This chapter explains how to develop an Automation Model using the GUI Editor, where logic corresponding to a service is visually represented as a graphical diagram. Additionally, it covers how to develop automation models using various services that collect and process data.

The development process for an X-UP Model consists of the following steps

1. Develop the model using the X-UP Builder.

2. Test the developed model in the X-UP Builder.

3. Deploy the model to the X-UP Server using the deploy function in the X-UP Builder.

4. Test the deployed model using the X-UP Test Web Page.

In an Automation Model, data is acquired from a data source using an Invoke function.

Invoke can process data in modular units, and multiple Invokes can be combined to build a model.

This chapter covers the following topics.

• Developing a model using SAP RFC Invoke

• Developing a model using Select Invoke

• Developing a model using Modify Invoke

• Developing a model using Procedure Invoke

• Developing a model using OpenAPI Invoke

• Developing a model using X-UP Invoke

• Developing a model using Visual COBOL Invoke

• Processing data using DataSet Row Loop Function

• Processing data using Merge Function

• Processing data using Quick Merge Function

• Processing data using XML Parser Function

Developing a Model Using SAP RFC Invoke

This section explains the process of developing a model using SAP RFC Function in Automation Model.

The SAP RFC Invoke development steps in the Automation Model are as follows.

• Create an X-UP Project

• Create an Automation Model and SAP RFC Invoke

• Create a Data Source and Configure Properties

• Test the Invoke

• Test the Model

Creating an X-UP Project

1. Open the New X-UP Project Wizard by selecting [File > New > X-UP Project] from the menu.

2. In the New X-UP Project Wizard, enter the desired project name in the Project name field and click the Finish button.

3. Verify that the X-UP project has been created in the X-UP Explorer as shown below.

Creating an Automation Model and Generating an SAP RFC Invoke

1. Select [File > New > X-UP Automation Model] to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the OK button.

3. After completing the New Model Wizard, the following screen will appear.

4. From the Palette, select SAP RFC under Invoke and click on the editor to generate the SAP RFC Invoke.

Creating a Data Source and Configuring Properties

1. Double-click the created SAP RFC Invoke(1) or click the ‘Properties’ tab and then click the ‘SAP RFC icon’[ ](2) to launch the wizard.

2. In the Invoke SAP RFC Wizard, click create new DataSource []

3. On the New DataSource page, define a new data source. Enter the required values in each field and click the Test Connection button to verify the connection.

4. After confirming the connection, click the Finish button.

5. Select SAP RFC as the DataSource, then click the Get Function List button [] to retrieve the list of functions registered on the server.

6. Use wildcard (*) search to find functions within the group.

7. Select(1) the desired function from the retrieved function list, then review (2) the function’s input parameters and output parameters.

8. The SAP RFC parameters will be converted into X-UP parameters (3).

9. Click the Test button(4)to open the Define Input Value Wizard, configure input parameter values, and click the Finish button to verify the output data.

10. Click OK to confirm that the input and output parameters have been successfully created.

Invoke 테스트하기

1. This is the created SAP RFC Invoke. Based on the test results of the Invoke, the input parameters and output parameters will be generated.

2. Select the InvokeInfo of the SAP RFC Invoke in the Properties and click [ ] 를 클릭하여 테스트를 진행합니다.

3. When the "Define Input Value" wizard appears, input the test values you set during the Properties configuration and click the Finish button.

4. If the test is successfully completed, you can check the results in the Test Result.

Testing the Model

1. When you right-click in the model editor, a popup menu will appear. From the popup menu, select Test to test the model.

2. Once the test is complete, the output of the model will be shown in the Result ParameterSet view.

1. Click the Test button to display the results in the Result ParameterSet.

Select Invoke를 이용한 모델 개발하기

이 절에서는 Automation 모델을 이용하여 데이터베이스로부터 Select 쿼리로 데이터를 획득하는 개발방법에 대하여 설명합니다.

이 절에서 설명하는 Automation 모델의 Select Invoke 개발단계는 다음과 같습니다.

