl.authorizationCheck: #NOT_REQUIRED
64 | @EndUserText.label: 'Flight View - CDS Data Model'
65 | //...
66 |
67 | define view entity /DMO/I_Flight
68 | as select from /dmo/flight as Flight
69 |
70 | //...
71 | {
72 | //...
73 |
74 | /* A price is a typical measure */
75 | @Semantics.amount.currencyCode: 'CurrencyCode'
76 | Flight.price as Price,
77 |
78 | //...
79 |
80 | /* Maximum Seats and Occupied Seats are numerical and will help calculating the occupation rate */
81 | Flight.seats_max as MaximumSeats,
82 | Flight.seats_occupied as OccupiedSeats,
83 |
84 | //...
85 | }
86 | ```
87 |
88 |
89 | **Step 4)** We need to put measures into a perspective. This perspective is called ***dimension*** in analytical terms. Have a look at the "/DMO/I_Flight" CDS View, find suitable dimensions & note them down.
90 | Solution
91 |
92 | ```abap
93 | @AccessControl.authorizationCheck: #NOT_REQUIRED
94 | @EndUserText.label: 'Flight View - CDS Data Model'
95 | //...
96 |
97 | define view entity /DMO/I_Flight
98 | as select from /dmo/flight as Flight
99 |
100 | //...
101 | {
102 | //...
103 |
104 | /* Key Fields are always dimensions */
105 | key Flight.carrier_id as AirlineID,
106 |
107 | //...
108 | key Flight.connection_id as ConnectionID,
109 |
110 | //...
111 | key Flight.flight_date as FlightDate,
112 |
113 | //...
114 |
115 | /* Basically all fields that are no measures can be dimensions */
116 | Flight.plane_type_id as PlaneType,
117 |
118 | //...
119 | }
120 | ```
121 |
122 |
123 | ## Summary
124 |
125 | Now that you have analysed the FLIGHT data model, we know which elements are needed to start building our first analytical entity: The cube.
126 | Continue to - [Exercise 2 - Build a Cube](../ex2/README.md)
127 |
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1 | # Exercise 2 - Build a Cube with Dimensions
2 |
3 | In this exercise, we will create a cube. The cube is the heart of our analytical model. It draws together all required measures & dimensions and defines the functionality of the analytical model.
4 |
5 | The cube view is a `view entity` with the header annotation `@Analytics.dataCategory: #CUBE`.
6 | A dimension view is a `view entity` with the header annotation `@Analytics.dataCategory: #DIMENSION`.
7 |
8 | ## Exercise 2.1 - Build the Basic Cube
9 |
10 | **Step 1)** Create your own sub-package like "ZDT187v_[YourInitials]" underneath ZLOCAL
11 | - add it to your favorite packages
12 | - as transport request create "ZDT187v [YourInitials] Flight Hands-On"
13 |
14 | **Step 2)** Create a Cube View in your package.
15 | - Right-click the package and choose
16 | - New -> Other Repository Object -> Core Data Services -> Data Definition
17 | - Click "Next"
18 | - Enter the name "ZDT187v_[YourInitials]_Flight_Cube"
19 | - Give it the description "Flight Cube"
20 | - As Referenced Object, use "/DMO/I_FLIGHT"
21 | - Click "Next"
22 | - Use your request from Step 1
23 | - Click "Next"
24 | - Use the template "Define a View Entity for a Cube" (Prerequisite is that you downloaded and installed the templates)
25 | - Click "Finish"
26 |
27 | **Step 3)** As the annotation inheritance is switched off, you need to manually add the annotation `@Semantics.amount.currencyCode` with the reference to the according currency code field to the price field.
28 |
29 | **Step 4)** Press SHIFT+F1 to nicely format your sorce code, then activate the view.
30 | Activating your cube view will raise a warning that your cube does not have an access protection.
31 | Usually you would define an access protection, a so called 'DCL' for the cube. We do not cover this in this hands-on session and will ignore this warning.
32 |
33 | Hint: Your code should now look like this
34 |
35 | ```abap
36 |
37 | /* setting the value to #NOT_REQUIRED would remove the warning */
38 | @AccessControl.authorizationCheck: #CHECK
39 | @EndUserText.label: 'Flight Cube'
40 | /* Stopping annotation inheritance can help avoiding confusions */
41 | @Metadata.ignorePropagatedAnnotations: true
42 |
43 | /* This header annotation makes the view entity an analytical cube */
44 | @Analytics.dataCategory: #CUBE
45 | @Analytics.internalName: #LOCAL
46 |
47 | define view entity ZDT187v_[YourInitials]_Flight_Cube as select from /DMO/I_Flight {
48 | key AirlineID,
49 | key ConnectionID,
50 | key FlightDate,
51 |
52 | @Semantics.amount.currencyCode: 'CurrencyCode'
53 | Price,
54 |
55 | CurrencyCode,
56 | PlaneType,
57 | MaximumSeats,
58 | OccupiedSeats,
59 |
60 | /* Associations */
61 | _Airline,
62 | _Connection
63 | _Currency
64 | }
65 |
66 | ```
67 |
68 |
69 | **Step 5)** Now that you created your first analytical object in the ABAP Development Tools, right-click it in the project explorer, then choose 'Show in' -> 'Relation Explorer'. This perspective is an alternative view to the project explorer that is dedicated to analytical data models.
70 | The Relation Explorer
71 |
72 | 
73 |
74 |
75 |
76 | ## Exercise 2.2 - Prepare the Measures
77 |
78 | Measures in an analytical cube need to be prepared so that an aggregation can take place when querying. The analytical engine needs an aggregation type as well as the right units and currency codes for quantities and amounts.
79 |
80 | **Step 1)** Identify your measures, put them in a suitable order together between the dimensions and the associations.
81 |
82 | **Step 2)** Add the annotation `@Aggregation.default` with a suitabble value (either `#SUM`, `#MIN` or `#MAX`) to your measures.
83 |
84 | **Step 3)** Add an additional measure that will act as a counter for the flights.
