Learn how to use OCI GoldenGate Data Replication and Data Transforms deployments together to load and transform data between two Autonomous AI Databases.

To successfully complete this quickstart you need:

• A source Autonomous AI Database with sample data loaded, and supplemental logging enabled.

  Tip:

  You can download the OCI GoldenGate sample data, if you need sample data to work with.

  • Use the Autonomous AI Database's Database actions SQL tool to run the two scripts to create the user schema and tables.
  • Use the SQL tool to enable supplemental logging.

  Follow the steps in Lab 1, Task 3: Load the ATP schema for more details.
• Unlock the GGADMIN user on the source Autonomous AI Database instance
  1. On the Autonomous AI Database Details page, select Database Users from the Database actions menu.

     Tip:

     Use the Autonomous AI Database administrator credentials provided when you created the instance to log in, if prompted.
  2. Locate the GGADMIN user, and then select Edit from its ellipsis (three dots) menu.
  3. In the Edit User panel, enter a password, confirm that password, and then deselect Account is Locked.
  4. Click Apply Changes.

1. Create a Data Replication deployment.
2. Create a source Oracle Autonomous AI Transaction Processing (ATP) connection.
3. Create a target Autonomous AI Lakehouse (ALK) connection.
4. Assign a connection to the deployment.
5. Use the SQL tool to enable supplemental logging:

   ALTER DATABASE ADD SUPPLEMENTAL LOG DATA

6. Run the following query in the SQL tool to ensure that support_mode=FULL for all tables in the source database:

   
   select * from DBA_GOLDENGATE_SUPPORT_MODE where owner = 'SRC_OCIGGLL';

1. On the deployment Details page, click Launch console.
2. If required, enter oggadmin for User name and the password you used when creating the deployment, and then click Sign In.
3. Add Transaction Data and a Checkpoint Table:
   1. Open the navigation menu and then click DB Connections.
   2. Click Connect to database SourceDB.
   3. In the navigation menu, click Trandata, and then click Add Trandata (plus icon).
   4. For Schema Name, enter SRC_OCIGGLL, and then click Submit.
   5. To verify, enter SRC_OCIGGLL into the Search field and click Search.
   6. Open the navigation menu and then click DB Connections.
   7. Click Connect to database TargetDB.
   8. In the navigation menu, click Checkpoint, and then click Add Checkpoint (plus icon).
   9. For Checkpoint Table, enter "SRCMIRROR_OCIGGLL"."CHECKTABLE", and then click Submit.
4. Add an Extract.

   Note:

   See additional extract parameter options for more information about parameters that you can use to specify source tables.

   On the Extract Parameters page, append the following lines under EXTTRAIL <trail-name>:

   -- Capture DDL operations for listed schema tables
   ddl include mapped
   
   -- Add step-by-step history of 
   -- to the report file. Very useful when troubleshooting.
   ddloptions report 
   
   -- Write capture stats per table to the report file daily.
   report at 00:01 
   
   -- Rollover the report file weekly. Useful when IE runs
   -- without being stopped/started for long periods of time to
   -- keep the report files from becoming too large.
   reportrollover at 00:01 on Sunday 
   
   -- Report total operations captured, and operations per second
   -- every 10 minutes.
   reportcount every 10 minutes, rate 
   
   -- Table list for capture
   table SRC_OCIGGLL.*;

5. Check for long running transactions. Run the following script on your source database:

   select start_scn, start_time from gv$transaction where start_scn < (select max(start_scn) from dba_capture);

   If the query returns any rows, then you must locate the transaction's SCN and then either commit or rollback the transaction.

1. Create an Oracle Object Store bucket.

   Take note of the namespace and bucket name for use with the Export and Import scripts.

2. Create an Auth Token, and then copy and paste the token string to a text editor for later use.
3. Create a credential in your source database, replacing the <user-name> and <token> with your Oracle Cloud account username and the token string you created in the previous step:

   BEGIN
     DBMS_CLOUD.CREATE_CREDENTIAL(
       credential_name => 'ADB_OBJECTSTORE', 
       username => '<user-name>',
       password => '<token>'
     );
   END;

4. Run the following script in your source database to create the Export Data job. Ensure that you replace the <region>, <namespace>, and <bucket-name> in Object Store URI accordingly. SRC_OCIGGLL.dmp is a file that will be created when this script runs.

