Amazon Redshift

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

Job options

[ 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 } ]

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Amazon Redshift job options:

• AGGREGATION_PARALLELISM

• FAIL_ON_WRITE_ERROR

• SKIP_FAILED_FILES

• TRUNCATE_COLUMNS

General job options:

• COMMENT

• COMPUTE_CLUSTER

• END_AT

• RUN_INTERVAL

• RUN_PARALLELISM

• 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.