Install and configure BigQuery Connector for SAP on a host outside of Google Cloud

This guide shows how to install and configure version 2.8 (latest) of the BigQuery Connector for SAP in an SAP LT Replication Server that is running on a host that is on premises, on another cloud provider, or in another environment outside of Google Cloud.

If your SAP LT Replication Server box is managed by SAP through the SAP RISE program, then you follow this guide to install and configure BigQuery Connector for SAP.

This guide covers how to prepare BigQuery, SAP Landscape Transformation Replication Server (SAP LT Replication Server), and BigQuery Connector for SAP to replicate SAP data from SAP applications directly and securely to BigQuery in real time.

This guide is intended for SAP administrators, Google Cloud administrators, and other SAP and Google Cloud security and data professionals.

Prerequisites

Before you install BigQuery Connector for SAP, make sure that the following prerequisites have been satisfied:

  • You have read the BigQuery Connector for SAP planning guide. The planning guide explains BigQuery Connector for SAP options, performance considerations, field mapping, and other information that you need for the optimal configuration of BigQuery Connector for SAP.

  • If you don't have a Google Cloud project already, create one:

    Go to project selector

  • Billing is enabled for your project. Learn how to confirm that billing is enabled for your project. A billing account is required for BigQuery streaming API, BigQuery, and to download BigQuery Connector for SAP.

  • Maintenance for the installed SAP software is current and the versions of all of the SAP software are compatible with each other, as documented in the SAP Product Availability Matrix.

  • The versions of the SAP software you are using are supported by the BigQuery Connector for SAP, as documented in Software requirements.

  • You have the correct SAP licenses that are required to replicate data to any target via the SAP LT Replication Server SDK. For more information about SAP licensing, see SAP Note 2707835.

  • SAP LT Replication Server is installed. For information about installing SAP LT Replication Server, see the SAP documentation.

  • The RFC or database connection between SAP LT Replication Server and the source system is configured. If necessary, test the RFC connections by using SAP transaction SM59. Test database connections by using SAP transaction DBACOCKPIT.

Overview of the installation and configuration process

The following table shows procedures covered in this guide and the roles that typically perform them.

Procedure Role
If necessary, after validating all appropriate licenses from SAP, follow the SAP instructions to install an SAP Landscape Transformation Replication Server. SAP administrator.
If necessary, install the user interface (UI) add-on for SAP NetWeaver. For more information, see SAP software version requirements. SAP administrator.
Establish a network connection between your SAP system and Google Cloud. Network administrator.
Enable the required Google Cloud APIs. Google Cloud administrator.
Enable private access to the Google Cloud APIs. Google Cloud network administrator.
Create a BigQuery dataset. Google Cloud administrator or data engineer.
Set up Google Cloud authentication and authorization. Google Cloud security administrator.
Download the BigQuery Connector for SAP installation package. Google Cloud billing account holder.
Install BigQuery Connector for SAP. SAP administrator.
Create SAP roles and permissions for BigQuery Connector for SAP. SAP administrator.
Configure replication. Data engineers or administrators.
Test replication. Data engineers or administrators.
Validate replication. Data engineers or administrators.

Establish a network connection to Google Cloud

If your SAP workload is not running on Google Cloud, you or a network administrator needs to establish a secure, high-bandwidth, low-latency connection to Google Cloud.

You have the following two connection options:

To set a connection up, follow the instructions provided by the Google Cloud connection service that you select.

Each connection service has different instructions for different scenarios, so review the service documentation and follow the instructions for your scenario.

Enable the required Google Cloud APIs

Before BigQuery Connector for SAP can access BigQuery, you need to enable the following Google Cloud APIs:

  • The BigQuery API
  • The IAM Service Account Credentials API

For information about how to enable Google Cloud APIs, see Enabling APIs.

Enable private access to the Google Cloud APIs

If your SAP workload is not running on Google Cloud, after you establish a network connection to Google Cloud, you need to enable private access to the Google Cloud APIs.

To enable private API access, see Configuring Private Google Access for on-premises hosts.

Create a BigQuery dataset

Before you can test Google Cloud authentication and authorization for BigQuery or create target BigQuery tables, you or a data engineer or administrator needs to create a BigQuery dataset.

To create a BigQuery dataset, your user account must have the proper IAM permissions for BigQuery. For more information, see Required permissions.

  1. In the Google Cloud console, go to the BigQuery page:

    Go to BigQuery

  2. Next to your project ID, click the View actions icon, , and then click Create dataset.

    Diagram is described in the preceding text

  3. In the Dataset ID field, enter a unique name. For more information, see Name datasets.

After you set up Google Cloud authentication and authorization, you test access to Google Cloud by retrieving information about this dataset.

For more information about creating BigQuery datasets, see Creating datasets.

Set up Google Cloud authentication and authorization

For authentication to Google Cloud and authorization to access BigQuery, a Google Cloud security administrator and an SAP administrator need to set up authentication using JSON Web Tokens (JWT) signed by Google Cloud.

The high-level configuration steps are as follows:

Create a service account for JWT based token retrieval

Create a service account

For JWT based authentication to Google Cloud, BigQuery Connector for SAP needs an IAM service account.

To create a service account for JWT based token retrieval, complete the following steps:

  1. In the Google Cloud console, go to the IAM & Admin Service accounts page.

    Go to Service accounts

  2. If prompted, select your Google Cloud project.

  3. Click Create Service Account.

  4. Specify a name for the service account and, optionally, a description.

  5. Click Create and Continue.

  6. In the Grant this service account access to project panel, select the Service Account Token Creator role.

  7. Click Continue.

  8. As appropriate, grant other users access to the service account.

  9. Click Done. The service account appears in the list of service accounts for the Google Cloud project.

Create a service account key

You need to create a P12 service account key for the service account used for JWT based token retrieval.

To create a service account key, complete the following steps:

  1. In the Google Cloud console, go to the IAM & Admin Service accounts page.

    Go to Service accounts

  2. Select your Google Cloud project.

  3. Click the email address of the service account that you created for JWT based token retrieval in the previous section, Create a service account.