   DECLARE
   ind NUMBER;              -- Loop index
   h1 NUMBER;               -- Data Pump job handle
   percent_done NUMBER;     -- Percentage of job complete
   job_state VARCHAR2(30);  -- To keep track of job state
   le ku$_LogEntry;         -- For WIP and error messages
   js ku$_JobStatus;        -- The job status from get_status
   jd ku$_JobDesc;          -- The job description from get_status
   sts ku$_Status;          -- The status object returned by get_status
   
   BEGIN
   -- Create a (user-named) Data Pump job to do a schema export.
   h1 := DBMS_DATAPUMP.OPEN('EXPORT','SCHEMA',NULL,'SRC_OCIGGLL_EXPORT','LATEST');
   
   -- Specify a single dump file for the job (using the handle just returned
   -- and a directory object, which must already be defined and accessible
   -- to the user running this procedure.
   DBMS_DATAPUMP.ADD_FILE(h1,'https://objectstorage.<region>.oraclecloud.com/n/<namespace>/b/<bucket-name>/o/SRC_OCIGGLL.dmp','ADB_OBJECTSTORE','100MB',DBMS_DATAPUMP.KU$_FILE_TYPE_URIDUMP_FILE,1);
   
   -- A metadata filter is used to specify the schema that will be exported.
   DBMS_DATAPUMP.METADATA_FILTER(h1,'SCHEMA_EXPR','IN (''SRC_OCIGGLL'')');
   
   -- Start the job. An exception will be generated if something is not set up properly.
   DBMS_DATAPUMP.START_JOB(h1);
   
   -- The export job should now be running. In the following loop, the job
   -- is monitored until it completes. In the meantime, progress information is displayed.
   percent_done := 0;
   job_state := 'UNDEFINED';
   while (job_state != 'COMPLETED') and (job_state != 'STOPPED') loop
     dbms_datapump.get_status(h1,dbms_datapump.ku$_status_job_error + dbms_datapump.ku$_status_job_status + dbms_datapump.ku$_status_wip,-1,job_state,sts);
     js := sts.job_status;
   
   -- If the percentage done changed, display the new value.
   if js.percent_done != percent_done
   then
     dbms_output.put_line('*** Job percent done = ' || to_char(js.percent_done));
     percent_done := js.percent_done;
   end if;
   
   -- If any work-in-progress (WIP) or error messages were received for the job, display them.
   if (bitand(sts.mask,dbms_datapump.ku$_status_wip) != 0)
   then
     le := sts.wip;
   else
     if (bitand(sts.mask,dbms_datapump.ku$_status_job_error) != 0)
     then
       le := sts.error;
     else
       le := null;
     end if;
   end if;
   if le is not null
   then
     ind := le.FIRST;
     while ind is not null loop
       dbms_output.put_line(le(ind).LogText);
       ind := le.NEXT(ind);
     end loop;
   end if;
     end loop;
   
     -- Indicate that the job finished and detach from it.
     dbms_output.put_line('Job has completed');
     dbms_output.put_line('Final job state = ' || job_state);
     dbms_datapump.detach(h1);
   END;

1. Create a credential in your target database to access Oracle Object Store (using the same information in the preceding section).

   BEGIN
     DBMS_CLOUD.CREATE_CREDENTIAL( 
       credential_name => 'ADB_OBJECTSTORE',
       username => '<user-name>',
       password => '<token>'
     );
   END;

2. Run the following script in your target database to import data from the SRC_OCIGGLL.dmp. Ensure that you replace the <region>, <namespace>, and <bucket-name> in Object Store URI accordingly:

   DECLARE
   ind NUMBER;  -- Loop index
   h1 NUMBER;  -- Data Pump job handle
   percent_done NUMBER;  -- Percentage of job complete
   job_state VARCHAR2(30);  -- To keep track of job state
   le ku$_LogEntry;  -- For WIP and error messages
   js ku$_JobStatus;  -- The job status from get_status
   jd ku$_JobDesc;  -- The job description from get_status
   sts ku$_Status;  -- The status object returned by get_status
   BEGIN
   
   -- Create a (user-named) Data Pump job to do a "full" import (everything
   -- in the dump file without filtering).
   h1 := DBMS_DATAPUMP.OPEN('IMPORT','FULL',NULL,'SRCMIRROR_OCIGGLL_IMPORT');
   
   -- Specify the single dump file for the job (using the handle just returned)
   -- and directory object, which must already be defined and accessible
   -- to the user running this procedure. This is the dump file created by
   -- the export operation in the first example.
   
