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  • Tonic Structural User Guide
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    • Structural data generation workflow
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  • Creating and managing workspaces
    • Managing workspaces
      • Viewing your list of workspaces
      • Creating, editing, or deleting a workspace
      • Workspace configuration settings
        • Workspace identification and connection type
        • Data connection settings
        • Configuring secrets managers for database connections
        • Data generation settings
        • Enabling and configuring upsert
        • Writing output to Tonic Ephemeral
        • Writing output to a container repository
        • Advanced workspace overrides
      • About the workspace management view
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      • Assigning tags to a workspace
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  • Configuring data generation
    • Privacy Hub
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      • Performing scans on collections
      • Using Collection View
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      • Running the Structural sensitivity scan
      • Manually indicating whether a column is sensitive
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        • Enabling consistency
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      • Reviewing and applying recommended generators
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      • Document View for file connector JSON columns
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      • About subsetting
      • Using table filtering for data warehouses and Spark-based data connectors
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    • Using the Privacy Report to verify data protection
  • Running data generation
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  • Installing and Administering Structural
    • Structural architecture
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    • Deploying a self-hosted Structural instance
      • Deployment checklist
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      • Deploying with Docker Compose
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      • Enabling the option to write output data to a container repository
        • Setting up a Kubernetes cluster to use to write output data to a container repository
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      • Entering and updating your license key
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    • Using Structural Cloud
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        • GitHub
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  • Connecting to your data
    • About data connectors
    • Overview for database administrators
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    • Amazon DynamoDB
      • System requirements and limitations for DynamoDB
      • Structural differences and limitations with DynamoDB
      • Before you create a DynamoDB workspace
      • Configuring DynamoDB workspace data connections
    • Amazon EMR
      • Structural process overview for Amazon EMR
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      • Structural differences and limitations with Amazon EMR
      • Before you create an Amazon EMR workspace
        • Creating IAM roles for Structural and Amazon EMR
        • Creating Athena workgroups
        • Configuration for cross-account setups
      • Configuring Amazon EMR workspace data connections
    • Amazon Redshift
      • Structural process overview for Amazon Redshift
      • Structural differences and limitations with Amazon Redshift
      • Before you create an Amazon Redshift workspace
        • Required AWS instance profile permissions for Amazon Redshift
        • Setting up the AWS Lambda role for Amazon Redshift
        • AWS KMS permissions for Amazon SQS message encryption
        • Amazon Redshift-specific Structural environment settings
        • Source and destination database permissions for Amazon Redshift
      • Configuring Amazon Redshift workspace data connections
    • Databricks
      • Structural process overview for Databricks
      • System requirements for Databricks
      • Structural differences and limitations with Databricks
      • Before you create a Databricks workspace
        • Granting access to storage
        • Setting up your Databricks cluster
        • Configuring the destination database schema creation
      • Configuring Databricks workspace data connections
    • Db2 for LUW
      • System requirements for Db2 for LUW
      • Structural differences and limitations with Db2 for LUW
      • Before you create a Db2 for LUW workspace
      • Configuring Db2 for LUW workspace data connections
    • File connector
      • Overview of the file connector process
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      • Structural differences and limitations with the file connector
      • Before you create a file connector workspace
      • Configuring the file connector storage type and output options
      • Managing file groups in a file connector workspace
      • Downloading generated file connector files
    • Google BigQuery
      • Structural differences and limitations with Google BigQuery
      • Before you create a Google BigQuery workspace
      • Configuring Google BigQuery workspace data connections
      • Resolving schema changes for de-identified views
    • MongoDB
      • System requirements for MongoDB
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    • MySQL
      • System requirements for MySQL
      • Before you create a MySQL workspace
      • Configuring MySQL workspace data connections
    • Oracle
      • Known limitations for Oracle schema objects
      • System requirements for Oracle
      • Structural differences and limitations with Oracle
      • Before you create an Oracle workspace
      • Configuring Oracle workspace data connections
    • PostgreSQL
      • System requirements for PostgreSQL