  4. Under the service account name, click the Keys tab.

  5. Click the Add Key drop-down menu, and then select Create new key to create a service account key.

  6. Accept P12 as the key type and click Create.

    A private key is saved to your computer.

  7. Make a note of the password for the private key file, notasecret.

    Provide the private key and password to your SAP administrator to import the private key into STRUST, as described in Import the service account key into STRUST.

Enable JWT signing for the service account on the SAP LT Replication Server host

To enable JWT signing for the service account that you created for JWT based token retrieval, you need to add the parameter JWT_SERVC_ACCT to the table /GOOG/BQ_PARAM and configure the service account.

To enable JWT signing for a service account, complete the following steps:

  1. In the SAP GUI, enter the /GOOG/SLT_SETTINGS transaction preceded by /n:

    /n/GOOG/SLT_SETTINGS

  2. From the Settings Table drop-down menu in the launch screen for the /GOOG/SLT_SETTINGS transaction, select Parameters.

  3. Click the Execute icon. The BigQuery Settings Maintenance - Parameters screen displays.

  4. Click the Insert Row icon.

  5. In the displayed row, specify the following settings:

    1. In the Parameter Name field, enter JWT_SERVC_ACCT. The parameter description is automatically populated.
    2. In the Parameter Value field, enter the email address of the service account that you created for JWT based token retrieval in the previous section, Create a service account.

  6. Click Save.

    Your settings are stored as a record in the /GOOG/BQ_PARAM configuration table and the Changed By, Changed On, and Changed At fields are automatically populated.

Configure security settings for Google Cloud on the SAP LT Replication Server host

Create a new Secure Store and Forward (SSF) Application

In the table SSFAPPLIC, the ZG_JWT entry is imported as part of the BigQuery Connector for SAP transport. In case, the ZG_JWT entry is not imported, you need to create a new entry with the name ZG_JWT by using transaction SE16.

To create a new entry in the table SSFAPPLIC, complete the following steps:

  1. In the SAP GUI, enter transaction code SE16.
  2. In the Table Name field, enter SSFAPPLIC, and then create a new entry.
  3. For the APPLIC field, enter ZG_JWT.
  4. Except the B_INCCERTS, B_DETACHED, B_ASKPWD, and B_DISTRIB fields, select all other fields.
  5. In the DESCRIPT field, enter JWT Signature for GCP.

  6. Save the new entry.

    This entry becomes a new node in transaction STRUST, where you import the service account key.

Enable the STRUST node

Use transaction SSFA to enable the STRUST node for JWT Signature for GCP.

To enable the STRUST node, complete the following steps:

  1. In the SAP GUI, enter transaction SSFA.
  2. Click New Entries.

  3. In the SSF Application drop-down list, select JWT Signature for GCP. This is the new entry that you created in the table SSFAPPLIC.

    The following screenshot shows the application-specific SSF parameters that are automatically populated by SAP.

    Application specific SSF parameters

  4. Save the new entry.

    A new node SSF JWT Signature for GCP is enabled in transaction STRUST. Now you import the service account key into this node.

Import the service account key into STRUST

To import the service account key into STRUST, complete the following steps:

  1. In the SAP GUI, enter transaction code STRUST.

    Verify the new node in transaction STRUST is SSF JWT Signature for GCP.

  2. Import the private key file:

    1. Select PSE > Import from the menu bar.
    2. Depending on your source system type, select the appropriate private key:
      • S4/HANA
        1. Select the P12 private key.
        2. Enter the file password notasecret, and then click OK.
      • ECC
        1. Select the PSE private key. You need to convert the P12 private key that you downloaded earlier into a PSE private key. For more information about converting a P12 key into a PSE key, see Convert P12 key into PSE key.
        2. Enter the file PIN that you created during the private key conversion from P12 key to PSE key, and then click OK.

  3. Select PSE > Save as.

  4. Select the SSF Application option button, and in the corresponding field, select the new SSF Application node that you created in Create a new Secure Store and Forward (SSF) Application.

  5. Save the new entry.

    The service key is attached to the SSF application node SSF JWT Signature for GCP.

Convert the P12 private key into PSE key

If your source system is SAP NetWeaver 7.0x (SAP ECC), then you need to convert the P12 key into a PSE key.

To convert the P12 key into a PSE key, complete the following steps:

  1. Go to the path: 

    /usr/sap/SID/SYS/exe/run/

    Replace SID with the SAP system ID.

  2. Run the following command after replacing the placeholders: 

    sapgenpse import_p12 -p PSE_PATH_AND_FILE_NAME P12_PATH_AND_FILE_NAME.p12

    Replace the following:

    • PSE_PATH_AND_FILE_NAME: specify the path and file name for the PSE file
    • P12_PATH_AND_FILE_NAME: specify the path and file name for the P12 key file

  3. Enter the password of P12 private key file, notasecret.

  4. Create a new PIN for the PSE private key and re-enter your PIN.

  5. Make a note of the PIN, you need to provide this PIN when importing the PSE private key file into STRUST.

For information from SAP about about how to convert a P12 key into a PSE key, see:

Create a service account for authorization to access BigQuery

Create a service account

BigQuery Connector for SAP needs an IAM service account for authentication and authorization to access BigQuery.

This service account must be a principal in the Google Cloud project that contains your BigQuery dataset. If you create the service account in the same project as the BigQuery dataset, the service account is added as a principal to the project automatically.

If you create the service account in a project other than the project that contains the BigQuery dataset, you need to add the service account to the BigQuery dataset project in an additional step.

To create a service account, complete the following steps:

  1. In the Google Cloud console, go to the IAM & Admin Service accounts page.

    Go to Service accounts

  2. If prompted, select your Google Cloud project.

  3. Click Create Service Account.

  4. Specify a name for the service account and, optionally, a description.

  5. Click Create and Continue.

  6. If you are creating the service account in the same project as the BigQuery dataset, in the Grant this service account access to project panel, select the following roles:

    • BigQuery Data Editor
    • BigQuery Job User

    If you are creating the service account in a different project than the BigQuery dataset, do not grant any roles to the service account.

