Conditional Catalog Sets¶

Alation Cloud Service Applies to Alation Cloud Service instances of Alation

Customer Managed Applies to customer-managed instances of Alation

Important

You are viewing documentation for Classic Alation.

Conditional catalog sets allow you to dynamically group RDBMS objects (schemas, tables, or columns) based on user-defined name-matching rules. Instead of manually selecting individual objects into a set, you define criteria that Alation uses to automatically populate the set with matching objects. This ensures that catalog sets remain up-to-date as your catalog evolves:

Objects are automatically added to the set when they meet the defined conditions.

Through the set, you can modify field values across multiple catalog objects in a single action.

Any changes to the fields in the set are instantly applied to all its members.

To create and manage catalog sets, including bulk-editing field values for their members, you must have either Catalog Admin role or Server Admin role.

In this topic:

Create a Conditional Catalog Set¶

To create a conditional set:

Click Save to apply the rule. Alation matches the objects and displays the matching ones in the Catalog Set Members table.

Review the catalog set members to ensure the group includes all the intended objects. Once confirmed, you can proceed to bulk-edit fields for all members in the set.

Click Save to apply the rule. Alation matches the objects and displays the matching ones in the Catalog Set Members table.
Review the catalog set members to ensure the group includes all the intended objects. Once confirmed, you can proceed to bulk-edit fields for all members in the set.
Click the Edit button for the Description field, enter a description, and click Save.

Use Regex in Catalog Set Rules¶

You can use Regex (regular expression) patterns when configuring catalog set membership rules. Select matches regex as the condition for the name matching rule to use regular expressions.

Alation supports the regular expression syntax of Python’s re module.

Basic Regex Syntax¶

Syntax	Description	Example
`a`	A specific character, like `a`
`ab`	A specific string, like `ab`
`^`	The start of a string	`^3`: The string starts with `3`.
`$`	The end of a string	`3$`: The string ends with `3`.
`.`	Wildcard. Matches any character except newline (`\n`).	`a.b`: Matches any three-character string that starts with `a`, ends with `b`, and has any one character in between.
`\`	Escapes a special character	`Price\: \d+\.\d{2}`: The backslashes `\` escape the colon and the period, which ensures the pattern matches a literal colon and a literal dot.
`\|`	Matches either side (OR logic)	`drg\|ssn`: Matches `drg` or `ssn` anywhere in the text. `^<drg>$\|^<ssn>$`: Matches `drg` or `ssn` if they are the entire content of the string.

Regex Examples¶

Refer to these examples for information on using some common Regex patterns:

Finding Column Names That Contain “email” Anywhere¶

Goal: Match column names that contain the word email anywhere, even with other symbols or words before or after.
Regex pattern: .*email.*
Explanation:
- .: Matches any character (except for line terminators like newline \n)
- *: Means zero or more occurrences of the immediately preceding element. In .*, it means zero or more of any character.
- email: The literal word email.
Example matches:
- Matching examples:
  user_email
  
  email_address
  
  customer-email
  
  contact_email_1
- Non-matching examples:
  e-mail (Doesn’t contain the contiguous substring email)
  
  mail (Lacks the leading e)

Finding Column Names That Start With “ssn”¶

Goal: Match column names that start with ssn, followed by any additional characters.
Regex pattern: ^ssn\w*
Explanation:
- ^: Ensures the match starts at the beginning of the column name.
- ssn: The literal word ssn.
- \w*: Matches zero or more word characters (letters, digits, or underscores) after ssn.
Example matches:
- Matching examples:
  ssn_number
  
  ssn123
  
  ssnid
  
  ssn_backup
- Non-matching examples:
  my_ssn (Doesn’t start with ssn)
  
  oldssn (Doesn’t start with ssn)

Finding Column Names “name” or “number”¶

Goal: Match column names name or number.
Regex pattern: ^(name|number)$
Explanation:
- ^: Asserts the position at the start of the string.
- (name|number): Matches either name or number.
- $: Asserts the position at the end of the string.
Example matches:
- Matching examples:
  name
  
  number
- Non-matching examples:
  first_name (name isn’t a standalone occurrence)
  
  name_customer (name isn’t a standalone occurrence)
  
  named_column (name isn’t separate but part of a larger word)
  
  numbering_system (number isn’t separate but part of a larger word)

Finding Column Names That End with a Year After an Underscore¶

Goal: Match column names that end with an underscore followed by a four-digit year (e.g., _2025).
Regex pattern: \w+_\d{4}$
Explanation:
- \w+: Matches one or more word characters (letters, digits, or underscores) at the beginning of the column name.
- _: Requires an underscore before the year.
- \d{4}: Matches exactly four digits, commonly representing a year.
- $: Ensures the pattern matches only at the end of the column name.
Example matches:
- Matching examples:
  sales_data_2025
  
  report_2023
  
  backup_1999
  
  some_word_2040
- Non-matching examples:
  @_2025 (A non-word character before the underscore)
  
  2025_report (Year is at the start, not at the end after an underscore)
  
  sales_data_23 (Year is not four digits long)

Bulk-curate Shared Fields¶

You can manage catalog field values for all catalog set members from the Shared Fields tab on the catalog set’s properties page. Any values applied through the set are automatically propagated to all its members.

Learn more in Bulk-Curate Field Values Using Shared Fields.

Update or Delete Catalog Sets¶

For details on how to modify or delete a catalog set, refer to Manage Catalog Sets.