   DBMS_DATAPUMP.ADD_FILE(h1,'https://objectstorage.<region>.oraclecloud.com/n/<namespace>/b/<bucket-name>/o/SRC_OCIGGLL.dmp','ADB_OBJECTSTORE',null,DBMS_DATAPUMP.KU$_FILE_TYPE_URIDUMP_FILE);
   
   
   -- A metadata remap will map all schema objects from SRC_OCIGGLL to SRCMIRROR_OCIGGLL.
   DBMS_DATAPUMP.METADATA_REMAP(h1,'REMAP_SCHEMA','SRC_OCIGGLL','SRCMIRROR_OCIGGLL');
   
   -- If a table already exists in the destination schema, skip it (leave
   -- the preexisting table alone). This is the default, but it does not hurt
   -- to specify it explicitly.
   DBMS_DATAPUMP.SET_PARAMETER(h1,'TABLE_EXISTS_ACTION','SKIP');
   
   -- Start the job. An exception is returned if something is not set up properly.
   DBMS_DATAPUMP.START_JOB(h1);
   
   -- The import job should now be running. In the following loop, the job is
   -- monitored until it completes. In the meantime, progress information is
   -- displayed. Note: this is identical to the export example.
   percent_done := 0;
   job_state := 'UNDEFINED';
   while (job_state != 'COMPLETED') and (job_state != 'STOPPED') loop
     dbms_datapump.get_status(h1,
       dbms_datapump.ku$_status_job_error +
       dbms_datapump.ku$_status_job_status +
       dbms_datapump.ku$_status_wip,-1,job_state,sts);
       js := sts.job_status;
   
     -- If the percentage done changed, display the new value.
     if js.percent_done != percent_done
     then
       dbms_output.put_line('*** Job percent done = ' ||
       to_char(js.percent_done));
       percent_done := js.percent_done;
     end if;
   
     -- If any work-in-progress (WIP) or Error messages were received for the job, display them.
     if (bitand(sts.mask,dbms_datapump.ku$_status_wip) != 0)
     then
       le := sts.wip;
     else
       if (bitand(sts.mask,dbms_datapump.ku$_status_job_error) != 0)
       then
         le := sts.error;
       else
         le := null;
       end if;
     end if;
     if le is not null
     then
       ind := le.FIRST;
       while ind is not null loop
         dbms_output.put_line(le(ind).LogText);
         ind := le.NEXT(ind);
       end loop;
     end if;
   end loop;
   
   -- Indicate that the job finished and gracefully detach from it.
   dbms_output.put_line('Job has completed');
   dbms_output.put_line('Final job state = ' || job_state);
   dbms_datapump.detach(h1);
   END;

1. Add and run a Replicat.
   On the Parameter File screen, replace MAP *.*, TARGET *.*; with the following script:

   -- Capture DDL operations for listed schema tables
   --
   ddl include mapped
   --
   -- Add step-by-step history of ddl operations captured
   -- to the report file. Very useful when troubleshooting.
   --
   ddloptions report
   --
   -- Write capture stats per table to the report file daily.
   --
   report at 00:01
   --
   -- Rollover the report file weekly. Useful when PR runs
   -- without being stopped/started for long periods of time to
   -- keep the report files from becoming too large.
   --
   reportrollover at 00:01 on Sunday
   --
   -- Report total operations captured, and operations per second
   -- every 10 minutes.
   --
   reportcount every 10 minutes, rate
   --
   -- Table map list for apply
   --
   DBOPTIONS ENABLE_INSTANTIATION_FILTERING;
   MAP SRC_OCIGGLL.*, TARGET SRCMIRROR_OCIGGLL.*;

   Note:

   DBOPTIONS ENABLE_INSTATIATION_FILTERING enables CSN filtering on tables imported using Oracle Data Pump. For more information, see DBOPTIONS Reference.
2. Perform Inserts to the source database:
   1. Return to the Oracle Cloud console and use the navigation menu to navigate back to Oracle AI Database, Autonomous AI Transaction Processing, and then SourceDB.
   2. On the SourceDB Details page, click Database actions, and then click SQL.
   3. Enter the following inserts, and then click Run Script:

      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1000,'Houston',20,743113);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1001,'Dallas',20,822416);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1002,'San Francisco',21,157574);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1003,'Los Angeles',21,743878);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1004,'San Diego',21,840689);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1005,'Chicago',23,616472);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1006,'Memphis',23,580075);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1007,'New York City',22,124434);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1008,'Boston',22,275581);
      Insert into SRC_OCIGGLL.SRC_CITY (CITY_ID,CITY,REGION_ID,POPULATION) values (1009,'Washington D.C.',22,688002);

   4. In the OCI GoldenGate Deployment Console, click the Extract name (UAEXT), and then click Statistics. Verify that SRC_OCIGGLL.SRC_CITY is listed with 10 inserts.
   5. Go back to the Overview screen, click the Replicat name (REP), and then click Statistics. Verify that SRCMIRROR_OCIGGLL.SRC_CITY is listed with 10 inserts

1. Create a Data Transforms deployment.
2. Create a Generic connection.

   Note:

   For example, for Autonomous Databases in US East (Ashburn) use the following values:

   • For Host, enter adb.us-ashburn-1.oraclecloud.com:1522.
   • For Subnet, select the same subnet as the deployment from the dropdown.
3. Assign the Generic connection to the deployment.
4. Create TRG_CUSTOMER in SRCMIRROR_OCIGGLL in your Autonomous Data Warehouse (ADW) instance:
   1. In the Oracle Cloud console, open the navigation menu, navigate to Oracle Database, and then select Autonomous Data Warehouse.
   2. On the Autonomous Databases page, click on your ADW instance.
   3. On the ADW Autonomous Database details page, click Database actions, and then select SQL from the dropdown. If the Database actions menu takes too long to load, you can click Database actions directly, and then select SQL from the Database actions page.
   4. Enter the following into the Worksheet, and then click Run Statement.

      create table SRCMIRROR_OCIGGLL.TRG_CUSTOMER (
         CUST_ID              NUMBER(10,0)     not null,
         DEAR                 VARCHAR2(4 BYTE),
         CUST_NAME            VARCHAR2(50 BYTE),
         ADDRESS              VARCHAR2(100 BYTE),
         CITY_ID              NUMBER(10,0),
         PHONE                VARCHAR2(50 BYTE),
         AGE                  NUMBER(3,0),
         AGE_RANGE            VARCHAR2(50 BYTE),
         SALES_PERS           VARCHAR2(50 BYTE),
         CRE_DATE             DATE,
         UPD_DATE             DATE,
         constraint PK_TRG_CUSTOMER primary key (CUST_ID)
      );

5. Launch the Data Transforms deployment console:
   1. Navigate back to the Deployments page, and then select the deployment you created in Task 6.
   2. On the Deployment details page, click Launch console.
   3. Log in to the Data Transforms deployment console.
6. Create ADW Connection:
   1. Open the navigation menu, click Connections, and then click Create Connection.
   2. On the Select Type page, under Databases select Oracle, and then click Next.
   3. On the Connection details page, complete the form fields as follows, and then click Create:
      1. For Name, enter ADW_IAD.
      2. Select Use Credential File.
      3. For Wallet File, upload your (ADW) wallet file.

         Note:

         To download your ADW wallet file, click Database Connection on the ADW details page.
      4. From the Services dropdown, select <name>_low.
      5. For User, enter ADMIN.
      6. For Password, enter your ADW password.
7. Import Data Entity:
   1. Open the navigation menu, click Data Entities, and then click Import Data Entity.
   2. For Connection, select ADW_IAD from the dropdown.
   3. For Schema, select SRCMIRROR_OCIGGLL from the dropdown.
   4. Click Start.
8. Create Project:
   1. Open the navigation menu, click Projects.
   2. On the Projects page, click Create Project.
   3. In the Create Project dialog, for Name, enter demo-pipeline, and then click Create.