  7. Click Continue.

  8. As appropriate, grant other users access to the service account.

  9. Click Done. The service account appears in the list of service accounts for the project.

  10. If you created the service account in a different project than the project that contains the BigQuery dataset, note the name of the service account. You specify the name when you add the service account to the BigQuery project. For more information, see Add the service account to the BigQuery project.

The service account is now listed as a principal on the IAM Permissions page of the Google Cloud project in which the service account was created.

Add the service account to the BigQuery project

If you created the service account for BigQuery Connector for SAP in a project other than the project that contains the target BigQuery dataset, you need to add the service account to the BigQuery dataset project.

If you created the service account in the same project as the BigQuery dataset, you can skip this step.

To add an existing service account to the BigQuery dataset project, complete the following steps:

  1. In the Google Cloud console, go to the IAM Permissions page:

    Go to IAM permissions

  2. Confirm that the name of the project that contains the target BigQuery dataset is displayed near the top of the page. For example:

    Permissions for project "PROJECT_NAME"

    If it is not, switch projects.

  3. On the IAM page, click Add. The Add principals to "PROJECT_NAME" dialog opens.

  4. In the Add principals to "PROJECT_NAME" dialog, complete the following steps:

    1. In the New principals field, specify the name of the service account.
    2. In the Select a role field, specify BigQuery Data Editor.
    3. Click ADD ANOTHER ROLE. The Select a role field displays again.
    4. In the Select a role field, specify BigQuery Job User.
    5. Click Save. The service account appears in the list of project principals on the IAM page.

The service account can now be used to access the BigQuery dataset in this project.

Set up SSL certificates and HTTPS

Communication between BigQuery Connector for SAP and the BigQuery API is secured by using SSL and HTTPS.

  1. Download the following certificates from the Google Trust Services repository:

    • GTS Root R1
    • GTS CA 1C3

  2. In the SAP GUI, use the STRUST transaction to import both the root and subordinate certificate into the SSL client SSL Client (Standard) PSE folder.

    For more information from SAP, see SAP Help - Maintain PSE Certification list.

  3. On the SAP LT Replication Server host, confirm that any firewall rules or proxies are configured to allow egress traffic from the HTTPS port to the BigQuery API.

    Specifically, SAP LT Replication Server needs to be able to access the following Google Cloud APIs:

    • https://bigquery.googleapis.com
    • https://iamcredentials.googleapis.com

    If you want BigQuery Connector for SAP to access Google Cloud APIs through Private Service Connect endpoints in your VPC network, then you must configure RFC destinations and specify your Private Service Connect endpoints in those RFC destinations. For more information, see RFC destinations.

For more information from SAP about setting up SSL, see SAP Note 510007 - Additional considerations for setting up SSL on Application Server ABAP.

Create ABAP configurations

Create RFC destinations

RFC destinations GOOG_OAUTH2_TOKEN, GOOG_IAMCREDENTIALS, and GOOG_BIGQUERY are imported as part of the BigQuery Connector for SAP transport. In case these RFC destinations are not imported, then you need to create new RFC destinations GOOG_OAUTH2_TOKEN, GOOG_IAMCREDENTIALS, and GOOG_BIGQUERY, by using transaction SM59.

For information about creating RFC destinations, see Configure RFC destinations.

Specify access settings in /GOOG/CLIENT_KEY

Use transaction SM30 to specify settings for access to Google Cloud. BigQuery Connector for SAP stores the settings as a record in the /GOOG/CLIENT_KEY custom configuration table.

To specify the access settings, complete the following steps:

  1. In the SAP GUI, enter transaction code SM30.

  2. Select the /GOOG/CLIENT_KEY configuration table.

  3. Enter values for the following table fields:

    Field Data type Description
    Name String The name of this CLIENT_KEY configuration.
    Service Account Name String

    The name of the service account, in email address format, that was created for BigQuery Connector for SAP in the step Create a service account. For example: sap-example-svc-acct@example-project-123456.iam.gserviceaccount.com.

    Scope String The access scope.

    Specify the https://www.googleapis.com/auth/cloud-platform API access scope, as recommended by Compute Engine.

    Project ID String The ID of the project that contains your target BigQuery dataset.
    Command name String Leave this field blank.
    Authorization Class String The authorization class.

    Specify /GOOG/CL_GCP_AUTH_JWT.

    Authorization Field Not applicable Leave this field blank.
    Token Refresh Seconds Integer Leave this field blank.

Specify RFC destinations in /GOOG/SERVIC_MAP

Use transaction SM30 to specify RFC destinations in the service mapping table /GOOG/SERVIC_MAP.

To specify the RFC destinations, complete the following steps:

  1. In the SAP GUI, enter transaction code SM30.

  2. In the /GOOG/CLIENT_KEY table that you created in the preceding section, note the value for the Name field.

  3. In the table /GOOG/SERVIC_MAP, create entries with the following field values:

Name Service Name RFC Destination
CLIENT_KEY_TABLE_NAME googleapis.com/oauth2 GOOG_OAUTH2_TOKEN
CLIENT_KEY_TABLE_NAME iamcredentials.googleapis.com GOOG_IAMCREDENTIALS

Replace CLIENT_KEY_TABLE_NAME with the table name that you noted in the preceding step.

Download the installation package

Download the latest BigQuery Connector for SAP installation package from BigQuery Connector for SAP download portal.

You need your Cloud Billing number to complete the download. For information about billing accounts, see Cloud Billing & payments profile.

The installation package includes transport files that you copy into the appropriate transport directory for SAP LT Replication Server.

Install BigQuery Connector for SAP

After you receive the installation package that contains the BigQuery Connector for SAP transport files, your SAP administrator can install BigQuery Connector for SAP by importing the transport files into SAP LT Replication Server.