85 | - The expression to be used for this is `cast (1 as abap.int4) as TotalFlights`
86 | - The cast makes sure that the resulting data type is able to count to 2.147.483.647 (without the cast it would have been 256 - a 2 byte integer)
87 | - Give it a suitable aggregation as well
88 |
89 | Hint: Your code should now look like this
90 |
91 | ```abap
92 |
93 | @EndUserText.label: 'Flight Cube'
94 | @Metadata.ignorePropagatedAnnotations: true
95 | @AccessControl.authorizationCheck: #NOT_REQUIRED
96 | @Analytics.dataCategory: #CUBE
97 |
98 | define view entity ZDT187v_[YourInitials]_Flight_Cube
99 | as select from /DMO/I_Flight
100 |
101 | {
102 | key AirlineID,
103 |
104 | key ConnectionID,
105 |
106 | key FlightDate,
107 |
108 | PlaneType,
109 |
110 | /* Measures */
111 |
112 | CurrencyCode,
113 | @Semantics.amount.currencyCode: 'CurrencyCode'
114 | @Aggregation.default: #MAX
115 | Price,
116 |
117 | @Aggregation.default: #SUM
118 | MaximumSeats,
119 |
120 | @Aggregation.default: #SUM
121 | OccupiedSeats,
122 |
123 | @Aggregation.default: #SUM
124 | cast (1 as abap.int4) as TotalFlights,
125 |
126 | /* Associations */
127 |
128 | _Airline,
129 | _Connection
130 | }
131 |
132 | ```
133 |
134 |
135 | ## Exercise 2.3 - Prepare the Dimensions
136 |
137 | The current dimension fields in the cube view are just IDs. In order to be displayed nicely with an according text and with the option to display additional attributes (e.g. the name and city of the airline or the distance or the departure airport of the connection), we need to reference the according dimension views as foreign key references to them. This can not only be done for the key fields of the cube view, but for all dimension fields.
138 |
139 | For the airline and the connection, we do already have associations that we took over from /DMO/I_Flight, but these lead to master data views that are not built for the usage as analytical dimensions. Therefore, we will have to replace them. We will also remove the association to the currency view as we don't want to use it.
140 |
141 | You will now create the needed dimension views.
142 |
143 | | Association Alias | Target | Dimension View |
144 | | --- | --- | --- |
145 | | _Airline | /dmo/carrier (table) | ZDT187v_[YourInitials]_Airline_Dim |
146 | | _Connection | /dmo/connection (table) | ZDT187v_[YourInitials]_Connection_Dim |
147 |
148 | **Step 1)** Create the dimension view for the Airline.
149 | - Proceed as described in 2.1, step 2 but use the template "Define a View Entity for a Dimension" instead
150 | - Naming and targets, see table above
151 |
152 | **Step 2)** Enter the representative key as value of the `@ObjectModel.representativeKey` annotation.
153 | The representative key is the most specific key of your key fields. In our case there is only one key field: CarrierId.
154 |
155 | **Step 3)** Enter the Name field as value of the `@ObjectModel.text.element` annotation.
156 | This will improve the usability of your analytical application as the airline name can now be displayed along with the airline id.
157 |
158 | **Step 4)** Press SHIFT+F1 to nicely format your sorce code. Then activate the view.
159 |
160 | Hint: Your ZDT187v_[YourInitials]_Airline_Dim code should now look like this
161 |
162 | ```abap
163 |
164 | @AccessControl.authorizationCheck: #CHECK
165 | @EndUserText.label: 'Carrier Dimension'
166 | @Metadata.ignorePropagatedAnnotations: true
167 | @Analytics.dataCategory: #DIMENSION
168 | @Analytics.internalName: #LOCAL
169 | @ObjectModel.representativeKey: 'CarrierId'
170 |
171 | define view entity ZDT187v_[YourInitials]_Airline_Dim
172 | as select from /dmo/carrier
173 | {
174 | @ObjectModel.text.element: ['Name']
175 | key carrier_id as CarrierId,
176 | @Semantics.text: true
177 | name as Name,
178 | currency_code as CurrencyCode,
179 | local_created_by as LocalCreatedBy,
180 | local_created_at as LocalCreatedAt,
181 | local_last_changed_by as LocalLastChangedBy,
182 | local_last_changed_at as LocalLastChangedAt,
183 | last_changed_at as LastChangedAt
184 | }
185 |
186 | ```
187 |
188 |
189 | **Step 5)** Now create the dimension view for the connection in the same way.
190 | - Set the representative Key to 'ConnectionId'.
191 |
192 | **Step 6)** Optional: Check the hint to see how a readable text 'Trip' was created and used as text element for the ConnectionId.
193 |
194 | Hint: Calculated text element
195 |
196 | ```abap
197 |
198 | //...
199 |
200 | @ObjectModel.text.element: ['Trip']
201 | key connection_id as ConnectionId,
202 |
203 | //...
204 | concat(airport_from_id, concat('->', airport_to_id)) as Trip,
205 |
206 | //...
207 |
208 | ```
209 |
210 |
211 | **Step 7)** Add an association to the Airline dimension that you created before and use it as foreign key association on the AirlineId.
212 | - `association [1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on $projection.CarrierId = _Airline.CarrierId`
213 | - `@ObjectModel.foreignKey.association: '_Airline'`
214 |
215 | **Step 8)** Press SHIFT+F1 to nicely format your sorce code. Then activate the view.
216 |
217 | Hint: Your ZDT187v_[YourInitials]_Connection_Dim code should now look like this
218 |
219 | ```abap
220 |
221 | @AccessControl.authorizationCheck: #NOT_REQUIRED
222 | @EndUserText.label: 'Connection Dimension'
223 | @Metadata.ignorePropagatedAnnotations: true
224 | @Analytics.dataCategory: #DIMENSION
225 | @Analytics.internalName: #LOCAL
226 | @ObjectModel.representativeKey: 'ConnectionId'
227 |
228 | define view entity ZDT187v_[YourInitials]_Connection_Dim
229 | as select from /dmo/connection
230 | association [1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on $projection.CarrierId = _Airline.CarrierId
231 | {
232 | @ObjectModel.foreignKey.association: '_Airline'
233 | key carrier_id as CarrierId,
234 | @ObjectModel.text.element: ['Trip']
235 | key connection_id as ConnectionId,
236 | airport_from_id as AirportFromId,
237 | airport_to_id as AirportToId,
238 | concat(airport_from_id, concat('->', airport_to_id)) as Trip,
239 | departure_time as DepartureTime,
240 | arrival_time as ArrivalTime,
241 | distance as Distance,
242 | distance_unit as DistanceUnit,
243 | _Airline
244 | }
245 |
246 | ```
247 |
248 |
249 | ## Exercise 2.4 - Use the Dimensions
250 |
251 | Back in your cube view, create associations to the dimension views, expose the associations so that they can finally be used as foreign key reference on your dimension fields.