• X-UP 프로젝트 생성하기

• Automation 모델을 생성 및 Select Invoke 생성하기

• 입력 파라메터 설정 및 Properties 설정하기(SQL 변경)

• Invoke 테스트하기

• 모델 테스트하기

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and Select Invoke

1. Select the [File > New > X-UP Automation Model] menu to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click OK.

3. Once the New Model Wizard is completed, the screen below will appear.

4. In the X-UP DataSource view on the right side of the screen, select new DataSource to run the Wizard.

5. In the New DataSource wizard, define the new data source. Enter the required values in each field and click the Test Connection button to verify the connection to the DataSource.

6. After confirming the connection, click the Finish button.

7. In the X-UP DataSource view, select the DataSource []and retrieve the table list.

8. From the retrieved table list, select the ADDRESS_BOOK table and drag and drop it into the editor.

9. Choose Select Invoke from either Select Invoke or Modify Invoke to create a Select Invoke.

10. Alternatively, you can select Select Invoke from the Palette and click the editor to create the Select Invoke.

11. The generated Select Invoke will have a DataSet as the output parameter by default.

12. The generated SQL query will be a Select SQL that retrieves all columns without a WHERE clause.

Setting Input Parameters and Properties (SQL Modification)

In this step, the input parameters are defined and the properties necessary to retrieve data from the data source are configured.

1. Select the DataSet from the Palette (1)and click the editor(2)to create the dataset.

2. The default name for the created dataset is ‘dataset + index.’ Change the name and alias to IN_DS(3)

3. Connect the modified dataset to the Select Invoke(2) using Connect(1) from the Palette

4. Once connected, the dataset icon will turn blue and will be required as input parameters.

5. In the Properties tab, under the ‘InOut’ section, you can confirm that it has been changed to ‘in’(3)

6. The dataset output is renamed to OUT_DS, with the alias and name modified, and set to ‘out’.

7. Select the IN_DS dataset, go to Properties, and choose ‘Schema’ to add an ID and define the data type.

8. Double-click the Select Invoke to automatically modify the generated SQL. In this example, the ID from IN_DS is used as an input variable to query the ADDRESS_BOOK table. If the ID is not null, only the record with the provided ID will be queried.

$r_title(Before modification)
 select 
	ID,
	NAME,
	COMPANY,
	EMAIL,
	PHONE,
	BIRTHDAY,
	NOTES
 from MIMASHUP.ADDRESS_BOOK

$r_title(After modification)
select 
	ID,
	NAME,
	COMPANY,
	EMAIL,
	PHONE,
	BIRTHDAY,
	NOTES
from ADDRESS_BOOK
<dynamic prepend="where">
	<isNotNull property="IN_DS.ID">
		ID = #IN_DS.ID#
	</isNotNull>
</dynamic>

Invoke 테스트하기

1. Click the preview button[] at the top right of the SQL view shown in the Properties InvokeInfo of the Select Invoke. In the Define Test Value window, add a row, input ‘5’, and click the ‘Finish’ button.

2. The test results will be displayed in the Result ParameterSet view.

Model Testing

1. Right-click in the model editor to open the popup menu. Select "Test" from the menu to test the model.

2. After the test is complete, the model's output will be shown in the Result ParameterSet view.

3. At the bottom of the Result ParameterSet view, there are tabs for Parameters and DataSets. You can confirm that a dataset named ‘OUT_DS’ exists as the output parameter.

Developing a Model Using Modify Invoke

This section explains the development method for modifying data in a database using an Automation model.

The development steps for the Modify Invoke Automation model described in this section are as follows.

• Create an X-UP project

• Create an Automation model and Select Invoke

• Set input parameters and configure properties

• Test the Invoke

• Test the model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and Modify Invoke

1. Select [File > New > X-UP Automation Model] to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the OK button.

3. After completing the New Model Wizard, the screen below will appear.

4. 화면 우측의 X-UP DataSource 뷰에서 new DataSource를 선택해 Wizard를 실행합니다.

5. New DataSource 위자드에서 새로운 데이터소스를 정의합니다. 아래와 같이 각 필드 값을 입력한 후 ‘Test Connection’버튼을 선택하여 DataSource와 연결이 정상적으로 맺어지는지 확인합니다.