The SAP transport for BigQuery Connector for SAP contains all of the objects that are required for BigQuery Connector for SAP, including the /GOOG/ namespace, DDIC objects, the SLT SDK BADI implementation and classes, report programs, and more.

Before importing the transport files into SAP LT Replication Server, verify that your SAP LT Replication Server is supported by BigQuery Connector for SAP, as documented in Software requirements.

In spite of using a supported version of SAP LT Replication Server, in some cases, while importing the transport files, you might see the error message, Requests do not match the component version of the target system. In such cases, you need to re-import the transport files into SAP LT Replication Server and while re-importing, on the Import Transport Request screen, go to the Options tab, and then select the Ignore Invalid Component Version checkbox.

The following procedure is a general procedure. Each SAP system is different, so work with your SAP administrator to determine any changes to the procedure that might be required for your SAP system:

  1. Copy BigQuery Connector for SAP transport files into the following SAP LT Replication Server transport import directories:

    • /usr/sap/trans/cofiles/KXXXXXX.ED1
    • /usr/sap/trans/data/RXXXXXX.ED1

    In the preceding examples, XXXXXX represents the numbered file name.

  2. In the SAP GUI, use transaction code STMS_IMPORT or STMS to import the files into the SAP system.

  3. Make sure all objects in /GOOG/SLT_SDK package are active and consistent:

    1. In the SAP interface, enter transaction code SE80.
    2. In the package selector, select /GOOG/SLT_SDK.

    3. In the Object name field, right-click on the package /GOOG/SLT_SDK, and then choose Check > Package Check > Objects of Package.

      A green check in the Result column indicates that all objects passed the package check.

Confirm that BigQuery Connector for SAP is ready to configure

To further confirm that the transport files have been imported correctly and that BigQuery Connector for SAP is ready to configure, confirm that BigQuery Connector for SAP Business Add-In (BAdI) implementation is active and that BigQuery Connector for SAP replication applications have entries in the IUUC_REPL_APPL table.

  1. Check the BAdI implementation:
    1. Use the transaction SE80 to navigate to and select the /GOOG/EI_IUUC_REPL_RUNTIME_BQ enhancement object folder.
    2. Select Enh. Implementation Elements on the right side of the page.
    3. Under Runtime Behavior, confirm that Implementation is active is checked.
  2. Check the replication applications:
    1. Using the SAP Data Browser or transaction SE16, display the IUUC_REPL_APPL table.
    2. Confirm that the following applications appear in the IUUC_REPL_APPL table:
      • /GOOG/SLT_BQ
      • ZGOOG_SLT_BQ, for use when the /GOOG/ namespace isn't registered

Create SAP roles and authorizations for BigQuery Connector for SAP

To work with BigQuery Connector for SAP, in addition to the standard SAP LT Replication Server authorizations, users need access to the custom transactions that are provided with BigQuery Connector for SAP: /GOOG/SLT_SETTINGS and /GOOG/REPLIC_VALID.

To use the Load Simulation tool, users need access to the custom transaction /GOOG/LOAD_SIMULATE that is provided with BigQuery Connector for SAP.

By default, users that have access to the custom transactions /GOOG/SLT_SETTINGS and /GOOG/REPLIC_VALIDcan modify the settings of any configuration, so if you need to, you can restrict access to specific configurations. For users who only need to view the BigQuery Connector for SAP settings, you can grant them read-only access to the custom transaction /GOOG/SLT_SETT_DISP.

The BigQuery Connector for SAP transport files include the Google BigQuery Settings Authorization object, ZGOOG_MTID, for authorizations that are specific to BigQuery Connector for SAP.

To grant access to the custom transactions and restrict access to specific configurations, perform the following steps:

  1. Using SAP transaction code PFCG, define a role for the BigQuery Connector for SAP.

  2. Grant the role access to the custom transactions /GOOG/SLT_SETTINGS, /GOOG/REPLIC_VALID, and /GOOG/LOAD_SIMULATE.

  3. To limit the access of a role, specify the authorization group of each configuration that the role can access by using the ZGOOG_MTID authorization object. For example:

    • Authorization object for BigQuery Connector for SAP (ZGOOG_MTID):
      • Activity 01
      • Authorization Group AUTH_GROUP_1,AUTH_GROUP_N

    The AUTH_GROUP_01 and AUTH_GROUP_N are values that are defined in the SAP LT Replication Server configuration.

    The authorization groups specified for ZGOOG_MTID must match the authorization groups that are specified for the role in the SAP S_DMIS_SLT authorization object.

Create SAP roles and authorizations for viewing BigQuery Connector for SAP settings

To grant read-only access for the custom transaction /GOOG/SLT_SETT_DISP, perform the following steps:

  1. Using SAP transaction code PFCG, define a role for viewing the BigQuery Connector for SAP settings.

  2. Grant the role access to the custom transaction /GOOG/SLT_SETT_DISP.

  3. Add the authorization object for BigQuery Connector for SAP (ZGOOG_MTID) with the following attributes:

    • Activity 03
    • Authorization Group = *

  4. Generate the role profile and assign relevant users to the role.

Configure replication

To configure replication, you specify both BigQuery Connector for SAP and SAP LT Replication Server settings.

Specify access settings in /GOOG/CLIENT_KEY

Use transaction SM30 to specify settings for access to BigQuery. BigQuery Connector for SAP stores the settings as a record in the /GOOG/CLIENT_KEY custom configuration table.

To specify the access settings:

  1. In the SAP GUI, enter transaction code SM30.

  2. Select the /GOOG/CLIENT_KEY configuration table.

  3. Enter values for the following table fields:

    Field Data type Description
    Name String

    Specify a descriptive name for the CLIENT_KEY configuration, such as ABAP_SDK_CKEY.

    A client key name is a unique identifier that is used by the BigQuery Connector for SAP to identify the configurations for accessing BigQuery.
    Service Account Name String

    Leave this field blank.

    Scope String

    Leave this field blank.

    Project ID String The ID of the project that contains your target BigQuery dataset.
    Command name String

    Leave this field blank.
    Authorization Class String The authorization class to use for replication.