252 |
253 | | Association Alias | Dimension View |
254 | | --- | --- |
255 | | _Airline | ZDT187v_[YourInitials]_Airline_Dim |
256 | | _Connection | ZDT187v_[YourInitials]_Connection_Dim |
257 | | _FlightDate | I_CalendarDate |
258 |
259 | **Step 1)** Add an association to the airline dimension you created in Exercise 2.2, Step 1 and expose it as _Airline.
260 |
261 | Hint: An association is defined right after the `select from` clause. For the airline dimension, it will look like this
262 |
263 | `association [0..1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on _Airline.CarrierId = $projection.AirlineID`
264 |
265 |
266 |
267 | **Step 2)** Add an association to the connection dimension that you created in Exercise 2.2, Step 2 in the same way. Expose it as _Connection.
268 | Hint: The association to the connection dimension will look like this
269 |
270 | `association [0..1] to ZDT187v_[YourInitials]_Connection_Dim as _Connection on _Connection.CarrierId = $projection.AirlineID and _Connection.ConnectionId = $projection.ConnectionID`
271 |
272 |
273 |
274 | **Step 3)** Add an association to the dimension I_CalendarDate in the same way. Expose it by adding its alias _FlightDate to the element list.
275 |
276 | Hint: The association to I_CalendarDate will look like this
277 |
278 | `association [0..1] to I_CalendarDate as _FlightDate on _FlightDate.CalendarDate = $projection.FlightDate`
279 |
280 |
281 |
282 | **Step 4)** Add the associations you just introduced as foreign key relations to your dimension key fields by using the annotation `@ObjectModel.foreignKey.association`. As value, choose the alias of the exposed association.
283 |
284 | **Step 5)** Press SHIFT+F1 to nicely format your sorce code. Then activate the view.
285 |
286 | Hint: Your cube code should now look like this
287 |
288 | ```abap
289 |
290 | @EndUserText.label: 'Flight Cube'
291 | @Metadata.ignorePropagatedAnnotations: true
292 | @AccessControl.authorizationCheck: #NOT_REQUIRED
293 | @Analytics.dataCategory: #CUBE
294 |
295 | define view entity ZDT187v_[YourInitials]_Flight_Cube
296 | as select from /DMO/I_Flight
297 | association [0..1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on _Airline.CarrierId = $projection.AirlineID
298 | association [0..1] to ZDT187v_[YourInitials]_Connection_Dim as _Connection on _Connection.CarrierId = $projection.AirlineID
299 | and _Connection.ConnectionId = $projection.ConnectionID
300 | association [0..1] to I_CalendarDate as _FlightDate on _FlightDate.CalendarDate = $projection.FlightDate
301 |
302 | {
303 | @ObjectModel.foreignKey.association: '_Airline'
304 | key AirlineID,
305 |
306 | @ObjectModel.foreignKey.association: '_Connection'
307 | key ConnectionID,
308 |
309 | @ObjectModel.foreignKey.association: '_FlightDate'
310 | key FlightDate,
311 |
312 | PlaneType,
313 |
314 | /* Measures */
315 |
316 | CurrencyCode,
317 |
318 | @Semantics.amount.currencyCode: 'CurrencyCode'
319 | @Aggregation.default: #MAX
320 | Price,
321 |
322 | @Aggregation.default: #SUM
323 | MaximumSeats,
324 |
325 | @Aggregation.default: #SUM
326 | OccupiedSeats,
327 |
328 | @Aggregation.default: #SUM
329 | cast (1 as abap.int4) as TotalFlights,
330 |
331 | /* Associations for Dimensions */
332 |
333 | _Airline,
334 | _Connection,
335 | _FlightDate
336 | }
337 |
338 | ```
339 |
340 |
341 | ## Exercise 2.5 - Optional: Add and use additional Dimensions
342 |
343 | The cube that we have prepared now is ready to be used, but we want to add some additional functionality to it in terms of dimensions that we later can aggregate by.
344 | Even though we have added dimension views that give us access to additional display attributes like the departure or arrival airport of the destination or the month and quarter of the flight date, we would not be able to use these attributes as criteria to aggregate by. Every field that we want to use as aggregation criteria later on has to be an element of the cube view.
345 | Therefore, we will now use the associations to the dimensions to add those fields directly to the cube.
346 |
347 | If you are in a hurry, continue to - [Exercise 3 - Build a Cube ](../ex3/README.md) as the optional exercise will take some time.
348 |
349 |
350 | **Step 1)** Optional: Use the _Connection association to add target and destiantion airport as dimensions
351 |
352 | Hint
353 |
354 | ```abap
355 |
356 | define view entity ZDT187v_[YourInitials]_Flights_Cube
357 | //...
358 | {
359 | //...
360 | _Connection.AirportFromId,
361 | _Connection.AirportToId,
362 | /...
363 | }
364 |
365 | ```
366 |
367 |
368 | **Step 2)** Optional: Create an additional dimension view ZDT187v_[YourInitials]_Airport_Dim.
369 | - Proceed as described in Exercise 2.1, Step 2
370 | - choose /dmo/airport as the referenced data source
371 | - use the template "Define a View Entity for a Dimension"
372 | - fill in the representative key and text element
373 | - Press SHIFT+F1 to nicely format your sorce code. Then activate the view
374 |
375 | Hint: Your ZDT187v_[YourInitials]_Airport_Dim code should now look like this
376 |
377 | ```abap
378 |
379 | @AccessControl.authorizationCheck: #CHECK
380 | @EndUserText.label: 'Airport Dimension'
381 | @Metadata.ignorePropagatedAnnotations: true
382 | @Analytics.internalName: #LOCAL
383 | @Analytics.dataCategory: #DIMENSION
384 | @ObjectModel.representativeKey: 'AirportId'
385 |
386 | define view entity ZDT187v_[YourInitials]_Airport_Dim
387 | as select from /dmo/airport
388 | {
389 | @ObjectModel.text.element: ['Name']
390 | key airport_id as AirportId,
391 | name as Name,
392 | city as City,
393 | country as Country
394 | }
395 |
396 | ```
397 |
398 |
399 | **Step 3)** Optional: Use the new dimension view in your cube.
