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SQL ELT optimization for multiple targets

SQL ELT optimization
for multiple targets

You can add multiple Amazon Redshift V2 targets in a mapping.

When you configure a mapping to write to multiple Amazon Redshift V2 targets, you can further optimize the write operation when you configure full

SQL ELT optimization

To optimize, you can choose to configure an insert, update, upsert, delete, or data driven operation for multiple targets individually.

You can select the same or different Amazon Redshift V2 target table in multiple Target transformations and perform different operations for each of the Target transformations to run independent of each other.

If your mapping contains multiple pipelines, you can define the flow run order to load the targets from the pipelines in a particular order.

When you define the flow run order for multiple pipelines and also set

-DEnableSingleCommit=true

for a single pipeline, the

-DEnableSingleCommit=true

property in given precedence.

Rules and guidelines

Consider the following rules and guidelines when you optimize full

SQL ELT optimization

for multiple targets:

When you run a mapping and use the same target table in all the targets, the row count is different from the row count of the mapping that runs without

SQL ELT optimization

. Applicable when you use an Amazon S3 source and perform an upsert operation on multiple Amazon Redshift V2 targets.

When you run a mapping and use the same target table in all the targets, the Secure Agent writes a different set of data to the target than the data of the mapping that runs without

SQL ELT optimization

. Applicable when you use an Amazon S3 source, perform an insert operation on multiple Amazon Redshift V2 targets, and enable the

Truncate Target Table Before Data Load

advanced target property.

SQL ELT optimization for mapping tasks

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