SAS Data Integration Studio 3.3- P15 potx

Main Tasks for Administrators Preparation 65 server that is used to access the external file. This server must be able to resolve the physical path that you specify for the external file. As another example, suppose that you use the View Data option to view the contents of a table in the Inventory tree. To display the contents of the table, the default SAS application server or a SAS application server that is specified in the library metadata for the table must be able to resolve the path to the table. For the relevant server to resolve the path to a table in a SAS library, one of the following conditions must be met: The metadata for the library does not include an assignment to a SAS application server, and the default SAS application server can resolve the physical path that is specified for this library. The metadata for the library includes an assignment to a SAS application server that contains a SAS Workspace Server component, and the SAS Workspace Server is accessible in the current session. The metadata for the library includes an assignment to a SAS application server, and SAS/CONNECT is installed on both the SAS application server and the machine where the data resides. For more information about configuring SAS/CONNECT to access data on a machine that is remote to the default SAS application server, administrators should see “Multi-Tier Environments” in the SAS Data Integration Studio chapter in the SAS Intelligence Platform: Administration Guide. Note: If you select a library that is assigned to an inactive server, you receive a Cannot connect to workspace server error. Check to be sure that the server assigned to the library is running and is the active server. Execute a Job on a Remote Host See “Deploying a Job for Execution on a Remote Host” on page 68. Deploying a Job for Scheduling Preparation After you have verified that a SAS Data Integration Studio job runs successfully, you might want to schedule it to run in batch mode at a specified date and time. Scheduling a job is a two-stage process as follows: 1 An administrator deploys the job for scheduling. Code is generated for the job and the generated code is saved to a file. Metadata about the deployed job is saved to the current metadata repository. 2 The job is scheduled using the Schedule Manager plug-in to SAS Management Console or another scheduler. If possible, test a job and verify its output before deploying the job for scheduling. A job cannot be deployed for scheduling unless it is checked in. If you attempt to deploy a job that has been checked out, deployment fails and an error message displays. The error message indicates that the job is locked by a user. You cannot deploy a job for scheduling unless your metadata profile enables you to connect to SAS Data Integration Studio without change-management control. For 66 Deploy a Job for Scheduling Chapter 6 details about administrative profiles, see “Creating a Metadata Profile (for Administrators)” on page 58. It is assumed that the prerequisites for job scheduling have been met, as described in the SAS Data Integration Studio chapter in the SAS Intelligence Platform: Administration Guide. Deploy a Job for Scheduling Assume that you have tested a SAS Data Integration Studio job and verified its output and you are ready to deploy the job for scheduling in SAS Management Console. 1 Start SAS Data Integration Studio. A window displays that has various options for maintaining a metadata profile. 2 Select a profile that will enable you to connect to SAS Data Integration Studio without change-management control. 3 In the tree view, select the Inventory tab. 4 In the Inventory tree, expand the Jobs group. 5 Select one or more jobs that you want to deploy, right-click to display the pop-up menu, and select Deploy for Scheduling . The Deploy for Scheduling window displays. If you selected only one job, the file name for that job appears in the Directory Path field in the Deploy for Scheduling window. If you selected more than one job, no file names appear in the Directory Path field in the Deploy for Scheduling window. However, a separate file will be created for each job that is selected. Each deployed job file will be named after the corresponding job. 6 In the SAS server field, accept the default server or select the server that will be used to generate and store code for the selected job. 7 The next step is to select the job deployment directory. One or more job deployment directories were defined for the selected server when the metadata for that server was created. Click the Select button. The Deployment Directories window displays. 8 In the Deployment Directories window, select a directory where the generated code for the selected job will be stored, then click OK. You are returned to the Deploy for Scheduling window. The directory that you selected is specified in the Directory name field. If you selected one job, in the File name field you can edit the default name of the file that will contain the generated code for the selected job. The name must be unique in the context of the directory name that is specified above. 9 When you are ready to deploy the job or jobs, click OK. Code is generated for the selected job or jobs and is saved to the directory that is specified in the Directory name field. Metadata about the deployed jobs is saved to the current metadata repository. A status window displays. It states whether the deployment was successful or not. The icon next to the jobs that you selected changes to indicate that the jobs are now available for scheduling in SAS Management Console. A small clock is added to the job icon. Next Tasks After a job has been deployed from SAS Data Integration Studio, you can schedule the job by using the Schedule Manager plug-in to SAS Management Console or another scheduler. For details about the Schedule Manager plug-in, see its Help or see the SAS Management Console: User’s Guide. See also the chapter about SAS scheduling in the SAS Intelligence Platform: Administration Guide. Main Tasks for Administrators Additional Information About Job Scheduling 67 If you deploy a job for scheduling and then update the job, you must redeploy the job so that the latest version of the job is scheduled. For details, see redeploying jobs for scheduling topic in the Help. Note: The code that is generated for a job contains the credentials of the person who created the job. If a person’s credentials have changed, and a deployed job contains outdated user credentials, the deployed job will fail to execute. The remedy is to redeploy the job with the appropriate credentials. Additional Information About Job Scheduling The Help for SAS Data Integration Studio contains additional information about job scheduling. To display the relevant Help topics, follow these steps: 1 From the SAS Data Integration Studio menu bar, select Help Contents. The Help window displays. 