400 | - Add two associations to the new dimension in your cube view
401 | - one for the origin airport `as _AirportFrom`
402 | - another one for the destination airport `as _AirportTo`
403 | - expose both
404 | - and use them as foreign key reference for the AirportFrom and the AirportTo field
405 |
406 | Hint
407 |
408 | ```abap
409 |
410 | define view entity ZDT187v_[YourInitials]_Flights_Cube
411 | //...
412 | association [0..1] to ZDT187v_[YourInitials]_Airport_Dim as _AirportFrom on _AirportFrom.AirportId = $projection.AirportFromId
413 | association [0..1] to ZDT187v_[YourInitials]_Airport_Dim as _AirportTo on _AirportTo.AirportId = $projection.AirportToId
414 | {
415 | //...
416 | @ObjectModel.foreignKey.association: '_AirportFrom'
417 | _Connection.AirportFromId,
418 |
419 | @ObjectModel.foreignKey.association: '_AirportTo'
420 | _Connection.AirportToId,
421 |
422 | /...
423 | _AirportFrom,
424 | _AirportTo,
425 | /...
426 | }
427 |
428 | ```
429 |
430 |
431 |
432 | **Step 4)** Optional: Sometimes, dimensions can also include measures. To be able to analyse and aggregate them, they need to be part of the cube as well.
433 | Use the _Connection association to add the flight distance together with the distance unit as additional measure.
434 | - As the distance is an amount with a unit, you need to add `@Semantics.quantity.unitOfMeasure: 'DistanceUnit'` to it
435 | - as well as a suitable aggregation, e.g. `@Aggregation.default: #MAX`
436 |
437 | Hint
438 |
439 | ```abap
440 |
441 | define view entity ZDT187v_[YourInitials]_Flights_Cube
442 | //...
443 | {
444 | //...
445 | _Connection.DistanceUnit,
446 |
447 | @Semantics.quantity.unitOfMeasure: 'DistanceUnit'
448 | @Aggregation.default: #MAX
449 | _Connection.Distance,
450 |
451 | /...
452 | }
453 |
454 | ```
455 |
456 |
457 |
458 | **Step 5)** Optional: Use the _FlightDate association to add the flight quarter as well as the flight year as dimensions.
459 | - Add a label e.g. `@EndUserText.label: 'Flight Year'` to the field to give it a readable name
460 | - Explain the analytical engine that the field is a calendar year by setting `@Semantics.calendar.year: true`
461 | This will enable additional display attributes in the UI later on.
462 | - Finally set the fields in relation to the Flight Date with `@ObjectModel.value.derivedFrom: [ 'FlightDate' ]`
463 | This is again a hint for the analytical engine and is especially important if multiple dates are in your model.
464 |
465 | Hint
466 |
467 | ```abap
468 |
469 | define view entity ZDT187v_[YourInitials]_Flights_Cube
470 | //...
471 | {
472 | //...
473 | @EndUserText.label: 'Flight Quarter'
474 | @Semantics.calendar.yearQuarter: true
475 | @ObjectModel.value.derivedFrom: [ 'FlightDate' ]
476 | _FlightDate.YearQuarter,
477 |
478 | @EndUserText.label: 'Flight Year'
479 | @Semantics.calendar.year: true
480 | @ObjectModel.value.derivedFrom: [ 'FlightDate' ]
481 | _FlightDate.CalendarYear,
482 | /...
483 | }
484 |
485 | ```
486 |
487 |
488 | **Step 6)** Press SHIFT+F1 to nicely format your sorce code. Then activate the view.
489 |
490 | ## Summary
491 |
492 | You have now learned what measures and dimensions are and how to build an analytical cube view. The cube is the center of the analytical data model and the so called star schema.
493 | The cube defines the capabilities of your analytical model and draws together all measures and dimensions. Every dimension that you later want to aggregate by needs to be part of the cube view.
494 | Calculations that have to happen before the aggregation (like the counter that you introduced) have to happen in the cube as well.
495 |
496 | Hint: Your final cube view should now look like this
497 |
498 | ```abap
499 |
500 | @AccessControl.authorizationCheck: #CHECK
501 | @EndUserText.label: 'Flight Cube'
502 | @Metadata.ignorePropagatedAnnotations: true
503 | @Analytics.dataCategory: #CUBE
504 | @Analytics.internalName: #LOCAL
505 |
506 | define view entity ZDT187v_[YourInitials]_Flights_Cube
507 | as select from /DMO/I_Flight
508 | association [0..1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on _Airline.CarrierId = $projection.AirlineID
509 | association [0..1] to ZDT187v_[YourInitials]_Connection_Dim as _Connection on _Connection.CarrierId = $projection.AirlineID
510 | and _Connection.ConnectionId = $projection.ConnectionID
511 | association [0..1] to I_CalendarDate as _FlightDate on _FlightDate.CalendarDate = $projection.FlightDate
512 | /* start optional associations */
513 | association [0..1] to ZDT187v_[YourInitials]_Airport_Dim as _AirportFrom on _AirportFrom.AirportId = $projection.AirportFromId
514 | association [0..1] to ZDT187v_[YourInitials]_Airport_Dimn as _AirportTo on _AirportTo.AirportId = $projection.AirportToId
515 | /* end optional associations */
516 | {
517 | @ObjectModel.foreignKey.association: '_Airline'
518 | key AirlineID,
519 |
520 | @ObjectModel.foreignKey.association: '_Connection'
521 | key ConnectionID,
522 |
523 | @ObjectModel.foreignKey.association: '_FlightDate'
524 | key FlightDate,
525 |
526 | PlaneType,
527 |
528 | /* start optional dimensions */
529 | @ObjectModel.foreignKey.association: '_AirportFrom'
530 | _Connection.AirportFromId,
531 |
532 | @ObjectModel.foreignKey.association: '_AirportTo'
533 | _Connection.AirportToId,
534 |
535 | @EndUserText.label: 'Flight Quarter'
536 | @Semantics.calendar.yearQuarter: true
537 | @ObjectModel.value.derivedFrom: [ 'FlightDate' ]
538 | _FlightDate.YearQuarter,
539 |
540 | @EndUserText.label: 'Flight Year'
541 | @Semantics.calendar.year: true
542 | @ObjectModel.value.derivedFrom: [ 'FlightDate' ]
543 | _FlightDate.CalendarYear,
544 | /* end optional dimensions */
545 |
546 | /* Measures */
547 |
548 | CurrencyCode,
549 |
550 | @Semantics.amount.currencyCode: 'CurrencyCode'
551 | @Aggregation.default: #MAX
552 | Price,
553 |
554 | @Aggregation.default: #SUM
555 | MaximumSeats,
556 |
557 | @Aggregation.default: #SUM
558 | OccupiedSeats,
559 |
560 | @Aggregation.default: #SUM
561 | cast (1 as abap.int4) as TotalFlights,
562 |
563 | _Connection.DistanceUnit,
564 |
565 | /* start optional measure */
566 | @Semantics.quantity.unitOfMeasure: 'DistanceUnit'
567 | @Aggregation.default: #MAX
568 | _Connection.Distance,
569 | /* end optional measure */
570 |
571 |
572 | /* Associations for Dimensions */
573 |
574 | _Airline,
575 | _Connection,
576 |
577 | /* start optional associations */