6. Connection 확인 후에 ‘Finish’ 버튼을 클릭합니다.

7. In the X-UP DataSource view, select the DataSource[]to retrieve the table list.

8. From the retrieved table list, select the 'ADDRESS_BOOK' table and drag-and-drop it into the editor.

9. From either Select Invoke or Modify Invoke, choose Modify Invoke to generate the Modify Invoke.

10. Alternatively, you can select Modify Invoke from the Palette's Invoke section and click the editor to create the Modify Invoke.fy Invoke를 생성할 수 있습니다.

11. Upon creating Modify Invoke, a wizard will appear, allowing you to select the initial columns.

12. Click the 'Select All' button and then click the 'OK' button. The generated Modify Invoke will, by default, have an input dataset and output dataset as parameters.

Configuring Input Parameters and Setting Properties

1. Click the input dataset and select 'General' under Properties to change the name and alias to 'IN_DS'.

2. If Modify Invoke was created in the left Palette, manually create the input parameters (as shown in image 1 below) and specify the schema for the input parameter 'IN_DS'. Click the Import button (as shown in image 3 below).

3. For dataset column settings, click the 'Add' button[] to manually enter the columns or click the 'Import' button to retrieve column information from the database table, another X-UP model, or an XML file.

4. In the Import Dataset Schema wizard, select the schema of the 'ADDRESS_BOOK' table from the 'DB_ORACLE' data source.

5. After changing the name of the input dataset, double-click Modify Invoke. In the Invoke Modify SQL popup, the Target DataSet combo box will display the types of datasets in the input parameters. Here, select 'IN_DS'. You will see that the Insert/Update/Delete queries are automatically populated.

Invoke Testing

1. Click the preview button[] on the top-right corner of the SQL view in the Modify Invoke's Properties InvokeInfo to start the test.

2. When the Define Input Value wizard is generated, input the data to be used for the Modify Invoke test.

3. Click the Add button[] to enter the data.

4. After entering the data, click the Finish button.

The Action field for transaction processing of the entered row is explained below.

5. After the test is successfully completed, the result can be viewed in the Result ParameterSet view.

Model Testing

Developing a Model Using Procedure Invoke

This section explains how to develop a model that calls a database procedure or function using an Automation model.

The steps for developing an Automation model using Procedure Invoke are as follows.

• Create an X-UP Project

• Create an Automation Model and Procedure Invoke

• Test the Invoke

• Test the Model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and Procedure Invoke

1. Select [File > New > X-UP Automation Model] from the menu to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the OK button.

3. After completing the New Model Wizard, the screen shown below will appear.

4. 화면 우측의 X-UP DataSource 뷰에서 new DataSource를 선택해 Wizard를 실행합니다.

5. New DataSource 위자드에서 새로운 데이터소스를 정의합니다. 아래와 같이 각 필드 값을 입력한 후 ‘Test Connection’버튼을 선택하여 DataSource와 연결이 정상적으로 맺어지는지 확인합니다.

6. Connection 확인 후에 ‘Finish’ 버튼을 클릭합니다.

7. In the X-UP DataSource view, select a DataSource [](1) to retrieve the list of Procedures and Functions.

8. From the retrieved procedure list, select the desired procedure and drag it to the editor(2).

9. Alternatively, you can select Procedure Invoke (3) from the Palette's Invoke section and click the editor to create the Procedure Invoke

10. In the wizard that appears, click the Test button.

11. Enter the values in the Define Input Value section and click the Finish button.

12. You can verify the output values after the procedure has been invoked.

13. Click the OK button to complete the configuration of the input and output parameters for the Procedure Invoke.

Invoke Testing

1. The created Procedure Invoke will generate input and output parameters based on the test results.

2. In the Properties of the Procedure Invoke, select InvokeInfo and click [ ] to begin the test

3. When performing the test, enter the same values as when you clicked the Test button during the creation of the Procedure Invoke in "Create Automation Model and Procedure Invoke," and you will be able to check the results.

4. After a successful test, you can view the results in the Result ParameterSet view.

Model Testing

Developing a Model Using OpenApi Invoke

This section explains how to develop an OpenApi model using Apple Inc.'s Apple Store services.

Apple Store provides lists of new releases and popular rankings by category. The data is provided in an XML-based RSS format. X-UP Builder collects XML-formatted data and creates structured parameters.