1. Create Data Flow:

   Note:

   Learn more about the Data Flow Editor.
   1. Select the name of your project.
   2. On the Project Details page, under Resources, click Data Flows, and then click Create Data Flow.
   3. In the Create Data Flow dialog, for Name, enter Load TRG_CUSTOMER, and optionally, a description. Click Create. The design canvas opens.
   4. On the Add a Schema dialog, complete the form fields as follows, and then click OK:
      1. For Connection, select ADW_IAD from the dropdown.
      2. For Schema, select SRCMIRROR_OCIGGLL from the dropdown.
   5. Drag the following data entities and components onto the design canvas:
      1. In the Data Entities panel, expand the SRCMIRROR_OCIGGLL schema. Drag the SRC_AGE_GROUP data entity to the design canvas.
      2. In the Data Entities panel, expand the SRCMIRROR_OCIGGLL schema. Drag the SRC_SALES_PERSON data entity to the design canvas.
      3. From the Data Transform toolbar, drag the Lookup component to the design canvas.
      4. From the Data Transform toolbar, drag the Join component to the design canvas.
      5. In the Data Entities panel, under SRCMIRROR_OCIGGLL, drag the SRC_CUSTOMER data entity to the design canvas.
   6. Connect the following data entities to the Lookup component:
      1. Click on the SRC_AGE_GROUP Connector icon and drag the icon to Lookup component.
      2. Click on the SRC_CUSTOMER Connector icon and drag the icon to the Lookup component.
   7. On the design canvas, click Lookup to open the Lookup panel. In the Lookup panel, switch to the Attributes tab and then paste the following query into Lookup Condition:

      SRC_CUSTOMER.AGE between SRC_AGE_GROUP.AGE_MIN and SRC_AGE_GROUP.AGE_MAX

   8. Connect the following components to the Join component:
      1. Click on the SRC_SALES_PERSON Connector icon and drag the icon to the Join component.
      2. Click on the Lookup Connector icon and drag the icon to the Join component.
   9. On the design canvas, click Join to open the Join panel. In the Join panel, switch to the Attributes tab and then paste the following query into Join Condition:

      SRC_CUSTOMER.SALES_PERS_ID=SRC_SALES_PERSON.SALES_PERS_ID

   10. Drag the following data entity and component onto the design canvas:
       1. In the Data Entities panel, under SRCMIRROR_OCIGGLL, drag the TRG_CUSTOMER data entity to the design canvas.
       2. Click on the Join Connector icon and drag the icon to the TRG_CUSTOMER data entity.
       3. On the design canvas, click TRG_CUSTOMER and expand the data entity.
   11. On the Attributes tab, enable Key for CUST_ID, and disable Update for CRE_DATE and disable Insert for UPD_DATE.
   12. On the Column Mapping tab, ensure the Name matches the Expression:
       1. CUST_ID

          SRC_CUSTOMER.CUSTID

       2. DEAR

          CASE WHEN SRC_CUSTOMER.DEAR = 0 THEN 'Mr' WHEN SRC_CUSTOMER.DEAR = 1 THEN 'Mrs' ELSE 'Ms' END

       3. CUST_NAME

          SRC_CUSTOMER.FIRST_NAME || ' ' || UPPER(SRC_CUSTOMER.LAST_NAME)

       4. SALES_PERS

          SRC_SALES_PERSON.FIRST_NAME || ' ' ||UPPER(SRC_SALES_PERSON.LAST_NAME)

       5. CRE_DATE

          SYSDATE

       6. UPD_DATE

          SYSDATE

       7. Use other mappings as-is.
   13. On the Options tab, for Mode, select Incremental Update from the dropdown.
   14. Collapse TRG_CUSTOMER.
   15. Click Save Data Flow.
2. Create Workflow:
   1. Select the name of your project, select Workflows, and then select Create Workflow.
   2. For name, enter Orchestrate Data Warehouse Load. Click Create.
   3. Drag the SQL icon on the design canvas.
   4. Double click the SQL step in the editor to open the step properties page.
   5. On the General tab, for name, enter Data Cleansing.
   6. Select the Attributes tab, for Connection, select ADW_IAD from the dropdown.
   7. For SQL, copy the following query:

      delete from SRCMIRROR_OCIGGLL.TRG_CUSTOMER where CITY_ID > 110

   8. Collapse SQL.
   9. Under Data Flows, drag the TRG_CUSTOMER Data Flow to the design canvas.
   10. Click on the Data Cleansing SQL workflow line and drag the ok (green arrow) icon to the TRG_CUSTOMER Data Flow.
   11. Click Save Workflow, and then click Start Workflow.
3. Create and Manage Jobs.