578 | _AirportFrom,
579 | _AirportTo,
580 | _FlightDate
581 | /* end optional associations */
582 | }
583 |
584 | ```
585 |
586 |
587 | Continue to - [Exercise 3 - Build a Query ](../ex3/README.MD)
588 |
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/exercises/ex2/images/01-RelationExplorer.png:
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https://raw.githubusercontent.com/SAP-samples/teched2023-DT187v/e35519c03f0aaa8f8330e215079b1645d8145a5d/exercises/ex2/images/01-RelationExplorer.png
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/exercises/ex2/sources/ZDT187v_XX_Airline_Dim:
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1 | @AccessControl.authorizationCheck: #CHECK
2 | @EndUserText.label: 'Carrier Dimension'
3 | @Metadata.ignorePropagatedAnnotations: true
4 | @Analytics.dataCategory: #DIMENSION
5 | @Analytics.internalName: #LOCAL
6 | @ObjectModel.representativeKey: 'CarrierId'
7 |
8 | define view entity ZDT187v_[YourInitials]_Airline_Dim
9 | as select from /dmo/carrier
10 | {
11 | @ObjectModel.text.element: ['Name']
12 | key carrier_id as CarrierId,
13 | @Semantics.text: true
14 | name as Name,
15 | currency_code as CurrencyCode,
16 | local_created_by as LocalCreatedBy,
17 | local_created_at as LocalCreatedAt,
18 | local_last_changed_by as LocalLastChangedBy,
19 | local_last_changed_at as LocalLastChangedAt,
20 | last_changed_at as LastChangedAt
21 | }
22 |
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/exercises/ex2/sources/ZDT187v_XX_Airport_Dim:
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1 | @AccessControl.authorizationCheck: #CHECK
2 | @EndUserText.label: 'Airport Dimension'
3 | @Metadata.ignorePropagatedAnnotations: true
4 | @Analytics.internalName: #LOCAL
5 | @Analytics.dataCategory: #DIMENSION
6 | @ObjectModel.representativeKey: 'AirportId'
7 |
8 | define view entity ZDT187v_[YourInitials]_Airport_Dim
9 | as select from /dmo/airport
10 | {
11 | @ObjectModel.text.element: ['Name']
12 | key airport_id as AirportId,
13 | name as Name,
14 | city as City,
15 | country as Country
16 | }
17 |
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/exercises/ex2/sources/ZDT187v_XX_Connection_Dim:
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1 | @AccessControl.authorizationCheck: #CHECK
2 | @EndUserText.label: 'Connection Dimension'
3 | @Metadata.ignorePropagatedAnnotations: true
4 | @Analytics.dataCategory: #DIMENSION
5 | @Analytics.internalName: #LOCAL
6 | @ObjectModel.representativeKey: 'ConnectionId'
7 |
8 | define view entity ZDT187v_[YourInitials]_Connection_Dim
9 | as select from /dmo/connection
10 | association [1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on $projection.CarrierId = _Airline.CarrierId
11 | {
12 | @ObjectModel.foreignKey.association: '_Airline'
13 | key carrier_id as CarrierId,
14 | @ObjectModel.text.element: ['Trip']
15 | key connection_id as ConnectionId,
16 | airport_from_id as AirportFromId,
17 | airport_to_id as AirportToId,
18 | concat(airport_from_id, concat('->', airport_to_id)) as Trip,
19 | departure_time as DepartureTime,
20 | arrival_time as ArrivalTime,
21 | distance as Distance,
22 | distance_unit as DistanceUnit,
23 | _Airline
24 | }
25 |
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/exercises/ex2/sources/ZDT187v_XX_Flight_Cube:
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1 | @AccessControl.authorizationCheck: #CHECK
2 | @EndUserText.label: 'Flight Cube'
3 | @Metadata.ignorePropagatedAnnotations: true
4 | @Analytics.dataCategory: #CUBE
5 | @Analytics.internalName: #LOCAL
6 |
7 | define view entity ZDT187v_[YourInitials]_Flight_Cube
8 | as select from /DMO/I_Flight
9 | association [0..1] to ZDT187v_[YourInitials]_Airline_Dim as _Airline on _Airline.CarrierId = $projection.AirlineID
10 | association [0..1] to ZDT187v_[YourInitials]_Connection_Dim as _Connection on _Connection.CarrierId = $projection.AirlineID
11 | and _Connection.ConnectionId = $projection.ConnectionID
12 | association [0..1] to I_CalendarDate as _FlightDate on _FlightDate.CalendarDate = $projection.FlightDate
13 | /* start optional associations */
14 | association [0..1] to ZDT187v_[YourInitials]_Airport_Dim as _AirportFrom on _AirportFrom.AirportId = $projection.AirportFromId
15 | association [0..1] to ZDT187v_[YourInitials]_Airport_Dim as _AirportTo on _AirportTo.AirportId = $projection.AirportToId
16 | /* end optional associations */
17 | {
18 | @ObjectModel.foreignKey.association: '_Airline'
19 | key AirlineID,
20 |
21 | @ObjectModel.foreignKey.association: '_Connection'
22 | key ConnectionID,
23 |
24 | @ObjectModel.foreignKey.association: '_FlightDate'
25 | key FlightDate,
26 |
27 | PlaneType,
28 |
29 | /* start optional dimensions */
30 | @ObjectModel.foreignKey.association: '_AirportFrom'
31 | _Connection.AirportFromId,
32 |
33 | @ObjectModel.foreignKey.association: '_AirportTo'
34 | _Connection.AirportToId,
35 |
36 | @EndUserText.label: 'Flight Quarter'
37 | @Semantics.calendar.yearQuarter: true
38 | @ObjectModel.value.derivedFrom: [ 'FlightDate' ]
39 | _FlightDate.YearQuarter,
40 |
41 | @EndUserText.label: 'Flight Year'
42 | @Semantics.calendar.year: true
43 | @ObjectModel.value.derivedFrom: [ 'FlightDate' ]
44 | _FlightDate.CalendarYear,
45 | /* end optional dimensions */
46 |
47 | /* Measures */
48 |
49 | CurrencyCode,
50 |
51 | @Semantics.amount.currencyCode: 'CurrencyCode'
52 | @Aggregation.default: #MAX
53 | Price,
54 |
55 | @Aggregation.default: #SUM
56 | MaximumSeats,
57 |
58 | @Aggregation.default: #SUM
59 | OccupiedSeats,
60 |
61 | @Aggregation.default: #SUM
62 | cast (1 as abap.int4) as TotalFlights,
63 |
64 | _Connection.DistanceUnit,
65 |
66 | /* start optional measure */
67 | @Semantics.quantity.unitOfMeasure: 'DistanceUnit'
68 | @Aggregation.default: #MAX
69 | _Connection.Distance,
70 | /* end optional measure */
71 |
72 |
73 | /* Associations for Dimensions */
74 |
75 | _Airline,
76 | _Connection,
77 |
78 | /* start optional associations */
79 | _AirportFrom,
80 | _AirportTo,
81 | _FlightDate
82 | /* end optional associations */
83 | }
84 |
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/exercises/ex3/README.MD:
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1 | # Exercise 3 - Build an analytical Query
2 |
3 | Now that we have built the analytical ***cube*** that defines the capabilities of our analytical model, lets formulate a ***query*** to that model.