The steps for developing an OpenApi model using OpenApi Invoke in this section are as follows.

• Create an X-UP Project

• Create an Automation Model and OpenApi Invoke

• Create Data Source and Configure Properties

• Test the Invoke

• Test the Model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and OpenApi Invoke

1. Select [File > New > X-UP Automation Model] menu to run the New Model Wizard

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the OK button.

3. After completing the New Model Wizard, the screen will appear as shown below.

4. From the Palette, select OpenApi under the Invoke section and click on the editor to create the OpenApi Invoke.

Creating a Data Source and Configuring Properties

1. Double-click the created OpenApi Invoke(1) or click the InvokingInfo tab in the ‘Prooperties’ view(2) and click the ‘OpenApi icon’[ ](3) to launch the wizard.

2. In the wizard, click Create new DataSource []

3. On the New DataSource page, define the new data source. After entering the field values as shown below, click the Test Connection button to check if the DataSource connection is established properly.

4. After confirming the connection, click the Finish button.

5. From the defined data source, select ‘OPENAPI_APPLE’.

6. Enter the appropriate Sub Path for the Base Path, then click the Test button. Example of the Sub Path: ‘topfreeapplications/limit=10/xml’.

7. If the service is successfully called, you will see the BODY and the actual HTTP Header response values as shown below.

8. When you click the OK button, you will see that the values verified during the test have been set as output parameters.

Invoke Testing

1. The OpenApi Invoke has been created. Based on the test results of the Invoke, input and output parameters are generated.

2. Remove the unused HTTP header response values.

3. Select the ‘InvokeInfo’(2) tab in the Properties of the OpenApi Invoke(1) and click [](3) to begin the test.

4. Once the test is successfully completed, the results can be viewed in the Result ParameterSet view. (In this example, if there are no input parameters, the output will be shown directly.)

Model Testing

Developing a Model Using X-UP Invoke

This section explains the process of using the Automation model to call an X-UP model deployed on a web application server.

The development steps for the X-UP Invoke in the Automation model described in this section are as follows.

• Create an X-UP Project

• Create an Automation Model and X-UP Invoke

• Create Data Source and Set Properties

• Test the Invoke

• Test the Model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and X-UP Invoke

1. Select the [File > New > X-UP Automation Model] menu to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the Finish button.

3. After the New Model Wizard is completed, the following screen will appear.

4. From the Palette, select X-UP under the Invoke section, and click the editor to create the X-UP Invoke.

5. To configure the created X-UP Invoke, either double-click it (1)or click the Properties tab and select the X-UP icon [ ](2) to launch the wizard.

Creating a DataSource and Configuring Properties

1. In the X-UP Model List Wizard, click create new DataSource [].

2. In the New DataSource Wizard, define the new data source by filling in the fields as shown below. Afterward, click the Test Connection button to ensure that the connection to the data source is established correctly.

3. After confirming the connection, click the Finish button.

Ensure that the data source is properly set to XUP_REMOTE.

4. After clicking OK, you can confirm that the input and output parameters have been created.

Invoke Testing

1. Select ‘InvokeInfo’ in the Properties of the X-UP Invoke and click[] to perform the test.

2. Once the test is successfully completed, you can check the results in the Result ParameterSet view.

Model Testing

Processing Data Using the DataSet Row Loop Function

This section explains the DataSet Row Loop Function, which allows for executing business logic repetitively for each row in a dataset.

The example provided utilizes SAP RFC Invoke to retrieve a FLIGHT LIST and processes it into a new dataset by filtering data based on specific conditions.

Development Steps Using the DataSetRowLoop Function.

• Create an X-UP Project

• Create an Automation Model

• Implement SAP RFC logic for input parameters

• Create a DataSetRowLoop function and add an event

• Use the UserMethod Function to define output parameters

• Test the Function

• Test the Model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model

1. Run the New Model Wizard by selecting [File > New > X-UP Automation Model].

2. In the New Model Wizard, enter the desired Model Name in the corresponding field and click OK.

3. After completing the New Model Wizard, the following screen will appear.

Implementing SAP RFC Logic for Input Parameters

1. In the Palette, select "SAP RFC" under Invoke and click on the editor to create an SAP RFC Invoke.

1. 생성 된 SAP RFC Invoke를(1) 더블클릭 하거나 ‘Properties’ 탭을 클릭하여 ‘SAP RFC icon’[ ](2)을 클릭하면 위자드가 실행 됩니다.

