Two tFileInputDelimited components
are configured to write the expected movie data and the rejected movie data to different
directories in your local file system; then tAzureStoragePut uploads
these files to an existing Azure Blob container.
Procedure
-
Double-click the tFileOutputDelimited which receives the
out1 link.
Its Basic
settings view is opened in the lower part of the Studio.
-
In the File
Name field, enter the directory you need to write the result in.
In this scenario, it is C:/tos_bd_gettingstarted_source_files/temps/out.csv, which
receives the records that contain the names of the movie directors.
-
In the Field separator field, enter
; within double quotation marks.
-
Click Advanced settings tab to open its view and clear
the Throw an error if the file already exists check box
to allow the component overwriting existing files of the same names.
-
Repeat the same operations to configure the
tFileOutputDelimited
that receives the reject
link, but set the directory, in the File
Name field, to C:/tos_bd_gettingstarted_source_files/temps/reject.csv.
-
Double-click the tAzureStoragePut to
open its Component view.
-
In the Account Name field and the Account
Key field, enter the credentials of the Azure Blob Storage
account to be used. Ensure that the administrator of the system has granted you
the appropriate access permissions to this storage account.
-
In the Container name field, enter the name of the Azure
Blob container to be used. This container must already exist.
-
In the Local folder field, enter the directory in which
the tFileOutputDelimited components write the output
files. In this example, the directory is
C:/tos_bd_gettingstarted_source_files/temps
.
-
In the Azure storage folder field, enter the name of the
folder to be used to store the data to be uploaded to Azure. If it does not
exist, this folder is created on the fly in the container you specified above in
the Container name field.
-
Press F6 to run the Job.
Results
The Run view is automatically
opened in the lower part of the Studio and shows the execution progress of this
Job.
Once done, you can check that the output has been written
in the Azure Blob Storage container.