      • Before you create a PostgreSQL workspace
      • Configuring PostgreSQL workspace data connections
    • Salesforce
      • System requirements for Salesforce
      • Structural differences and limitations with Salesforce
      • Before you create a Salesforce workspace
      • Configuring Salesforce workspace data connections
    • Snowflake on AWS
      • Structural process overviews for Snowflake on AWS
      • Structural differences and limitations with Snowflake on AWS
      • Before you create a Snowflake on AWS workspace
        • Required AWS instance profile permissions for Snowflake on AWS
        • Other configuration for Lambda processing
        • Source and destination database permissions for Snowflake on AWS
        • Configuring whether Structural creates the Snowflake on AWS destination database schema
      • Configuring Snowflake on AWS workspace data connections
    • Snowflake on Azure
      • Structural process overview for Snowflake on Azure
      • Structural differences and limitations with Snowflake on Azure
      • Before you create a Snowflake on Azure workspace
      • Configuring Snowflake on Azure workspace data connections
    • Spark SDK
      • Structural process overview for the Spark SDK
      • Structural differences and limitations with the Spark SDK
      • Configuring Spark SDK workspace data connections
      • Using Spark to run de-identification of the data
    • SQL Server
      • System requirements for SQL Server
      • Before you create a SQL Server workspace
      • Configuring SQL Server workspace data connections
    • Yugabyte
      • System requirements for Yugabyte
      • Structural differences and limitations with Yugabyte
      • Before you create a Yugabyte workspace
      • Configuring Yugabyte workspace data connections
      • Troubleshooting Yugabyte data generation issues
  • Using the Structural API
    • About the Structural API
    • Getting an API token
    • Getting the workspace ID
    • Using the Structural API to perform tasks
      • Configure environment settings
      • Manage generator presets
        • Retrieving the list of generator presets
        • Structure of a generator preset
        • Creating a custom generator preset
        • Updating an existing generator preset
        • Deleting a generator preset
      • Manage custom sensitivity rules
      • Create a workspace
      • Connect to source and destination data
      • Manage file groups in a file connector workspace
      • Assign table modes and filters to source database tables
      • Set column sensitivity
      • Assign generators to columns
        • Getting the generator IDs and available metadata
        • Updating generator configurations
        • Structure of a generator assignment
        • Generator API reference
          • Address (AddressGenerator)
          • Algebraic (AlgebraicGenerator)
          • Alphanumeric String Key (AlphaNumericPkGenerator)
          • Array Character Scramble (ArrayTextMaskGenerator)
          • Array JSON Mask (ArrayJsonMaskGenerator)
          • Array Regex Mask (ArrayRegexMaskGenerator)
          • ASCII Key (AsciiPkGenerator)
          • Business Name (BusinessNameGenerator)
          • Categorical (CategoricalGenerator)
          • Character Scramble (TextMaskGenerator)
          • Character Substitution (StringMaskGenerator)
          • Company Name (CompanyNameGenerator)
          • Conditional (ConditionalGenerator)
          • Constant (ConstantGenerator)
          • Continuous (GaussianGenerator)
          • Cross Table Sum (CrossTableAggregateGenerator)
          • CSV Mask (CsvMaskGenerator)
          • Custom Categorical (CustomCategoricalGenerator)
          • Date Truncation (DateTruncationGenerator)
          • Email (EmailGenerator)
          • Event Timestamps (EventGenerator)
          • File Name (FileNameGenerator)
          • Find and Replace (FindAndReplaceGenerator)
          • FNR (FnrGenerator)
          • Geo (GeoGenerator)
          • HIPAA Address (HipaaAddressGenerator)
          • Hostname (HostnameGenerator)
          • HStore Mask (HStoreMaskGenerator)
          • HTML Mask (HtmlMaskGenerator)
          • Integer Key (IntegerPkGenerator)
          • International Address (InternationalAddressGenerator)
          • IP Address (IPAddressGenerator)
          • JSON Mask (JsonMaskGenerator)
          • MAC Address (MACAddressGenerator)
          • Mongo ObjectId Key (ObjectIdPkGenerator)
          • Name (NameGenerator)
          • Noise Generator (NoiseGenerator)
          • Null (NullGenerator)
          • Numeric String Key (NumericStringPkGenerator)
          • Passthrough (PassthroughGenerator)
          • Phone (USPhoneNumberGenerator)
          • Random Boolean (RandomBooleanGenerator)
          • Random Double (RandomDoubleGenerator)
          • Random Hash (RandomStringGenerator)
          • Random Integer (RandomIntegerGenerator)
          • Random Timestamp (RandomTimestampGenerator)
          • Random UUID (UUIDGenerator)
          • Regex Mask (RegexMaskGenerator)
          • Sequential Integer (UniqueIntegerGenerator)
          • Shipping Container (ShippingContainerGenerator)
          • SIN (SINGenerator)
          • SSN (SsnGenerator)
          • Struct Mask (StructMaskGenerator)
          • Timestamp Shift (TimestampShiftGenerator)
          • Unique Email (UniqueEmailGenerator)
          • URL (UrlGenerator)
          • UUID Key (UuidPkGenerator)
          • XML Mask (XmlMaskGenerator)
      • Configure subsetting
      • Check for and resolve schema changes
      • Run data generation jobs
      • Schedule data generation jobs
    • Example script: Starting a data generation job
    • Example script: Polling for a job status and creating a Docker package
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On this page
  • Creating the source database user
  • TONIC_ORACLE_DBLINK_ENABLED is false (default)
  • TONIC_ORACLE_DBLINK_ENABLED is true
  • Creating the destination database user and schema
  • Configuring whether Structural creates the destination database schema