4 | The query defines more or less the initial layout of the table (the table is kind of a pivot table) that will be displayed in your analytical application.
5 |
6 | The analytical query view is a `transient view entity` with the `provider contract analytical_query`.
7 |
8 | ## Exercise 3.1 - Build the initial Query
9 |
10 | **Step 1)** Create a Query View in your package.
11 | - Right-click the package and choose
12 | - New -> Other Repository Object -> Core Data Services -> Data Definition
13 | - Click "Next"
14 | - Enter the name "ZDT187v_[YourInitials]_Flight_Query"
15 | - Give it the description "Flight Query"
16 | - As Referenced Object, use "ZDT187v_[YourInitials]_Flight_Cube"
17 | - Click "Next"
18 | - Use your request "ZDT187v [YourInitials] Flight Hands-On"
19 | - Click "Next"
20 | - Use the template "Define a View Entity for a Query" (Prerequisite is that you downloaded and installed the templates)
21 | - Click "Finish"
22 |
23 | **Step 2)** Fix the errors by removing the 'key' keyword. A query does not need them. Unfortunately this cannot be noted in templates.
24 |
25 | Hint: Your code should now look like this
26 |
27 | ```abap
28 |
29 | @AccessControl.authorizationCheck: #NOT_ALLOWED
30 | @EndUserText.label: 'Flight Query'
31 |
32 | define transient view entity ZDT187v_[YourInitials]_Flight_Query
33 | provider contract analytical_query
34 | as projection on ZDT187v_[YourInitials]_Flight_Cube {
35 | AirlineID,
36 | ConnectionID,
37 | FlightDate,
38 | PlaneType,
39 | AirportFromId,
40 | AirportToId,
41 | YearQuarter,
42 | CalendarYear,
43 | Price,
44 | CurrencyCode,
45 | MaximumSeats,
46 | OccupiedSeats,
47 | TotalFlights,
48 | DistanceUnit,
49 | Distance,
50 | /* Associations */
51 | _Airline,
52 | _AirportFrom,
53 | _AirportTo,
54 | _Connection,
55 | _FlightDate
56 | }
57 |
58 | ```
59 |
60 |
61 | **Step 3)** Define the layout by assigning the axis as well as the existence of totals for the dimension.
62 | For the axis, the annotation `@AnalyticsDetails.query.axis` is used.
63 | For the totals, we use `@AnalyticsDetails.query.totals`.
64 | In a standard layout, dimensions are on the row axis and the measures are on the column axis.
65 | If you assign a dimension to a different axis or remove it, the measures will be aggregated according to the layout.
66 | Example: If you have the price in the columns and only add the airline to the rows (either by removing other dimensions or by assigning them to the `#FREE` axis), then the maximum price of all flights that are conducted by the airline will be the result of the aggregation (assuming the default aggregation of the price is set to `#MAX`).
67 |
68 | Hint: See how it looks like
69 |
70 | ```abap
71 |
72 | /* You can freely decide if you write the annotations either in a flat or on object style */
73 |
74 | /* Object Style */
75 | @AnalyticsDetails.query: {
76 | axis: #ROWS,
77 | totals: #HIDE
78 | }
79 | AirlineID
80 |
81 | /* Flat Style */
82 | @AnalyticsDetails.query.axis: #ROWS
83 | @AnalyticsDetails.query.totals: #HIDE
84 | AirlineID
85 |
86 | ```
87 |
88 |
89 |
90 | ## Exercise 3.2 - Prepare the Measures
91 |
92 | Generally, all measures will always be (in a group) on the same axis. If you do not assign an axis at all, they will be on the column axis by default.
93 | If you assign different axes to the measures, the first one will win. For readability reasons, we will add the axis annotations to all measures here.
94 |
95 | **Step 1)** Add the `@AnalyticsDetails.query.axis: #COLUMNS` annotation to all measures.
96 |
97 | **Step 2)** Add a new (calculated) measure to the query by calculating the occupation rate as a percentage using the MaximumSeats and OccupiedSeats fields.
98 | Remember: Measures that need to be calculated after the aggregation have to be part of the query.
99 |
100 | Hint: See how it looks like
101 |
102 | ```abap
103 |
104 | /* label for a better user experience */
105 | @EndUserText.label: 'Occupation Rate'
106 | /* as the aggrregation is set already for the fields that are used in the calculation, we leave it up to the engine to decide for our formula */
107 | @Aggregation.default: #FORMULA
108 | /* the calculation formula */
109 | $projection.occupiedseats / $projection.maximumseats * 100 as OccupationRate,
110 |
111 | ```
112 |
113 |
114 | **Step 3)** Optional: To indicate, that the occupation rate is a percentage, add an according unit to it.