    Specify /GOOG/CL_GCP_AUTH.

    Authorization Field Not applicable Leave this field blank.
    Token Refresh Seconds Integer

    The amount of time, in seconds, before an access token expires and must be refreshed. The default value is 3500. You can overwrite this default value by setting a value for the CMD_SECS_DEFLT parameter in the advanced settings.

    Specifying a value from 1 to 3599 overrides the default expiration time. If you specify 0, then the BigQuery Connector for SAP uses the default value.

    Token Caching Boolean The flag that determines whether or not the access tokens retrieved from Google Cloud are cached.

    We recommend that you enable token caching after you are done configuring BigQuery Connector for SAP and testing your connection to Google Cloud. For more information about token caching, see Enable token caching.

Configure RFC destinations

To connect the BigQuery Connector for SAP to Google Cloud, we recommend that you use RFC destinations.

To configure the RFC destinations for your replication:

  1. In the SAP GUI, enter transaction code SM59.

  2. (Recommended) Create new RFC destinations by copying the sample RFC destinations GOOG_BIGQUERY and GOOG_IAMCREDENTIALS, and then make a note of the new RFC destination names. You use them in later steps.

    The BigQuery Connector for SAP uses RFC destinations to connect to BigQuery and IAM APIs, respectively.

    If you want to test RFC destination based connectivity, then you can skip this step and use the sample RFC destinations.

  3. For the RFC destinations that you created, complete the following steps:

    1. Go to the Technical Settings tab and make sure that the Service No. field is set with the value 443. This is the port that is used by the RFC destination for secure communication.

    2. Go to the Logon & Security tab and make sure that the SSL Certificate field is set with the option DFAULT SSL Client (Standard).

    3. Optionally, you can configure proxy settings, enable HTTP compression, and specify Private Service Connect endpoints.

    4. Save your changes.

    5. To test the connection, click Connection Test.

      A response containing 404 Not Found is acceptable and expected because the endpoint specified in the RFC destination corresponds to a Google Cloud service and not a specific resource hosted by the service. Such a response indicates that the target Google Cloud service is reachable and that no target resource was found.

  4. In the SAP GUI, enter transaction code SM30.

  5. In the /GOOG/CLIENT_KEY table that you created in the preceding section, note the value for the Name field.

  6. In the table /GOOG/SERVIC_MAP, create entries with the following field values:

    Google Cloud Key Name Google Service Name RFC Destination
    CLIENT_KEY_TABLE_NAME bigquery.googleapis.com Specify the name of your RFC destination that targets BigQuery. If you're using the sample RFC destination for testing purposes, then specify GOOG_BIGQUERY.
    CLIENT_KEY_TABLE_NAME iamcredentials.googleapis.com Specify the name of your RFC destination that targets IAM. If you're using the sample RFC destination for testing purposes, then specify GOOG_IAMCREDENTIALS.

    Replace CLIENT_KEY_TABLE_NAME with the client key name that you noted in the preceding step.

Configure proxy settings

When you use RFC destinations to connect to Google Cloud, you can route communication from BigQuery Connector for SAP through the proxy server that you're using in your SAP landscape.

If you do not want to use a proxy server or don't have one in your SAP landscape, then you can skip this step.

To configure proxy server settings for BigQuery Connector for SAP, complete the following steps:

  1. In the SAP GUI, enter transaction code SM59.

  2. Select your RFC destination that targets IAM.

  3. Go to the Technical Settings tab, and then enter values for the fields in the HTTP Proxy Options section.

  4. Repeat the previous step for your RFC destination that targets BigQuery.

Enable HTTP compression

When you use RFC destinations to connect to Google Cloud, you can enable HTTP compression.

If you do not want to enable this feature, then you can skip this step.

To enable HTTP compression, complete the following steps:

  1. In the SAP GUI, enter transaction code SM59.

  2. Select your RFC destination that targets BigQuery.

  3. Go to the Special Options tab.

  4. For the HTTP Version field, select HTTP 1.1.

  5. For the Compression field, select an appropriate value.

    For information about the compression options, see SAP Note 1037677 - HTTP compression compresses certain documents only

Specify Private Service Connect endpoints

If you want BigQuery Connector for SAP to use Private Service Connect endpoints to allow private consumption of BigQuery and IAM, then you need to create those endpoints in your Google Cloud project and specify them in the respective RFC destinations.

If you want BigQuery Connector for SAP to continue using the default, public API endpoints to connect to BigQuery and IAM, then skip this step.

To configure BigQuery Connector for SAP to use your Private Service Connect endpoints, complete the following steps:

  1. In the SAP GUI, enter transaction code SM59.

  2. Validate that you have created new RFC destinations for BigQuery and IAM. For instructions to create these RFC destinations, see Configure RFC destinations.

  3. Select the RFC destination that targets BigQuery and then complete the following steps:

    1. Go to the Technical Settings tab.

    2. For the Target Host field, enter the name of the Private Service Connect endpoint that you created to access BigQuery.

    3. Go to the Logon and Security tab.

    4. For the Service No. field, make sure that value 443 is specified.

    5. For the SSL Certificate field, make sure that the option DFAULT SSL Client (Standard) is selected.

  4. Select the RFC destination that targets IAM and then complete the following steps:

    1. Go to the Technical Settings tab.

    2. For the Target Host field, enter the name of the Private Service Connect endpoint that you created to access IAM.

    3. Go to the Logon and Security tab.

    4. For the Service No. field, make sure that value 443 is specified.

    5. For the SSL Certificate field, make sure that the option DFAULT SSL Client (Standard) is selected.

Enable token caching

To improve replication performance, we recommend that you enable caching for the access token that you retrieve from Google Cloud to access BigQuery.

Enabling token caching makes sure that an access token is reused until the access token expires or is revoked, which in turn reduces the number of HTTP calls made to retrieve new access tokens.

To enable token caching, select the Token Caching flag in the client key table /GOOG/CLIENT_KEY.