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  1. Connecting to your data
  2. Oracle

Before you create an Oracle workspace

Last updated 4 months ago

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Creating the source database user

This is the Oracle user that connects to the source database.

The source database user can be the same as the schema of the data. However, we recommend that you create a Tonic Structural-specific user that has more restricted or read-only access.

TheTONIC_ORACLE_DBLINK_ENABLED environment setting is deprecated and eventually will be removed. When that happens, Structural will no longer create a database link between the source and destination databases during data generation runs.

The details for providing the required access are slightly different based on whether you use database links.

By default, Structural assumes that database links are not enabled. If database links are enabled, then set the TONIC_ORACLE_DBLINK_ENABLED to true for both the worker and the web server. You can configure this environment setting from Structural Settings.

TONIC_ORACLE_DBLINK_ENABLED is false (default)

If TONIC_ORACLE_DBLINK_ENABLED is false, then to create the source database user, you can use one of the following options to create the source database user and grant the required access:

  • Grant the SELECT ANY DICTIONARY privilege

  • Grant the SELECT_CATALOG_ROLE role

  • Grant access to the ALL_ views (not recommended)

Grant the SELECT ANY DICTIONARY privilege

One way to grant the required access is to grant the SELECT ANY DICTIONARY privilege.

If you choose that option, then to create the source database user:

--create a user
CREATE USER TONIC IDENTIFIED BY "<tonic_password>";

--give the user the required access
GRANT CREATE SESSION TO TONIC;
GRANT SELECT ON SESSION_ROLES TO TONIC;
GRANT EXECUTE ON DBMS_METADATA TO TONIC;
GRANT SELECT ANY DICTIONARY TO TONIC;

--give the user access to tables in your preferred schema
BEGIN
    FOR x IN (SELECT owner, table_name FROM all_tables WHERE owner = '<source_schema>')
    LOOP
        EXECUTE IMMEDIATE 'GRANT SELECT ON "' || x.owner || '"."' || x.table_name || '" to TONIC';
    END LOOP;
END;

Grant the SELECT_CATALOG_ROLE role

Instead of the SELECT ANY DICTIONARY privilege, you can grant the SELECT_CATALOG_ROLE role.

If you choose that option, then to create the source database user:

--create a user
CREATE USER TONIC IDENTIFIED BY "<tonic_password>";

--give the user the required access
GRANT CREATE SESSION TO TONIC;
GRANT SELECT ON SESSION_ROLES TO TONIC;
GRANT EXECUTE ON DBMS_METADATA TO TONIC;
GRANT SELECT_CATALOG_ROLE TO TONIC;

--give the user access to tables in your preferred schema
BEGIN
    FOR x IN (SELECT owner, table_name FROM all_tables WHERE owner = '<source_schema>')
    LOOP
        EXECUTE IMMEDIATE 'GRANT SELECT ON "' || x.owner || '"."' || x.table_name || '" to TONIC';
    END LOOP;
END;

Grant access to the ALL_ views (not recommended)

If for security reasons you cannot use either of the previous options, Structural can use the ALL_* views that Oracle provides automatically.

By default, an Oracle installation uses a GRANT to PUBLIC to grant all users access to all tables that start with ALL_. For example:

GRANT SELECT ALL_TABLES TO PUBLIC
GRANT SELECT ALL_COLUMNS TO PUBLIC
...

If you do not revoke the PUBLIC access to the ALL_* views, then Structural can use this access to connect to the source database. To create the source database user:

--create a user
CREATE USER TONIC IDENTIFIED BY "<tonic_password>";

--give the user the required access
GRANT CREATE SESSION TO TONIC;
GRANT SELECT ON SESSION_ROLES TO TONIC;
GRANT EXECUTE ON DBMS_METADATA TO TONIC;
GRANT SELECT DBA_SEGMENTS TO TONIC;
GRANT SELECT DBA_LOBS TO TONIC;

--give the user access to tables in your preferred schema
BEGIN
    FOR x IN (SELECT owner, table_name FROM all_tables WHERE owner = '<source_schema>')
    LOOP
        EXECUTE IMMEDIATE 'GRANT SELECT ON "' || x.owner || '"."' || x.table_name || '" to TONIC';
    END LOOP;
END;

