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  1. Preface
  2. Introduction to Microsoft Azure Synapse SQL Connector
  3. Connections for Microsoft Azure Synapse SQL
  4. Mappings for Microsoft Azure Synapse SQL
  5. Upgrading to Microsoft Azure Synapse SQL Connector
  6. Migrating a mapping
  7. SQL ELT optimization
  8. Data type reference
  9. Troubleshooting

Microsoft Azure Synapse SQL Connector

Microsoft Azure Synapse SQL Connector

Configuring SQL ELT optimization

Configuring
SQL ELT optimization

To optimize a mapping, add the mapping to a task, and then configure
SQL ELT optimization
in the
mapping
task.
  1. Create a
    mapping
    task.
  2. In the
    SQL ELT Optimization
    section on the Runtime Options tab, set the
    SQL ELT optimization
    value to
    Full
    or
    To Source
    .
    You can use Source
    SQL ELT optimization
    only when you read from a Microsoft Azure Synapse SQL source.
    The Optimization context type option is not applicable for a Microsoft Azure Synapse SQL mapping task.
  3. If full
    SQL ELT optimization
    is not available, select how Data Integration handles
    SQL ELT optimization
    in the
    SQL ELT Optimization
    Fallback Option menu
    :
    • Partial
      SQL ELT optimization
      . Default. Data Integration pushes as much transformation logic as possible to the source and target database. The task processes any transformation logic that it can't push to a database. You can use Partial
      SQL ELT optimization
      only when you read from and write to Microsoft Azure Synapse SQL.
    • Non
      SQL ELT optimization
      . The task runs without
      SQL ELT optimization
      .
    • Fail Task. Data Integration fails the task.
    The fallback options are not applicable to mappings in advanced mode.
When you run the mapping task, the transformation logic is pushed to the
Microsoft Azure Synapse SQL
. To verify that the
SQL ELT optimization
has taken place, you can check the session log for the job.
You can monitor the jobs that you initiated on the
My Jobs
page. You choose to stop or clean stop a job. When you use clean stop, Data Integration terminates all the issued statements and processes spawned by the job.
This is not applicable to mappings in advanced mode
.

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