Piping blob data – PB Docs 150

Adding blob columns to a pipeline definition

When you select data to pipe, you cannot select a blob column
as part of the data source because blobs cannot be handled in a SELECT statement.
After the pipeline definition is created, you add blob columns,
one at a time, to the definition.

To add a blob column to a pipeline definition:

1. Select Design>Database Blob from
   the menu bar.

   If the Database Blob menu item is disabled

   The Database Blob menu item is disabled if the pipeline definition
   does not contain a unique key for at least one source table, or
   if the pipeline operation is Refresh, Append, or Update and the
   destination table has no blob columns.

   The Database Binary/Text Large Object dialog box
   displays. The Table box has a drop-down list of tables in the pipeline
   source that have a primary key and contain blob columns.

2. In the Table box, select the table that contains
   the blob column you want to add to the pipeline definition.

   For example, in the EAS Demo DB, the ole table
   contains a blob column named Object with the
   large binary datatype.

3. In the Large Binary/Text Column box,
   select a column that has a blob datatype.

4. In the Destination Column box, change the name
   of the destination column for the blob if you want to.

   If you want to add the column and see changes you make without
   closing the dialog box, click Apply after each change.

5. When you have specified the blob source and destination
   as needed, click OK.

To edit the source or destination name of the
blob column in the pipeline definition:

1. Display the blob column’s pop-up
   menu and select Properties.

To delete a blob column from the pipeline definition:

1. Display the blob column’s pop-up
   menu and select Clear.

Executing a pipeline with blob columns

After you have completed the pipeline definition by adding
one or more blob columns, you can execute the pipeline. When you
do, rows are piped a block at a time, depending on the Commit value.
For a given block, Row 1 is inserted, then Row 1 is updated with
Blob 1, then Row 1 is updated with Blob 2, and so on. Then Row 2
is inserted, and so on until the block is complete.