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# Amazon Redshift

The following job options are used when writing to Amazon Redshift tables. Upsolver will create missing tables in Redshift.

## Job options

```sql
[ AGGREGATION_PARALLELISM = <integer> ]
[ COMMENT = '<comment>' ]
[ COMPUTE_CLUSTER = <cluster_identifier> ]
[ END_AT = { NOW | timestamp } ]
[ FAIL_ON_WRITE_ERROR = { TRUE | FALSE } ]
[ RUN_INTERVAL = <integer> { MINUTE[S] | HOUR[S] | DAY[S] } ]
[ RUN_PARALLELISM = <integer> ]
[ SKIP_FAILED_FILES = { TRUE | FALSE } ]
[ START_FROM = { NOW | BEGINNING | timestamp } ]
[ TRUNCATE_COLUMNS = { TRUE | FALSE } ]
```

#### Jump to

Amazon Redshift job options:

* [`AGGREGATION_PARALLELISM`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#aggregation_parallelism-editable)
* [`FAIL_ON_WRITE_ERROR`](#fail_on_write_error)
* [`SKIP_FAILED_FILES`](#skip_failed_files)
* [`TRUNCATE_COLUMNS`](#truncate_columns)
* #### [`ADD_MISSING_COLUMNS`](#add_missing_columns-1)
* #### [`ON_COLUMN_TYPE_MISMATCH`](#on_column_type_mismatch-1)

General job options:

* [`COMMENT`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#comment-editable)
* [`COMPUTE_CLUSTER`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#compute_cluster-editable)
* [`END_AT`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#end_at-editable)
* [`RUN_INTERVAL`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#run_interval)
* [`RUN_PARALLELISM`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#run_parallelism-editable)
* [`START_FROM`](/content/reference-1/sql-commands/jobs/create-job/transformation/job-options.md#start_from)

#### `AGGREGATION_PARALLELISM` — editable

Type: `integer`

Default: `1`

(Optional) Only supported when the query contains aggregations. Formally known as "output sharding."

#### `FAIL_ON_WRITE_ERROR`

Type: `Boolean`

Default: `false`

(Optional) When `true`, the job will fail when an on-write error occurs.

#### `SKIP_FAILED_FILES`

Type: `Boolean`

Default: `true`

(Optional) When `true`, the job will skip any files in which the job is unsuccessful and continue with the rest of the files.

#### `TRUNCATE_COLUMNS`

Type: `Boolean`

Default: `false`

(Optional) When `true`,  data is truncated when inserting into an existing table containing `VARCHAR` or `CHARACTER VARYING` columns smaller than the incoming data size, to prevent the insert from failing.

When `false`, the insert fails if the incoming data is larger than the target column and `SKIP_FAILED_FILES` is also `false`.

#### `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.


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