2. Invoke SAP RFC 위자드에서 create new DataSource []를 클릭합니다.

3. New DataSource 페이지에서 새로운 데이터소스를 정의합니다. 아래와 같이 각 필드 값을 입력한 후 ‘Test Connection’ 버튼을 선택하여 DataSource와 연결이 정상적으로 맺어지는지 확인합니다.

4. Connection 확인 후에 ‘Finish’ 버튼을 클릭합니다.

5. DataSource를 SAP RFC을 선택하고 get function list 버튼 [] 을 클릭하여 서버에 등록된 Function 리스트를 호출 합니다.

6. 그룹(function) 검색 시 * 검색이 가능 합니다.

7. 검색된 function 리스트 중 호출하고자 하는 function을 선택(1) 하면 해당 function의 입력 파라메터와 출력 파라메터의 정보를 확인(2) 할 수 있습니다.

8. 동시에 SAP RFC 파라메터 형태를 X-UP Parameter 형태(3)로 나타납니다.

9. Test 버튼(4)을 클릭하여 생성된 Define Input Value 위자드의 입력 파라메터의 값을 설정하고 ‘Finish’ 버튼을 클릭하여 정상적으로 데이터가 표시되는지 확인합니다.

10. OK 버튼을 클릭할 경우 입력 파라메터와 출력 파라메터가 생성된 것을 확인할 수 있습니다.

Creating and Adding Events to the DataSetRowLoop Function

1. In the Palette, select 'DataSetRowLoop' from the Function category and click on the editor to create a DataSetRowLoop function.

2. Use the Connect tool(1) to link the output parameter ‘FLIGHT_LIST1’ from the SAP RFC Invoke to the input parameter(2) of the DataSetRowLoop function.

3. Right-click on the DataSetRowLoop function, select "Add Event", and choose "loopEvent" to add an event.

Setting Output Parameters Using the UserMethod Function

4. Use Connect to link the automatically generated rowIndex and dataset parameters from the event's output to the input parameters of the UserMethod function.

5. To define the output parameter, select DataSet from the Palette, add it(1), and link it to the UserMethod function's output parameter(2).

6. Rename the newly created dataset to 'FILTERED_FLIGHT_LIST'.(3)

7. Modify the schema of FILTERED_FLIGHT_LIST as shown below.

8. Double-click the UserMethod function, navigate to the automatically generated logic class, enter the following source code, and save it.

public void userMethod(ParameterSet globalParameterSet, EuserMethodParameters eps) throws AutomationFailException {
	DataSet filteredDataSet = globalParameterSet.getDataSet("FILTERED_FLIGHT_LIST");

	DataSet dataset = eps.getDataSet();
	int month = (dataset.getDateTime(0, "FLIGHTDATE").getMonth());
	// data filter
	if(month == 4) {
		int row = filteredDataSet.newRow();
		filteredDataSet .set(row, "AIRLINE", dataset.getString(0, "AIRLINE"));
		filteredDataSet .set(row, "CONNECTID", dataset.getInt(0, "CONNECTID"));
		filteredDataSet .set(row, "FLIGHTDATE", dataset.getString(0, "FLIGHTDATE"));
	}
}

Model Testing

1. Use the Palette’s "Connect" tool to link the Start node with the SAP RFC Invoke, DataSetRowLoop function, and the End node.

2. Right-click anywhere in the Model Editor, and a popup menu will appear. Select "Test" from the menu to execute the model test.

Using the Quick Merge Function for Data Processing

This section explains the Quick Merge function, which fuses two datasets obtained from multiple Invoke or Function operations to create a new dataset.

Development Steps for Using Quick Merge Function

• Create an X-UP Project

• Create an Automation Model and Quick Merge Function

• Generate Datasets to be Merged

• Configure the Merge Logic

• Test the Function

• Test the Model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and Quick Merge Function

1. Select [File > New > X-UP Automation Model] from the menu to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the Finish button.

