Array Foreign Key - Bulk Update

Select and export the array foreign key metadata to a .csv file, edit in a spreadsheet like Google Sheets or Excel, then perform a bulk update in DataPancake.

Ensure you have completed Initialization Guide

Open a new SQL file Snowflake workspace

Run a select statement for DATAPANCAKE.CORE.VW_DATASOURCE_FOREIGN_KEYS

SELECT
-- REQUIRED COLUMNS FOR BULK UPDATE
FOREIGN_KEY_ID, -- Unique ID for upsert operations - use {new_id} for new records
ARRAY_ID,
-- VIEW ONLY COLUMNS
DATASOURCE_ID,
DATASOURCE_NAME,
ARRAY_NAME,
-- EDITABLE COLUMNS FOR BULK UPDATE
PARENT_ATTRIBUTE_NAME,
FOREIGN_KEY_ALIAS_NAME,
INCLUDE_COLUMN_IN_ROW_ACCESS_POLICY,
ROW_ACCESS_POLICY_COLUMN_ORDER
FROM datapancake.core.vw_datasource_foreign_keys
ORDER BY DATASOURCE_NAME, ARRAY_NAME, PARENT_ATTRIBUTE_NAME;

You can choose which editable fields you wish to include in your select statement.

Verify the query successfully returns a list of attribute metadata

Download the results as a .csv file

Open the .csv file in either Excel or Google Sheets

Edit any editable columns as needed

Save (Excel) or download (Google Sheets) the file

Load the .csv into your stage

Run the bulk update stored procedure

Modify the <placeholders> with same database and schema you uploaded the stored procedure to.

When the stored procedure completes, the attribute metadata file will be moved to the archive folder.

call <database>.<schema>.sp_update_datapancake_array_foreign_key_metadata_core(
    '@<stage_name>/<staged_filename>.csv',
    '@<stage_name>/<archive_folder>/',
    '<snowflake_username>'
);

Verify the integration completed successfully by running the following query

select * from datapancake.core.vw_integration_process
where user_name = 'BWOLFF'
order by integration_process_date desc;