Apache Iceberg
These job options are used when writing to Upsolver-managed Apache Iceberg tables.
Tables created within Upsolver using your metastore connection are considered Upsolver-managed tables. Note that these tables can still be queried externally. For example, you can create an AWS Glue Data Catalog table within Upsolver, and this table can be queried within Upsolver itself or when you go to your Athena console.
Job options
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Apache Iceberg table options:
General job options:
ADD_MISSING_COLUMNS
ADD_MISSING_COLUMNS
Type: Boolean
Default: false
(Optional) When true
, columns that don't exist in the target table are added automatically when encountered.
When false
, you cannot do SELECT *
within the SELECT
statement of your transformation job.
ON_COLUMN_TYPE_MISMATCH
Type: String
Default: None
Possible values: Add Column
,None
This option is applicable only if ADD_MISSING_COLUMNS
=true.
It determines how to handle cases where the datatype of the source data does not match the datatype of the corresponding column in the target table.
If set to Add Column
, Upsolver will attempt to cast the incoming data to the original column's datatype. If the cast fails, a new column with the format <originalColumnName>_newDataType will be created, and the mismatched data will be written to this new column. For example, if the CLIENT_ID column is a number in the target table and a VARCHAR arrives in that column, a new column called CLIENT_ID_VARCHAR will be added for the string data. The original column will continue to be populated if the data can be cast successfully.
If set to None
, no new columns will be added, and only valid casts will be written to the original column.
FLATTEN_PATHS
FLATTEN_PATHS
Type: Array<String>
Default: ()
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