3. After the New Model Wizard is complete, the following screen will appear.

4. From the Palette, select the 'Quick Merge' function, then click on the editor to generate the Quick Merge function.

융합 할 데이터셋 생성하기

1. 화면 Palette에서 ‘DataSet’을 선택 하여 에디터를 클릭 합니다.

2. 생성된 데이터셋의 기본 명칭은 ‘dataset’ 입니다. 이름과 Alias를 DS_BOOK 으로 변경합니다.

3. Properties의 Schema에서 []를 클릭하여 Column 정보를 다음과 같이 추가 합니다.

4. DS_BOOK과 Merge 함수를 Palette의 Connect를 이용하여 연결합니다.

5. 위와 같은 방법으로 DataSet 하나를 더 생성하여 이름과 Alias를 DS_AUTHOR로 변경합니다.

6. Properties의 Schema에서 []를 클릭하여 Column 정보를 다음과 같이 추가합니다.

7. DS_AUTHOR와 Merge 함수를 Palette의 Connect를 이용하여 연결합니다.

Configuring Merge Logic

1. Double-click the Quick Merge function(1) in the editor, or click the 'Properties' tab and select the 'Quick Merge icon'[](2) to launch the wizard.

2. The two input datasets are automatically configured, with the 'Key Column' field set to 'book_name' for DS_BOOK and 'work' for DS_AUTHOR. Other fields are left with their default settings.

3. Click the Test button in the Quick Merge Wizard to test the merge logic.

4. Enter the following values in the Define Input Value wizard and click the Finish button.

Function Testing

1. Based on the test results, output parameters will be generated.

2. Select the ‘InvokeInfo’ in the Properties of the Quick Merge function and click[] to start the test.

3. When you enter the values and run the test, as in the 'Merge Logic Settings' section where the Test button in the wizard is selected, you will be able to see the results.

4. If the test is completed successfully, you can view the results in the Result ParameterSet view.

Invoke Testing

Data Processing Using the Merge Function

This section explains how to merge datasets obtained from multiple models to create a new dataset using the Merge function.

The steps involved in developing a merge model are as follows.

• Create an X-UP project

• Create an Automation model and the Merge function

• Create datasets to be merged

• Configure the merge logic

• Test the merge function

• Test the model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and the Merge Function

1. Select the [File > New > X-UP Automation Model] menu to launch the New Model Wizard.

2. In the New Model Wizard, enter the model name in the Model Name field and click the 'Finish' button.

3. Once the New Model Wizard is completed, the following screen will appear.

4. Select 'Merge' from the Palette’s Functions, and click on the editor to create the Merge function.

Creating Datasets to Be Merged

1. From the Palette screen, select 'DataSet' and click on the editor.

2. The default name of the created dataset is ‘dataset’. Change the name and alias to ‘DS_BOOK’.

3. In the Properties panel, click [] under Schema and add the column information as shown.

4. Use Palette's Connect to link DS_BOOK and the Merge function.

5. Create another dataset in the same way, and change the name and alias to ‘DS_AUTHOR’.

6. In the Properties panel, click[] under Schema and add the column information as shown.

7. Use Palette's Connect to link DS_AUTHOR and the Merge function.

Setting Up the Merge Logic

1. Double-click the Merge function in the editor(1) or click the 'Properties' tab and click the 'Merge icon'[ ](2) to launch the wizard.

2. Click ‘Create Default Merging SQL’ to generate the basic merge logic in the SQL editor.

3. Modify the merge logic in the SQL editor as shown below.

$r_title(Before modification)
select 
	a.id,
	a.book_name,
	a.author,
	b.no,
	b.name,
	b.work
from
DS_BOOK a, DS_AUTHOR b

$r_title(After modification)
select 
	a.id,
	a.book_name,
	a.author,
	b.no,
	b.name,
	b.work
from
DS_BOOK a, DS_AUTHOR b
where a.book_name = b.work

4. Click the Test button in the SQL editor to test the merge logic.

5. Enter the following values in Define Input Value and click the ‘Finish’ button.

Function Testing

1. Based on the test results, output parameters are generated.

2. Select 'InvokeInfo' in the Merge function's Properties and click[] to initiate the test.

3. Similar to the test conducted in the 'Set Up Merge Logic' section, enter the same values in the SQL editor when clicking the Test button and proceed with the test to verify the results.

