In this example the input data comprises a single
column carrying a vector. The example assumes that the job is running sequentially.
The input data set has a single column called 'col'..
The
following are some rows from the input data set:
Table 1. Input data set
Vector index |
0 |
1 |
2 |
3 |
4 |
row |
3 |
6 |
2 |
9 |
9 |
row |
3 |
2 |
7 |
2 |
4 |
row |
7 |
8 |
8 |
5 |
3 |
row |
4 |
8 |
7 |
1 |
6 |
row |
1 |
6 |
2 |
5 |
1 |
row |
0 |
1 |
6 |
7 |
8 |
row |
9 |
9 |
6 |
4 |
2 |
row |
0 |
8 |
4 |
4 |
3 |
row |
1 |
7 |
2 |
5 |
3 |
row |
7 |
9 |
4 |
7 |
8 |
The stage splits the columns it extracts from
the vector into separate columns called
column_nameN. You
do not have to explicitly define the output column names,
IBM® DataStage® will
do this for you as the job runs, but you might wish to do so to make the job
more understandable.
Table 2. Output column names
Column name |
SQL type |
col0 |
TinyInt |
col1 |
TinyInt |
col2 |
TinyInt |
col3 |
TinyInt |
col4 |
TinyInt |
The Vector Column property in the Properties tab
is set to 'col'.
The output data set will be:
Table 3. Output
data set
|
col0 |
col1 |
col2 |
col3 |
col4 |
row |
3 |
6 |
2 |
9 |
9 |
row |
3 |
2 |
7 |
2 |
4 |
row |
7 |
8 |
8 |
5 |
3 |
row |
4 |
8 |
7 |
1 |
6 |
row |
1 |
6 |
2 |
5 |
1 |
row |
0 |
1 |
6 |
7 |
8 |
row |
9 |
9 |
6 |
4 |
2 |
row |
0 |
8 |
4 |
4 |
3 |
row |
1 |
7 |
2 |
5 |
3 |
row |
7 |
9 |
4 |
7 |
8 |