Clear table with or without clearing data

The infor.clear_table stored procedure clears the Compass object definition. The Compass object definition includes the properties in the data object plus information about the object’s identifier paths, variation path and deleted indicator. Optionally, the stored procedure clears the Compass data storage.

This procedure is used to clear Compass when the object’s metadata definition, stored in the Data Catalog, is updated with changes that affect the core definition or when historic data must be cleared and stored again with the new definition. This procedure does not affect data in the “raw” Data Lake; it updates data stored for Compass data storage only.

This procedure is used when Data Lake data is purged, archived, or marked as corrupt. This operation clears all Compass data storage; it does not affect the “raw” Data Lake data.

Use this procedure when these changes occur:

• The data object metadata definition is updated with significant data type changes, such as changing a data type from a string to a number, or a number to a datetime. If Data Lake data has already been converted to Compass data storage, clear the table and the data.
• The data object metadata definition is updated with new properties. Use a value of ‘true’ to reload historic data based on the updated object definition. The data is refreshed when a query is executed on the data object.
• The data object metadata definition is updated with new properties. Use a value of ‘false’ to not clear the data if historic data is not affected and does not have to be converted again to Compass data storage.
• The Data Catalog Locale Selections change. Clear the table definitions when new locales are added or updated. The next time a query runs, the object is converted using the current Locale Selections. If historic data contains localized strings for the new or updated locale codes, clear the Compass data storage. If historic data, stored in Compass data storage does not contain localized strings for the new or updated locales, clearing the data is not necessary.
• The Data Lake data is purged, archived, or marked as corrupt.