4. Once the test is successfully completed, you can check the results in the Result ParameterSet view.

Model Testing

Using the XML Parser Function for Data Processing

This section explains how to use the XML Parser Function to easily convert XML-formatted data into dataset formats or primitive types.

The XML used in the example is the Sample XML Required for Using XML Parser Function.

The development steps for the Automation model using the XML Parser in this section are as follows.

• Create an X-UP Project

• Create an Automation Model and the XML Parser

• Define XML Parsing Rules

• Test the Function

• Test the Model

X-UP 프로젝트 생성하기

1. [File > New > X-UP Project] 메뉴를 선택하여 New X-UP Project Wizard를 실행합니다.

2. New X-UP Project Wizard에서 Project name 필드에 원하는 프로젝트 이름을 입력하고 ‘Finish’ 버튼을 클릭합니다.

3. X-UP Explorer에 아래와 같이 X-UP 프로젝트가 생성된 것을 확인합니다.

Creating an Automation Model and XML Parser Function

1. Select the [File > New > X-UP Automation Model] menu to run the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click OK.

3. After the New Model Wizard is completed, the following screen will appear.

4. From the Palette under Function, select ‘XML Parser’, and click the editor to create the XML Parser function.

Defining the XML Parsing Rules

1. Double-click the XML Parser(1) or click on the ‘Properties’ tab, then click the ‘ParserInfo’ and select the ‘XML Parser icon’[ ](2) to launch the XML Parser Wizard.

2. Copy the XML data from the Sample XML Required for Using XML Parser Function for input data.

3. Paste the XML string into the ‘XML Content’ area of the XML Parser Wizard.

4. The XML content will appear, and by clicking pretty view, it will display in a more readable format.

5. The ‘Parser Info’ section at the bottom will show the XML in a tree structure.

6. To parse the data, select the repeating ‘PLANT’(1) node in ParseInfo and drag(2) it into the Parse List.

7. Additionally, click the Add button[](3) at the top left of the ‘Parse List’ to create a new entry.

8. Once added to the Parse List, the ‘XPath’, ‘Const column’, ‘Condition’, and ‘Option’ (4) tabs in Parse Info will be activated.

9. The selected node will automatically be assigned to XPath, and its child nodes will be included. This information will be converted into a dataset.

10. Click the ‘Test’ button(1) to preview the result in the ‘Preview’ section(2).

11. After clicking OK, an output parameter dataset named ‘PLANT’ will be created.

12. The schema of the dataset will be formed based on the names of the child nodes corresponding to the XPath.

Function Testing

1. Select 'ParserInfo' in the XML Parser's Properties and click[] to start the test.

2. The 'Define Input Value' wizard will automatically input the XML used to define the parsing rules.

3. Click the 'Finish' button.

4. Once the test completes successfully, you can check the results in the Result ParameterSet view.

Model Testing

Developing a Model Using Visual Cobol Invoke

This section explains how to develop a model using Visual Cobol Invoke.

The steps for developing an Automation model using Visual Cobol Invoke are as follows.

• Create an X-UP Project

• Create an Automation Model and Visual Cobol Invoke

• Create a Data Source and Configure Properties

• Test the Invoke

• Test the Model

Creating an X-UP Project

1. Select [File > New > X-UP Project] from the menu to launch the New X-UP Project Wizard.

2. In the New X-UP Project Wizard, enter the desired project name in the Project name field and click the Finish button.

3. Verify that the X-UP project has been created in the X-UP Explorer, as shown below.

Creating an Automation Model and Visual Cobol Invoke

1. Select [File > New > X-UP Automation Model] from the menu to launch the New Model Wizard.

2. In the New Model Wizard, enter the desired model name in the Model Name field and click the OK button.

3. After the New Model Wizard is complete, the following screen will appear.

4. In the Palette, select Visual Cobol under the Invoke section, and click the editor to create the Visual Cobol Invoke.

Creating a DataSource and Setting Properties

1. Double-click the created Visual Cobol Invoke (1) or click the Properties tab and click the Visual Cobol Icon[](2) to launch the wizard.

