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Construct a Mask for Naming Data Sets in a Methodology

A data set name mask is a unique name that identifies each data set. It consists of one or more qualifiers separated by periods, and has a maximum input length of 64 characters, including the periods. When the data set name mask is translated, it has a maximum length of 44 characters including the periods.

To construct a data set name mask for your environment, determine the following:

• How do you plan to utilize deployment services?
  • Do you want each deployment to have a unique set of deployed data set names?

    or

  • Do you want to re-use a set of deployed data set names?

  If you want each deployment to have a unique set of deployed data set names:

  • The symbolic qualifier &MSMDID can be utilized to give each deployed library a unique name based upon the deployment.
  • This symbolic qualifier is unique for each deployment that is created. It is a numeric value and must be used in a mask at a place where numeric values are valid.

    Examples: Assume the deployment has an ID of 4700, and the LLQ of the data set is CAILOAD:

    • VENDOR.D&MSMDID.. would resolve to VENDOR.D4700.CAILOAD

      Note: The double dots in the mask represent two uses, the first dot delimits the variable name and the second dot is included as text in the resolved name.

    • SYSCA.D&MSMDID.T would resolve to SYSCA.D4700T.CAILOAD
  • The symbolic qualifier &YYMMDD provides you a value based on Julian Date format for the day you created the deployment. It is a numeric value that must be used in a mask at a place where numeric values are valid. This value can be used to help create unique name values.

    Examples: Assume the day the deployment was created was April 1st, 2010, and the LLQ of the data set is CAILOAD:

    • VENDOR.D&YYMMDD.. would resolve to VENDOR.D100401.CAILOAD

      Note: The double dots in the mask represent two uses, the first dot delimits the variable name and the second dot is included as text in the resolved name.

    • SYSCA.D&YYMMDD.T would resolve to SYSCA.D100401T.CAILOAD

  If you want to reuse a set of deployed data set names because this is a sandbox, and you do not need to preserve any prior deployments:

  • A constant name could be used as the mask.

    Examples: Assume the LLQ of the data set is CAILOAD:

    • SYSCA.VENDOR.PRODSET would resolve to SYSCA.VENDOR.PRODSET
• Is it possible that deployed libraries, in a multi-system deployment, could end up on Shared DASD between those systems or a shared catalog?
  • The data set names must be unique from deployment to deployment.
  • The symbolic qualifier &SYSNAME can be utilized to give each deployed library a unique name based upon the remote system name.
  • The symbolic qualifier &MSMDID can be utilized to give each deployed library a unique name based upon the deployment.
  • This symbolic qualifier is unique for each deployment that is created. It is a numeric value. It must be used in a mask at a place where numeric values are valid.

    Examples: Assume the deployment has an ID of 4700, and the LLQ of the data set is CAILOAD and the remotes systems are SYSA and SYSX:

    • VENDOR.&SYSNAME..D&MSMDID.. would resolve to VENDOR.SYSA.D4700.CAILOAD and VENDOR.SYSX.D4700.CAILOAD

      Note: The double dots in the mask represent two uses, the first dot delimits the variable name and the second dot is included as text in the resolved name.

    • SYSCA.D&MSMDID.T.&SYSNAME would resolve to SYSCA.D4700T.SYSA.CAILOAD and SYSCA.D4700T.SYSX.CAILOAD
• Is it possible that the product you are deploying does not have unique low-level qualifiers?

  Examples: Assume a product had two target libraries with the same LLQ:

  • SYINST.PROD.SYSTEM.RULES and SYINST.PROD.CUSTOM.RULES.
  • Because the mask, after resolution, is prepended in front of the LLQ, a technique is required for uniqueness.

  CA CSM provides the following symbolic qualifiers that could be utilized for low-level qualifiers:

  MSMSLQ

  This is the secondary low-level qualifier (SYSTEM and CUSTOM in the preceding examples).

  MSMDLIBN

  This is the deployed library number.

  MSMMLQ

  This is middle-level qualifier (PROD.SYSTEM and PROD.CUSTOM in the preceding examples).

  Examples:

  • SYSCA.&MSMSLQ. would resolve to SYSCA.SYSTEM.RULES and SYSCA.CUSTOM.RULES
  • SYSCA.RULES&MSMDLIBN. would resolve to SYSCA.RULES1.RULES and SYSCA.RULES2.RULES.
  • SYSCA.&MSMMLQ. would resolve to SYSCA.PROD.SYSTEM.RULES and SYSCA.PROD.CUSTOM.RULES
• Are there naming conventions on the remote system, and, for multi-system deployments, are the naming conventions similar enough to allow for a single mask to provide the desired results?
  • If, in your multi-system deployments, the naming conventions are similar enough to allow for a single mask to provide the desired results, use symbolic qualifiers and constants to construct well formed masks.
  • If, in your multi-system deployments, the naming conventions are not similar enough to allow for a single mask to provide the desired results, create multiple deployments, one for each remote system.

Note: There may be other considerations that are specific in your environment.

Keep the following points in mind when considering the construction of your data set name masks:

• They control what the deployed library is to be called. This makes it a critical element for deployment services to provide the desired results.
• The deployed libraries are cataloged on the remote system where they are created.
• The deployed libraries are created and accessed under the remote credentials for the remote system.
• Masks are methodology-based, which in turn are deployment-based. That means that one mask is utilized for all deployed libraries on any given deployment.
• Symbolic qualifiers are the key that lets a single mask provide a variety of data set names.

Business Value:

A methodology gives you the power and flexibility of creating and assigning unique data set name masks that are automatically applied when you deploy a product. This is especially useful in helping you adhere to your organization’s best practices for data set naming and standardization.

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