Data schema versions can be as arbitrary as you like; but they are most helpful when they provide meaning. Liferay’s data schema version convention communicates a schema’s compatibility with older versions of the software. It tells you whether a schema’s changes maintain or break compatibility with existing software. For example, if a new data schema removes a field your software expects, the schema breaks compatibility. But if a new schema’s changes are non-breaking (e.g., adds a new field), the schema is compatible and can be used with existing software. Since Liferay DXP 7.1, Liferay uses a meaningful schema version convention (similar to Semantic Versioning) to define new upgrade steps and support rollback of schema micro versions. The convention is optional but tracks data schema backwards compatibility.
Here’s Liferay’s schema version convention:
Each part means something:
MAJOR: Contains breaking schema/data changes that are incompatible with the latest version of existing code.
MINOR: Contains schema/data changes compatible with the latest version of existing code. The changes typically involve supporting new functionality.
MICRO: Contains schema/data changes that are compatible with the latest version of existing code.
Next are some concrete examples of micro, minor, and major changes.
Here are common micro changes:
- Modifying DB indexes.
- Modifying data values to adapt to current logic. These include backwards compatible data changes only. These changes commonly occur when data updates are missed for new functionalities.
- Converting a field from a String to a CLOB, as long as the field has few
records and isn’t used in
GROUP BYSQL clauses.
Here are common minor changes:
- Adding a new DB field.
- Creating a new DB table.
Here are common major changes:
- Removing a DB field
- Removing a DB table.
- Altering a column name.
- Decreasing the size of a
- Converting a field from a String to a CLOB, where the field is has many
records or is used in
GROUP BYSQL clauses.
Now you can ascribe meaningful versions to your module’s data schemas.