2 In the left pane of the Help window, select Task Overviews SAS Data Integration Studio Task Reference Maintaining Stored Processes. 68 Deploying a Job for Execution on a Remote Host Chapter 6 Deploying a Job for Execution on a Remote Host Preparation Administrators can use the Deploy for Scheduling window to deploy a job for execution on a host that is remote from the default SAS application server. Code is generated for the job and the generated code is saved to a file. Metadata about the deployed job is saved to the current metadata repository. After a job has been deployed to the remote host, it can be executed by any convenient means. Remember that the generated code is local to the server that is selected in the Deploy for Scheduling window. For example, suppose that the default SAS application server for SAS Data Integration Studio is named SASMain, but you want a job to execute on another SAS application server that is named DEZ_App Server. You would select DEZ_App Server in the Deploy for Scheduling window, and the code that is generated for the job would be local to DEZ_App Server. If possible, test a job and verify its output before deploying the job. A job cannot be deployed unless it is checked in. If you attempt to deploy a job that has been checked out, deployment fails and an error message displays. The error message indicates that the job is locked by a user. You cannot deploy a job unless your metadata profile enables you to connect to SAS Data Integration Studio without change-management control. For details about administrative profiles, see “Creating a Metadata Profile (for Administrators)” on page 58. A SAS Workspace Server and a SAS Data Step Batch Server must be configured on the remote host. For information about this configuration, administrators should see “Multi-Tier Environments” in the SAS Data Integration Studio chapter in the SAS Intelligence Platform: Administration Guide. Task Summary 1 Start SAS Data Integration Studio. A window displays that has various options for maintaining a metadata profile. 2 Select a profile that will enable you to connect to SAS Data Integration Studio without change-management control. 3 In the tree view, select the Inventory tab. 4 In the Inventory tree, expand the Jobs group. 5 Select one or more jobs that you want to deploy, right-click to display the pop-up menu, and select Deploy for Scheduling. The Deploy for Scheduling window displays. If you selected only one job, the file name for that job appears in the Directory Path field in the Deploy for Scheduling window. If you selected more than one job, no file names appear in the Directory Path field of the Deploy for Scheduling window. However, a separate file will be created for each job that is selected. Each deployed job file will be named after the corresponding job. 6 In the SAS server field, select the server that is to used to execute the selected job. In this example, you would not accept the default but would select the remote server, DEZ_App Server. Main Tasks for Administrators About Stored Processes 69 7 The next step is to select the job deployment directory. One or more job deployment directories were defined for the selected server when the metadata for that server was created. Click the Select button. The Deployment Directories window displays. 8 In the Deployment Directories window, select a directory where the generated code for the selected job will be stored, then click OK. You are returned to the Deploy for Scheduling window. The directory that you selected is specified in the Directory name field. If you selected one job, in the File name field you can edit the default name of the file that will contain the generated code for the selected job. The name must be unique in the context of the directory name that is specified above. 9 When you are ready to deploy the job or jobs, click OK. Code is generated for the selected job or jobs and is saved to the directory that is specified in the Directory name field. Metadata about the deployed jobs is saved to the current metadata repository. A status window displays. It states whether the deployment was successful or not. The icon next to the jobs that you selected changes to indicate that the jobs have been deployed to the remote server. Next Tasks After a job has been deployed to the remote host, it can be executed by any convenient means. Converting Jobs into Stored Processes About Stored Processes SAS Data Integration Studio enables you to create jobs that perform various data integration tasks. You can execute jobs immediately, or you can save them to a file so that a stored process server can execute them later. A stored process is a SAS program that is stored on a server and can be executed as required by requesting applications. You can use stored processes for Web reporting, analytics, building Web applications, delivering result packages to clients or to the mid-tier, and publishing results to channels or repositories. Stored processes can also access any SAS data source or external file and create new data sets, files, or other data targets supported by SAS. Administrators can generate one or more stored processes for a job that is selected in the Inventory tree or the Custom tree on the SAS Data Integration Studio desktop. Code is generated for the stored process and the generated code is saved to a file. Metadata about the stored process is saved in the current metadata repository. After the metadata has been saved to a repository, other applications can connect to the repository and access the stored processes that are defined there—if they have appropriate privilege. For example, a stored process that was generated for a SAS Data Integration Studio job could be executed from the following applications: SAS Add-In for Microsoft Office, a Component Object Model (COM) add-in that extends Microsoft Office by enabling you to dynamically execute stored processes and embed the results in Microsoft Word documents and Microsoft Excel spreadsheets. . have tested a SAS Data Integration Studio job and verified its output and you are ready to deploy the job for scheduling in SAS Management Console. 1 Start SAS Data Integration Studio. A window. see “Multi-Tier Environments” in the SAS Data Integration Studio chapter in the SAS Intelligence Platform: Administration Guide. Task Summary 1 Start SAS Data Integration Studio. A window displays that. Scheduling The Help for SAS Data Integration Studio contains additional information about job scheduling. To display the relevant Help topics, follow these steps: 1 From the SAS Data Integration Studio menu