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Known Issues
While you specify an SQL statement in the SQL Statement Editor of an ELT Snap as an expression, the dynamic validation for the expression displays inline errors when there is more than one incoming document and without the
'__sql__'
key to the current Snap, when you select Get Preview Data checkbox in the previous Snap, and when Preview Document Count in your user settings is set to a value more than 1.To prevent this error and similar ones, do not select the Get Preview Data checkbox in the previous Snap, set the Preview Document Count in your user settings to 1, or append a condition
where 1 = 0
to the SQL statement with the Get Preview Data checkbox selected.
Due to an issue with BigQuery table schema management (the time travel feature), an ALTER TABLE action (Add or Update column) that you attempt after deleting a column (DROP action) in your BigQuery target table causes the table to break and the Snap to fail.
As a workaround, you can consider either avoiding ALTER TABLE actions on your BigQuery instance or creating (CREATE) a temporary copy of your table and deleting (DROP) it after you use it.
- When your Databricks Lakehouse Platform instance uses Databricks Runtime Version 8.4 or lower, ELT operations involving large amounts of data might fail due to the smaller memory capacity of 536870912 bytes (512MB) allocated by default. This issue does not occur if you are using Databricks Runtime Version 9.0.
- When you configure an ELT Merge Into Snap to perform an Update or Delete operation or an ELT Execute Snap with a MERGE INTO statement that performs Update or Delete operation on a Databricks Lakehouse Platform cluster, it may return an error if multiple source rows attempt to update or delete the same target row. To prevent such errors, you need to preprocess the source table to have only unique rows.
ELT Pipelines created prior to 4.24 GA release using one or more of the ELT Insert Select, ELT Merge Into, ELT Load, and ELT Execute Snaps may fail to show expected preview data due to a common change made across the Snap Pack for the current release (4.26 GA). In such a scenario, replace the Snap in your Pipeline with the same Snap from the Asset Palette and configure the Snap's Settings again.
The Snap’s preview data (during validation) contains a value with precision higher than that of the actual floating point value (float data type) stored in the Delta. For example, 24.123404659344 instead of 24.1234. However, the Snap reflects the exact values during Pipeline executions.
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Field Name | Type | Field Dependency | Description | |||||||||
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Label* | String | None. | The name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your Pipeline. Default Value: NA Example: ELT Execute for SF | |||||||||
SQL Statements* | Fieldset | None. | Use this field set to define your SQL statements, one in each row. Click to add a new row. You can add as many SQL statements as you need. | |||||||||
SQL Statement Editor* | String/Expression | None. | Enter the SQL statement to run, in this field. The SQL statement must follow the SQL syntax as stipulated by the target database—Snowflake, Redshift, Azure Synapse, Databricks Lakehouse Platform or BigQuery.
Default Value: NA Example: drop table base_01_oldcodes; |
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