2. In the Invoke Cobol Wizard, click create a new DataSource[].

3. On the New DataSource page, define a new data source by entering the required values in the fields below. After that, click the Test Connection button to ensure the DataSource connection is established correctly.

4. After confirming the connection, click the Finish button.

5. Select Cobol as the DataSource and click the Select Method button[].

6. Choose the desired Method from the class and click the OK button.

7. Click the Test button.

8. Set the input parameter values in the Define Input Value wizard and click the Finish button to confirm that the data is displayed correctly.

9. Check the test results.

10. Click the OK button.

11. You can now confirm that the Visual Cobol Invoke has been created successfully.

Invoke Testing

1. The created Visual Cobol Invoke is ready. Based on the test results, input parameters and output parameters are generated.

2. Select InvokeInfo in the Properties of the Visual Cobol Invoke, and click[] to start the test.

3. When the Define Input Value wizard appears, enter the test values that were set during the Properties configuration and click the Finish button.

4. If the test is completed successfully, you can verify the results in the Test Result.

Model Testing

1. In the model editor, right-click to open the context menu. From the popup menu, select Test to run the model test.

2. Once the test is complete, the model's output will be displayed in the Result ParameterSet view.

3. Once the test is completed, the output of the model will be displayed in the Result ParameterSet view.

UserMethod 사용법

UserMethod의 사용법은 매우 무궁무진하기 때문에 대표적인 3가지 경우를 소개하겠습니다.

1. 다른 invoke를 UserMethod로 호출하기
2. session처리 예시
3. DatasetRowLoop와 UserMethod 같이 쓰기

1. 다른 invoke를 UserMethod로 호출하기

invoke들을 connection만으로 나타내기 힘들거나 복잡도가 높아 간단하게 실행시켜야 할 때 UserMethod를 통해 간소화할 수 있습니다.

• UserMethod의 코드

public void userMethod(ParameterSet globalParameterSet) throws AutomationFailException {
		//dataset3의 rowCount 수를 가져옴
		int rowCount = globalParameterSet.getDataSet("dataset3").getRowCount();
		
		//rowCount에 따라 실행 시킬 invoke 설정
		if(rowCount > 0) {
			// test_user() 실행
	        user(globalParameterSet);
		}else {
			// sqlite_sequence() 실행
	        sqlite_sequence(globalParameterSet);
		}  
	}

2. session처리 예시

• UserMethod의 코드

public void userMethod(ParameterSet globalParameterSet) throws AutomationFailException {
        // 사용자 세션 가져오기
        UserSession userSession = getUserSession();
        
        if (userSession != null) {
            String userId = (String) userSession.getAttribute("userId");
            System.out.println("User ID: " + userId);
        } else {
            throw new AutomationFailException("User session is null.");
        }
	}

3. DatasetRowLoop와 UserMethod 같이 쓰기

이 예시에서는 DatasetRowLoop의 간단한 사용 방법 및 주의해야 할 점을 설명합니다.

test_user select invoke를 실행하여 dataset1에 적재합니다.
dataSetRowLoop와 dataset1 을 연결 시켜 loopEvent생성합니다.
userMethod에서 dataset2에 중복 적재 방지를 위한 clearData()설정을 합니다.
loopEvent의 dataset을 조건으로 활용하기 위해 select1 invoke와 연결합니다. 해당 invoke실행 시 조회 결과를 dataset2에 적재합니다.
dataset2의 데이터를 user1 invoke에서 insert 수행

• UserMethod의 코드

public void userMethod(ParameterSet globalParameterSet, EuserMethodParameters eps) throws AutomationFailException {
		//그림의 rowIndex를 가져옴
		int rowIndex = eps.getRowIndex();
	    //rowIndex의 로그
	    System.out.println("Row index: " + rowIndex);
	    //dataset2의 데이터 삭제
	    globalParameterSet.getDataSet("dataset2").clearData();
	}

주의사항

datasetRowLoop실행시 loopEvent에 걸린 invoke도 rowCount 만큼 실행됩니다.
이때 UserMethod로 적절한 clearData()처리를 하지 않으면 loop횟수만큼 dataset에 쌓이게 됩니다.