(upbeat chiming music)
- [Narrator] When you convert your database schema
from one engine to another,
you also convert the extract, transform, and load processes.
You can use the AWS Schema Conversion Tool
to convert Microsoft SQL Server Integration Services
ETL packages
AWS SCT version 1.0.661 supports the conversion
of SSIS packages to AWS Glue and AWS Glue Studio.
This video shows how to create a new a AWS SCT project,
convert your source SSIS packages,
review them in AWS Glue Studio,
and verify the conversion.
Launch the AWS Schema Conversion Tool
and create a new project.
Enter a name of the project
and location to save a local project file.
Next, add Microsoft SQL Server
Integration Services as a source.
Enter the path to the folder
where you store your source SSIS packages.
Add AWS Glue Studio as a migration target.
AWS SCT connects to AWS Glue Studio
using your AWS credentials.
You can store your AWS credentials
in the AWS SCT Global Application Settings.
After AWS SCT connects to AWS Glue Studio,
create a mapping rule.
A mapping rule defines your source and target platforms.
Choose your source SSIS script
in the AWS Glue Studio target,
and then choose Create mapping.
Switch to the main view.
The source metadata tree includes your SSIS package.
This demo POC 1 component includes a Connection manager,
Data Flow Task, two sources, one target,
and a Merge Join transformation component.
SSIS packages interact with a database
which is specified in their Connection Manager component.
Your converted AWS Glue Studio jobs will also interact
with your new target database.
Because of that, specify an AWS Glue Studio connection
for all your source SSIS connections.
Make sure that you have already created all required
AWS Glue Studio connections.
Now, all is set to start the conversion.
After you convert your source SSIS packages,
AWS SCT creates objects in the target tree.
The target metadata tree includes AWS Glue Studio objects
such as Connections, Crawlers, Databases,
ETL Jobs, and Triggers.
AWS SCT converts SSIS packages to the objects
that have a directed acyclic graph structure.
Find the converted objects in the DAG's node,
review the converted code, and make changes if needed.
Save the converted files to Amazon S3
and configure your AWS Glue Studio jobs.
On the first step of the wizard,
edit the basic job properties,
such as name, script file name, and job parameter values.
On the second step, edit the Advanced job properties
such as IAM roll, Script file S3 path, and so on.
Make sure that you specify the IAM Role
with permissions to run AWS Glue Studio jobs.
Configure all job properties
and choose Finish to create AWS Glue Studio jobs.
Find these jobs in the ETL Jobs node
of the target metadata tree.
These jobs include scripts with required parameters,
which you specified in the wizard.
Create the a AWS Glue Studio jobs
for your configured ETL jobs.
The Apply status tab displays the status
of the AWS Glue Studio job creation.
Open AWS Glue Studio and refresh the list of jobs.
The list includes all three jobs from AWS SCT.
The AWS Glue Studio job includes a visual representation
of the Glue Studio job pipeline and the generated script.
Because SSIS components have different features
compared to AWS Glue Studio,
the converted jobs may include more components
than your source SSIS packages.
Now you can run your AWS Glue Studio job.
The job status changes to Succeeded.
Our job repopulates data in the Account Customer table.
We can see that this table includes 15 data rows.
Our source SSIS script produced the same output.
This means that AWS SCT correctly converts SSIS packages
to AWS Glue Studio.
Now you can use the converted script
with your new target database in the cloud.
This completes the overview of the SSIS packages
to AWS Glue Studio jobs conversion in AWS SCT.
Thanks for watching this video.