When you enable token caching, the access token is cached in the Shared Memory of your SAP LT Replication Server application server for the duration that is set for the Token Refresh Seconds field in the /GOOG/CLIENT_KEY table. If Token Refresh Seconds is not specified or is set to 0, then the access token is cached for the value specified in the CMD_SECS_DEFLT parameter in advanced settings.

For SAP workloads that are not running on Google Cloud, the cached access tokens also prevent technical issues that might arise while replicating huge data loads, where several processes of SAP LT Replication Server can simultaneously request for an access token at any given time.

Clear the cached access token

When token caching is enabled and you update the roles assigned to the service account that BigQuery Connector for SAP uses to access BigQuery, the new access token that corresponds to the updated roles is retrieved only after the existing cached token expires. In such situations, you can clear the access token manually.

To clear the cached access token, enter transaction SE38 and then run the program /GOOG/R_CLEAR_TOKEN_CACHE.

Create an SAP LT Replication Server replication configuration

Use SAP transaction LTRC to create an SAP LT Replication Server replication configuration.

If SAP LT Replication Server is running on a different server than the source SAP system, before you create a replication configuration, confirm that you have an RFC connection between the two systems.

Some of the settings in the replication configuration affect performance. To determine appropriate setting values for your installation, see the Performance Optimization Guide for your version of SAP LT Replication Server in the SAP Help Portal.

The interface and configuration options for SAP LT Replication Server might be slightly different depending on which version you are using.

To configure replication, use the procedure for your version of SAP LT Replication Server:

Configure replication in DMIS 2011 SP17, DMIS 2018 SP02, or later

The following steps configure replication in later versions of SAP LT Replication Server. If you are using an earlier version, see Configure replication in DMIS 2011 SP16, DMIS 2018 SP01, or earlier.

  1. In the SAP GUI, enter transaction code LTRC.

  2. Click the Create configuration icon. The Create Configuration wizard opens.

  3. In the Configuration Name and Description fields, enter a name and a description for the configuration, and then click Next.

    You can specify the Authorization Group for restricting access to a specific authorization group now or specify it later.

  4. In the Source System Connection Details panel:

    • Select the RFC Connection radio button.
    • In the RFC Destination field, specify the name of the RFC connection to the source system.
    • Select the checkboxes for Allow Multiple Usage and Read from Single Client as appropriate. For more information, see the SAP LT Replication Server documentationl.
    • Click Next.

    These steps are for an RFC connection, but if your source is a database, you can select DB Connection if you have already defined a connection by using transaction DBACOCKPIT instead.

  5. In the Target System Connection Details panel:

    • Select the radio button for Other.
    • In the Scenario field, select SLT SDK from the drop-down menu.
    • Click Next.

  6. On the Specify Transfer Settings panel:

    1. In the Application field of the Data Transfer Settings section, enter /GOOG/SLT_BQ or ZGOOG_SLT_BQ.

    2. In the Job options section, enter starting values in each of the following fields:

      • Number of Data Transfer Jobs
      • Number of Initial Load Jobs
      • Number of Calculation Jobs

    3. In the Replication Options section, select the Real Time radio button.

    4. Click Next.

  7. After reviewing the configuration, click Save.

  8. Make a note of the three-digit ID in the Mass Transfer column. You use it in a later step.

For more information, see the PDF attached to SAP Note 2652704: Replicating Data Using SLT SDK - DMIS 2011 SP17, DMIS 2018 SP02.pdf.

Configure replication in DMIS 2011 SP16, DMIS 2018 SP01, or earlier

The following steps configure replication in earlier versions of SAP LT Replication Server. If you are using a later version, see Configure replication in DMIS 2011 SP17, DMIS 2018 SP02, or later.

  1. In the SAP GUI, enter transaction code LTRC.
  2. Click New. A dialog opens for specifying a new configuration.
  3. In the step Specify Source System:
    • Choose RFC Connection as the connection type.
    • Enter the RFC connection name.
    • Ensure that the field Allow Multiple Usage is selected.
  4. In the step Specify Target System:
    • Enter the connection data to the target system.
    • Choose RFC Connection as the connection type.
    • In the field Scenario for RFC Communication, select the value Write Data to Target Using BAdI from the drop-down list. The RFC connection is automatically set to NONE.
  5. In the step Specify Transfer Settings, press F4 Help. The application that you defined previously is displayed in the Application field.
  6. Make a note of the three-digit ID in the Mass Transfer column. You use it in a later step.

For more information, see the PDF attached to SAP Note 2652704: Replicating Data Using SLT SDK - DMIS 2011 SP15, SP16, DMIS 2018 SP00, SP01.pdf.

Create a mass transfer configuration for BigQuery

Use the custom /GOOG/SLT_SETTINGS transaction to configure a mass transfer for BigQuery and specify the table and field mappings.

Select the initial mass transfer options

When you first enter the /GOOG/SLT_SETTINGS transaction, you select which part of the BigQuery mass transfer configuration you need to edit.

To select the part of the mass transfer configuration:

  1. In the SAP GUI, enter the /GOOG/SLT_SETTINGS transaction preceded by /n:

    /n/GOOG/SLT_SETTINGS

  2. From the Settings Table drop-down menu in the launch screen for the /GOOG/SLT_SETTINGS transaction, select Mass Transfers.

    For a new mass transfer configuration, leave the Mass Transfer Key field blank.

  3. Click the Execute icon. The BigQuery Settings Maintenance - Mass Transfers screen displays.

Specify table creation and other general attributes

In the initial section of a BigQuery mass transfer configuration, you identify the mass transfer configuration and specify the associated client key, as well as certain properties related to the creation of the target BigQuery table.

SAP LT Replication Server saves the mass transfer configuration as a record in the /GOOG/BQ_MASTR custom configuration table.

The fields that you specify in the following steps are required.