115 | This will need introducing the unit as a field & then referencing it from the calculated field.
116 |
117 | Hint: See how it looks like
118 |
119 | ```abap
120 |
121 | /* introduce the unit */
122 | cast( '%' as abap.unit ) as unitPercent,
123 | /...
124 | /* reference the new unit */
125 | @Semantics.quantity.unitOfMeasure: 'unitPercent'
126 | $projection.occupiedseats / $projection.maximumseats * 100 as OccupationRate,
127 |
128 | ```
129 |
130 |
131 | **Step 4)** Introduce a currency conversion for the price.
132 | As the price is listed in different currencies, it has to be converted so that it can be aggregated.
133 |
134 | Hint: Currency Conversion
135 |
136 | ```abap
137 |
138 | @AnalyticsDetails.query.axis: #COLUMNS
139 | @Semantics.amount.currencyCode: 'CurrencyCode'
140 | @Aggregation.default: #FORMULA
141 | currency_conversion (
142 | amount => curr_to_decfloat_amount( Price ),
143 | source_currency => CurrencyCode,
144 | target_currency => cast ( 'EUR' as abap.cuky( 5 ) ) ,
145 | exchange_rate_date => cast ( '20230101' as abap.dats),
146 | exchange_rate_type => 'M'
147 | ) as Price,
148 |
149 | ```
150 |
151 |
152 | **Step 5)** Introduce a virtual unit for the price.
153 | In case the price cannot be converted e.g. due to missing conversion rates, this has to be considered by displaying the original currency and amount instead of the target currency.
154 |
155 | Hint: Virtual unit
156 |
157 | ```abap
158 |
159 | virtual GlobalCurrency : abap.cuky( 5 ),
160 | /...
161 | @Semantics.amount.currencyCode: 'GlobalCurrency'
162 | /...
163 | currency_conversion (
164 | /...
165 | ) as Price,
166 |
167 | ```
168 |
169 |
170 | **Step 6)** Format & activate your analytical query view.
171 |
172 | Hint: Your query should now look like this
173 |
174 | ```abap
175 |
176 | @AccessControl.authorizationCheck: #NOT_ALLOWED
177 | @EndUserText.label: 'Flight Query'
178 |
179 | define transient view entity ZDT187v_[YourInitials]_Flight_Query
180 | provider contract analytical_query
181 | as projection on ZDT187v_[YourInitials]_Flight_Cube
182 | {
183 | /* Dimensions */
184 |
185 | @AnalyticsDetails.query.axis: #ROWS
186 | @AnalyticsDetails.query.totals: #HIDE
187 | AirlineID,
188 |
189 | @AnalyticsDetails.query.axis: #ROWS
190 | @AnalyticsDetails.query.totals: #HIDE
191 | ConnectionID,
192 |
193 | @AnalyticsDetails.query.axis: #ROWS
194 | @AnalyticsDetails.query.totals: #HIDE
195 | FlightDate,
196 |
197 | @AnalyticsDetails.query.axis: #FREE
198 | @AnalyticsDetails.query.totals: #HIDE
199 | PlaneType,
200 |
201 | @AnalyticsDetails.query.axis: #ROWS
202 | @AnalyticsDetails.query.totals: #SHOW
203 | AirportFromId,
204 |
205 | @AnalyticsDetails.query.axis: #FREE
206 | @AnalyticsDetails.query.totals: #HIDE
207 | AirportToId,
208 |
209 | @AnalyticsDetails.query.axis: #FREE
210 | @AnalyticsDetails.query.totals: #HIDE
211 | YearQuarter,
212 |
213 | @AnalyticsDetails.query.axis: #FREE
214 | @AnalyticsDetails.query.totals: #SHOW
215 | CalendarYear,
216 |
217 | /* Measures */
218 |
219 | @AnalyticsDetails.query.axis: #COLUMNS
220 | @Semantics.amount.currencyCode: 'GlobalCurrency'
221 | @Aggregation.default: #FORMULA
222 | currency_conversion (
223 | amount => curr_to_decfloat_amount( Price ),
224 | source_currency => CurrencyCode,
225 | target_currency => cast ( 'EUR' as abap.cuky( 5 ) ) ,
226 | exchange_rate_date => cast ( '20230101' as abap.dats),
227 | exchange_rate_type => 'M'
228 | ) as Price,
229 | virtual GlobalCurrency : abap.cuky( 5 ),
230 | CurrencyCode,
231 |
232 | @AnalyticsDetails.query.axis: #COLUMNS
233 | MaximumSeats,
234 |
235 | @AnalyticsDetails.query.axis: #COLUMNS
236 | OccupiedSeats,
237 |
238 | @AnalyticsDetails.query.axis: #COLUMNS
239 | @EndUserText.label: 'Occupation Rate'
240 | @Aggregation.default: #FORMULA
241 | @Semantics.quantity.unitOfMeasure: 'unitPercent'
242 | $projection.occupiedseats / $projection.maximumseats * 100 as OccupationRate,
243 | cast( '%' as abap.unit ) as unitPercent,
244 |
245 | @AnalyticsDetails.query.axis: #COLUMNS
246 | TotalFlights,
247 |
248 | @AnalyticsDetails.query.axis: #COLUMNS
249 | Distance,
250 | DistanceUnit,
251 |
252 | /* Associations */
253 | _Airline,
254 | _AirportFrom,
255 | _AirportTo,
256 | _Connection,
257 | _FlightDate
258 | }
259 |
260 | ```
261 |
262 |
263 | **Step 7)** Preview the query by right-clicking the query in the explorer and selecting 'Preview'.
264 | Be patient. It's just a free trial system ;-)
265 |
266 | ## Exercise 3.3 - Working with the Multi-Dimensional Analysis
267 |
268 | **Step 1)** Preview the query with the multi-dimensional analysis.
269 | To make use of the new multi-dimensional analysis based preview that we introduced to the trial systems, proceed as follows:
270 | - the preview for analytical queries opens in the browser
271 | - in case of an error, press F5 to reload
272 | - you may need to press 'go' to run the query
273 | - check if the result of the layout that you defined in the query meets your expectations
274 |
275 |

276 |
277 | **Step 2)** Try changing the layout in the app directly:
278 | - Open the layout side pannel (second icon from top in the right side bar)
279 | - Remove all attributes except the Airline from the rows
280 | - Remove all measures except for the occupation rate from the measures structure
281 | - Move the Departure Airport to the Columns
282 | - etc.