If you do revoke the PUBLIC access to the ALL_* views, then you must specifically grant access to the source database user for the required ALL_* views. To create the source database user:

--create a user
CREATE USER TONIC IDENTIFIED BY "<tonic_password>";

--give the user the required access
GRANT CREATE SESSION TO TONIC;
GRANT SELECT ON SESSION_ROLES TO TONIC;
GRANT EXECUTE ON DBMS_METADATA TO TONIC;
GRANT SELECT DBA_SEGMENTS TO TONIC;
GRANT SELECT DBA_LOBS TO TONIC;
GRANT SELECT ALL_COLL_TYPES TO TONIC;
GRANT SELECT ALL_CONS_COLUMNS TO TONIC;
GRANT SELECT ALL_CONSTRAINTS TO TONIC;
GRANT SELECT ALL_DEPENDENCIES TO TONIC;
GRANT SELECT ALL_IND_COLUMNS TO TONIC;
GRANT SELECT ALL_INDEXES TO TONIC;
GRANT SELECT ALL_MVIEW_LOGS TO TONIC;
GRANT SELECT ALL_MVIEWS TO TONIC;
GRANT SELECT ALL_NESTED_TABLES TO TONIC;
GRANT SELECT ALL_OBJECTS TO TONIC;
GRANT SELECT ALL_PROCEDURES TO TONIC;
GRANT SELECT ALL_TAB_COLS TO TONIC;
GRANT SELECT ALL_TAB_COLUMNS TO TONIC;
GRANT SELECT ALL_TAB_PRIVS TO TONIC;
GRANT SELECT ALL_TABLES TO TONIC;
GRANT SELECT ALL_TYPE_ATTRS TO TONIC;
GRANT SELECT ALL_TYPES TO TONIC;
GRANT SELECT ALL_USERS TO TONIC;

--give the user access to tables in your preferred schema
BEGIN
    FOR x IN (SELECT owner, table_name FROM all_tables WHERE owner = '<source_schema>')
    LOOP
        EXECUTE IMMEDIATE 'GRANT SELECT ON "' || x.owner || '"."' || x.table_name || '" to TONIC';
    END LOOP;
END;

TONIC_ORACLE_DBLINK_ENABLED is true

If TONIC_ORACLE_DBLINK_ENABLED is true, then to create the source database user:

--create a user
CREATE USER TONIC IDENTIFIED BY "<tonic_password>";

--give the user the required access
GRANT CREATE SESSION TO TONIC;
GRANT SELECT ON SESSION_ROLES TO TONIC;
GRANT EXP_FULL_DATABASE TO TONIC;
GRANT EXECUTE ON DBMS_METADATA TO TONIC;

--give the user access to tables in your preferred schema
BEGIN
    FOR x IN (SELECT owner, table_name FROM all_tables WHERE owner = '<source_schema>')
    LOOP
        EXECUTE IMMEDIATE 'GRANT SELECT ON "' || x.owner || '"."' || x.table_name || '" to TONIC';
    END LOOP;
END;

If TONIC_ORACLE_DBLINK_ENABLED is true, then Structural must be able to create a database link between the destination database and the source database. Structural uses the network link to process a data generation job.

Creating the destination database user and schema

This is the Oracle user that connects to the destination database. This user cannot be the same user as the output schema of the data.

Structural does not create the schema or the tablespace in the destination database. You must create the schemas and tablespaces before you generate data.

--create a new user
CREATE USER TONIC IDENTIFIED BY "<tonic_password>";

--this user must be granted more extensive privileges
GRANT ALL PRIVILEGES, IMP_FULL_DATABASE to TONIC;

--create the destination schema
CREATE USER <OUTPUT_NAME> IDENTIFIED BY "<OUTPUT_PASSWORD>";

Configuring whether Structural creates the destination database schema

By default, during each data generation job, Structural creates the database schema for the destination database tables, then populates the database tables based on the workspace configuration.

When TONIC_ORACLE_SKIP_CREATE_DB is true, then Structural does not create the destination database schema. Before you run data generation, you must create the destination database with the full schema.

During data generation, Structural deletes the data from the destination database tables, except in the following cases:

  • Tables that use Preserve Destination mode.

  • Upsert data generation.

It then populates the tables with the new destination data.

If you prefer to manage the destination database schema yourself, then set the TONIC_ORACLE_SKIP_CREATE_DB to true. You can add this setting manually to the Environment Settings list on Structural Settings.

environment setting
environment setting