  1. In the BigQuery Settings Maintenance - Mass Transfers screen, click the Append Row icon.

  2. In the displayed row, specify the following settings:

    1. In the Mass Transfer Key field, define a name for this transfer. This name becomes the primary key of the mass transfer.
    2. In the Mass Transfer ID field, enter the three-digit ID that was generated when you create the corresponding SAP LT Replication Server replication configuration.
    3. To use the labels or short descriptions of the source fields as the names for the target fields in BigQuery, click the Use Custom Names Flag checkbox. For more information about field names, see Default naming options for fields.

    4. To store the type of change that triggered an insert and to enable the validation of record counts between the source table, SAP LT Replication Server statistics, and the BigQuery table, select the Extra Fields Flag checkbox.

      When this flag is set, BigQuery Connector for SAP adds columns to the BigQuery table schema. For more information, see Extra fields for record changes and count queries.

    5. To stop sending data when a record with a data error is encountered, the Break at First Error Flag checkbox is checked by default. We recommend leaving this checked. For more information, see The BREAK flag.

    6. Optionally, to automatically reduce the chunk size when the byte size of a chunk exceeds the maximum byte size for HTTP requests that BigQuery accepts, click the Dynamic Chunk Size Flag checkbox. For more information about dynamic chunk size, see Dynamic chunk size.

    7. When a record with a data error is encountered, to skip the record and continue inserting records into the BigQuery table, click the Skip Invalid Records Flag checkbox. We recommend leaving this unchecked. For more information, see The SKIP flag.

    8. In the Google Cloud Key Name field, enter the name of the corresponding /GOOG/CLIENT_KEY configuration.

      BigQuery Connector for SAP retrieves the Google Cloud Project Identifier automatically from the /GOOG/CLIENT_KEY configuration.

    9. In the BigQuery Dataset field, enter the name of the target BigQuery dataset that you created earlier in this procedure.

    10. In the Is Setting Active Flag field, enable the mass transfer configuration by clicking the checkbox.

    11. Click Save.

      A mass transfer record is appended in the /GOOG/BQ_MASTR table and the Changed By, Changed On, and Changed At fields are automatically populated.

    12. Click Display Table.

      The new mass transfer record is displayed followed by the table attribute entry panel.

Specify table attributes

You can specify table attributes, such as table name and table partitioning, as well as the number of records to include in each transmission or chunk that is sent to BigQuery, in the second section of the /GOOG/SLT_SETTINGS transaction.

The settings that you specify are stored as a record in the /GOOG/BQ_TABLE configuration table.

These settings are optional.

To specify table attributes:

  1. Click the Append row icon.

  2. In the SAP Table Name field, enter the name of the source SAP table.

  3. In the External Table Name field, enter the name of the target BigQuery table. If the target table doesn't already exist, BigQuery Connector for SAP creates the table with this name. For the BigQuery naming conventions for tables, see Table naming.

  4. To send uncompressed data for all fields in a table, select Send Uncompressed Flag. With this setting enabled, BigQuery Connector for SAP replicates any empty fields in the source records with the values that the fields are initialized with in the source table. For better performance, don't select this flag.

    If you need to send uncompressed data for only specific fields, then don't select Send Uncompressed Flag at the table level. Instead, select Send Uncompressed Flag for those specific fields at field level. This option lets you retain the initial values of specific fields when replicating data to BigQuery, even if you're compressing the rest of the table data. For information about how to modify record compression at field level, see Change record compression at field level.

    For more information about the record compression behavior, see Record compression.

  5. Optionally, in the Chunk Size field, specify the maximum number of records to include in each chunk that is sent to BigQuery. We recommend that you use the default chunk size with BigQuery Connector for SAP, which is 10,000 records. If you need to, you can increase the chunk size up to 50,000 records, which is the maximum chunk size that BigQuery Connector for SAP allows.

    If the source records have a large number of fields, the number of fields can increase the overall byte size of the chunks, which can cause chunk errors. If this occurs, try reducing the chunk size to reduce the byte size. For more information, see Chunk size in the BigQuery Connector for SAP. Alternatively, to automatically adjust the chunk size, enable dynamic chunk size. For more information, see Dynamic chunk size.

  6. Optionally, in the Partition Type field, specify an increment of time to use for partitioning. Valid values are HOUR, DAY, MONTH, or YEAR. For more information, see Table partitioning.

  7. Optionally, in the Partition Field field, specify the name of a field in the target BigQuery table that contains a timestamp to use for partitioning. When you specify Partition Field, you must also specify Partition Type. For more information, see Table partitioning.

  8. In the Is Setting Active Flag field, enable the table attributes by clicking the checkbox. If the Is Setting Active Flag box is not checked, BigQuery Connector for SAP creates the BigQuery table with the name of the SAP source table, the default chunk size, and no partitioning.

  9. Click Save.

    Your attributes are stored as a record in the /GOOG/BQ_TABLE configuration table and the Changed By, Changed On, and Changed At fields are automatically populated.

  10. Click Display Fields.

    The new table attribute record is displayed, followed by the field mapping entry panel.

Customize the default field mapping

If the source SAP table contains timestamp fields or booleans, change the default data type mapping to accurately reflect the data type in the target BigQuery table.

You can also change other data types, as well as the names that are used for target fields.

You can edit the default mapping directly in the SAP GUI or you can export the default mapping to a spreadsheet or a text file so that others can edit the values without requiring access to SAP LT Replication Server.

For more information about the default field mapping and the changes you can make, see Field mapping.

To customize the default mapping for the target BigQuery fields:

  1. In the BigQuery Settings Maintenance - Fields page of the transaction /GOOG/SLT_SETTINGS, display the default field mappings for the mass transfer you are configuring.

  2. Edit the default target data types in the External Data Element column as needed. In particular, change the target data type for the following data types:

    • Timestamps. Change the default target data type from NUMERIC to TIMESTAMP or TIMESTAMP (LONG).
    • Booleans. Change the default target data type from STRING to BOOLEAN.
    • Hexadecimals. Change the default target data type from STRING to BYTES.

    To edit the default data type mapping:

    1. On the row of the field that you need to edit, click the External Data Element field.
    2. In the dialog for data types, select the BigQuery data type that you need.
    3. Confirm your changes, and then click Save.