283 |
284 | **Step 3)** Try changing the display properties:
285 | - Right click the Departure Airport in the UI
286 | - Select Dimension -> Properties
287 | - Switch the Desciption on
288 | - Display Totals
289 | - Change the sorting
290 | - etc.
291 |
292 | **Step 4)** Add display attributes:
293 | - In the sidebar, expand the Flight Date and
294 | - select Calendar Quarter
295 |
296 | **Step 5)** Observe the currency conversion behaviour:
297 | - Notice the blue warning on the top left of the table
298 | - Click it and see that conversion rates are missing
299 | - Expand the measure structure and de-select all measures except for the price
300 | - Empty the rows an only take the Flight Date into the rows
301 | - See that some prices cannot be aggregated as they contain different currencies and no conversion is available
302 | These issues are indicated with an '*'. Some dates have flights only in one currency. They will be displayed.
303 | - Now exchange the Flight Date with the airline and see that the aggregation happens without conversion in the local currency.
304 |
305 | **Step 6)** Play ;-)
306 |
307 | **Step 7)** Also try modifying the layout in the query view and observe the results in the UI (re-publish, re-load)
308 |
309 |
310 | ## Summary
311 |
312 | You now got to know common analytical modelling practices and learned the most important analytical terms.
313 | You have an impression on what 'multi-dimensional' analytics means and how analytical UIs behave.
314 |
315 | ### What's next?
316 |
317 | You are ready to learn more about embedded analytics for example in:
318 | - The [SAP Help on ABAP Cloud Analytics](https://help.sap.com/docs/abap-cloud/abap-analytics/abap-analytics)
319 | - The [Embedded Analytics Overview - Blog Post](https://blogs.sap.com/2022/11/30/embedded-analytics-with-abap-cloud-a-brief-overview-part-1/) by [Fabian Fellhauer](https://people.sap.com/fabianfellhauer)
320 |
321 | Take a look at the [ABAP Platform Analytical Modeling Examples](https://github.com/SAP-samples/abap-platform-analytics-data-modeling) repository. It contains a complete analytical model based on the flight reference scenario as well as loads of additional analytical queries that showcase different features of Embedded Analytics in the ABAP Platform.
322 |
323 | Further links can be found in the [Jump-Start Session slides](/exercises/ex3/images/231018_Embedded-Analytics-for-TechEd_Ext.pdf).
324 |
325 | Feel free to use this tutorial as a basis and explore further modeling practices within the trial system. What about e.g. implementing a hierarchy?
326 |
327 | You may also want to check the transactional side of the story? Then head to the session [Use ABAP Cloud for developer extensibility](https://github.com/SAP-samples/teched2023-DT182v) from [Andrè Fischer](https://people.sap.com/andre.fischer).
328 |
329 | The [slides of the Jump-Start Session](/exercises/ex3/images/231018_Embedded-Analytics-for-TechEd_Ext.pdf) are available in this GitHub repository as well.
330 |
331 |
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/exercises/ex3/sources/ZDT187v_XX_Flight_Query:
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1 | @AccessControl.authorizationCheck: #NOT_ALLOWED
2 | @EndUserText.label: 'Flight Query'
3 |
4 | define transient view entity ZDT187v_[YourInitials]_Flight_Query
5 | provider contract analytical_query
6 | as projection on ZDT187v_[YourInitials]_Flight_Cube
7 | {
8 | /* Dimensions */
9 |
10 | @AnalyticsDetails.query.axis: #ROWS
11 | @AnalyticsDetails.query.totals: #HIDE
12 | AirlineID,
13 |
14 | @AnalyticsDetails.query.axis: #ROWS
15 | @AnalyticsDetails.query.totals: #HIDE
16 | ConnectionID,
17 |
18 | @AnalyticsDetails.query.axis: #ROWS
19 | @AnalyticsDetails.query.totals: #HIDE
20 | FlightDate,
21 |
22 | @AnalyticsDetails.query.axis: #FREE
23 | @AnalyticsDetails.query.totals: #HIDE
24 | PlaneType,
25 |
26 | @AnalyticsDetails.query.axis: #ROWS
27 | @AnalyticsDetails.query.totals: #SHOW
28 | AirportFromId,
29 |
30 | @AnalyticsDetails.query.axis: #FREE
31 | @AnalyticsDetails.query.totals: #HIDE
32 | AirportToId,
33 |
34 | @AnalyticsDetails.query.axis: #FREE
35 | @AnalyticsDetails.query.totals: #HIDE
36 | YearQuarter,
37 |
38 | @AnalyticsDetails.query.axis: #FREE
39 | @AnalyticsDetails.query.totals: #SHOW
40 | CalendarYear,
41 |
42 | /* Measures */
43 |
44 | @AnalyticsDetails.query.axis: #COLUMNS
45 | @Semantics.amount.currencyCode: 'GlobalCurrency'
46 | @Aggregation.default: #FORMULA
47 | currency_conversion (
48 | amount => curr_to_decfloat_amount( Price ),
49 | source_currency => CurrencyCode,
50 | target_currency => cast ( 'EUR' as abap.cuky( 5 ) ) ,
51 | exchange_rate_date => cast ( '20230101' as abap.dats),
52 | exchange_rate_type => 'M'
53 | ) as Price,
54 | virtual GlobalCurrency : abap.cuky( 5 ),
55 | CurrencyCode,
56 |
57 | @AnalyticsDetails.query.axis: #COLUMNS
58 | MaximumSeats,
59 |
60 | @AnalyticsDetails.query.axis: #COLUMNS
61 | OccupiedSeats,
62 |
63 | @AnalyticsDetails.query.axis: #COLUMNS
64 | @EndUserText.label: 'Occupation Rate'
65 | @Aggregation.default: #FORMULA
66 | @Semantics.quantity.unitOfMeasure: 'unitPercent'
67 | $projection.occupiedseats / $projection.maximumseats * 100 as OccupationRate,
68 | cast( '%' as abap.unit ) as unitPercent,
69 |
70 | @AnalyticsDetails.query.axis: #COLUMNS
71 | TotalFlights,
72 |
73 | @AnalyticsDetails.query.axis: #COLUMNS
74 | Distance,
75 | DistanceUnit,
76 |
77 | /* Associations */
78 | _Airline,
79 | _AirportFrom,
80 | _AirportTo,
81 | _Connection,
82 | _FlightDate
83 | }
84 |
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