  3. If you specified the Custom Names flag in the BigQuery Settings Maintenance page, edit the default target field names in the Temporary Field Name column as needed.

    The values that you specify override the default names that are shown in the External Field Name column.

  4. Edit the default target field descriptions in the Field Description column as needed.

  5. Optionally, export the field map for external editing. For instructions, see Edit the BigQuery field map in a CSV file.

  6. After all changes are complete and any externally edited values have been uploaded, confirm that the Is Setting Active Flag checkbox is selected. If Is Setting Active Flag is not selected, BigQuery Connector for SAP creates target tables with the default values.

  7. Click Save.

    The changes are stored in the /GOOG/BQ_FIELD configuration table and the Changed By, Changed On, and Changed At fields are automatically populated.

Change record compression at field level

To improve replication performance, the BigQuery Connector for SAP compresses records by omitting all empty fields in the source record, which are then initialized with null in the target table in BigQuery. However, if you need to replicate some empty fields with their initial values to BigQuery while still using record compression, then you can select Send Uncompressed Flag for those specific fields.

For more information about the record compression behavior, see Record compression.

To change record compression at field level, complete the following steps:

  1. In the BigQuery Settings Maintenance - Fields page of the transaction /GOOG/SLT_SETTINGS, display the list of fields for the table whose mass transfer you are configuring.

  2. To send uncompressed data for a field, select Send Uncompressed Flag corresponding to the field.

  3. Click Save.

Test replication

Test the replication configuration by starting data provisioning:

  1. Open the SAP LT Replication Server Cockpit (transaction LTRC) in the SAP GUI.

  2. Click on the mass transfer configuration for the table replication that you are testing.

  3. Click Data Provisioning.

  4. In the Data Provisioning panel, start data provisioning:

    1. Enter the name of the source table.
    2. Click the radio button for the type of data provisioning that you want to test. For example, Start Load.

    3. Click the Execute icon. The data transfer begins and the progress is displayed on the Participating objects screen.

      If the table doesn't exist in BigQuery, the BigQuery Connector for SAP creates the table from a schema that it builds from the table and field attributes that you previously defined with the /GOOG/SLT_SETTINGS transaction.

      The length of time that an initial load of a table takes depends on the size of the table and its records.

      Messages are written to the SAP LT Replication Server Application Logs section in transaction LTRC.

Alternatively, you can test the replication to BigQuery by using the Load Simulation tool. For more information, see Load Simulation tool.

Validate replication

You can validate replication using the following methods:

  • In SAP LT Replication Server:
    • Monitor the replication on the Data Provisioning screen.
    • Check for error messages in the Application Logs screen.
  • On the table information tab in BigQuery:
    • Check the Schema tab to ensure that the schema looks right.
    • Check the Preview tab to see a preview of the inserted rows.
    • Check the Details tab for the number of rows inserted, the size of the table, and other information.
  • If the Extra Fields Flag checkbox was selected when the BigQuery table was configured, run the Replication Validation tool by entering the /GOOG/REPLIC_VALID custom transaction.

Check replication in SAP LT Replication Server

Use transaction LTRC to see the progress of initial load or replication jobs after you start them and to check for error messages.

You can see the status of the load under the Load Statistics tab and the progress of the job under the Data Transfer Monitor tab in SAP LT Replication Server.

On the Application Logs screen of transaction LTRC, you can see all of the messages that are returned by BigQuery, the BigQuery Connector for SAP, and SAP LT Replication Server.

Messages that are issued by BigQuery Connector for SAP code in SAP LT Replication Server start with the prefix /GOOG/SLT. Messages that are returned from the BigQuery API start with the prefix /GOOG/MSG.

Messages that are returned by SAP LT Replication Server do not start with a /GOOG/ prefix.

Check replication in BigQuery

In the Google Cloud console, confirm that the table was created and that BigQuery is inserting data into it.

  1. In the Google Cloud console, go to the BigQuery page.

    Go to BigQuery

  2. In the search field of the Explorer section, type the name of the target BigQuery table, and then press Enter.

    The table information is displayed under a tab in the content pane on the right side of the page.

  3. In the table information section, click the following headings to check the table and row insertion:

    • Preview, which shows the rows and fields that are inserted into the BigQuery table.
    • Schema, which shows the field names and data types.
    • Details, which shows the table size, the total number of rows, and other details.

Run the Replication Validation tool

If the Extra Fields Flag was selected when the BigQuery table was configured, you can use the Replication Validation tool to generate reports that compare the number of records in the BigQuery table with record counts in the SAP LT Replication Server statistics or the source table.

To run the Replication Validation tool:

  1. In the SAP GUI, enter the /GOOG/REPLIC_VALID transaction preceded by /n:

    /n/GOOG/REPLIC_VALID

  2. In the Processing Options section, click the Execute Validation radio button.

  3. In the Selection Options section, enter the following specifications:

    • From the drop-down menu in the GCP Partner Identifier field, select BigQuery.
    • From the drop-down menu in the Check Type field, select the type of report to generate:
      • Initial Load Counts
      • Replication Counts
      • Current Counts
    • If the Check Date field is displayed, specify the date that you need the counts for.
    • In the Mass Transfer Key field, enter the mass transfer configuration name.
    • Optionally, in the Tables Names field, specify the table names in the mass transfer configuration for which you need to generate the report.

  4. Run the Replication Validation tool by clicking the Execute icon.

  5. After the validation check is complete, in the Processing Options section, display the report by clicking the Display Report radio button and then clicking the Execute icon.

For more information, see Replication Validation tool.

Troubleshooting

For information about diagnosing and resolving issues that you might encounter when you configure and run loads or replications between SAP and BigQuery with BigQuery Connector for SAP, see BigQuery Connector for SAP troubleshooting guide.

Get support

If you need help resolving problems with replication and the BigQuery Connector for SAP, collect all available diagnostic information and contact Cloud Customer Care. For information about contacting Customer Care, see Getting support for SAP on Google Cloud.