informatica materials and latest interview questions and scenario: Informatica Real Time Scenerios

Split the non-key columns to separate tables with key column in both

Scenario 2:

Split the non-key columns to separate tables with key column in both / How to split the data of source table column-wise with respect to primary key. See the source and target tables below.

source table: ID is the key column, Name and Phone No are non-key columns

ID	Name	Phone No
10	AAA	123
20	BBB	234
30	CCC	434
40	DDD	343
50	EEE	442

Target Table 1

ID	Name
10	AAA
20	BBB
30	CCC
40	DDD
50	EEE

Target Table 2

ID	Phone No
10	123
20	234
30	434
40	343
50	442

Solution:

Step 1: Source qualifier: get the source table to the mapping area. See image below.

Step 2: Drag all the port from (from the previous step) to the Aggregator transformation and group by the key column. Since we have to split the columns to two different tables with the key column in each, so we are going use two expression transformation, each will take the key column and one non-key column. Connect aggregator transformation with each of the expression transformation as follows.

Step 3: We need another set of aggregator to be associated with each of the expression tranformation from the previous step.

Step 4: In the final step connect the aggregators with the two target tables as follows.

Here is the iconic view of the entire mapping.

Separating duplicate and non-duplicate rows to separate tables

Scenario 3:

How to segregate the duplicate and distinct rows from source table to separate target tables?

source table:

COL1	COL2	COL3
a	b	c
x	y	z
a	b	c
r	f	u
a	b	c
v	f	r
v	f	r

Target Table 1: Table containing all the unique rows

COL1	COL2	COL3
a	b	c
x	y	z
r	f	u
v	f	r

Target Table 2: Table containing all the duplicate rows

COL1	COL2	COL3
a	b	c
a	b	c
v	f	r

Solution:

Step 1: Drag the source to mapping and connect it to an aggregator transformation.

Step 2: In aggregator transformation, group by the key column and add a new port call it count_rec to count the key column.

Step 3: connect a router to the aggregator from the previous step.In router make two groups one named "original" and another as "duplicate"
In original write count_rec=1 and in duplicate write count_rec>1.

The picture below depicting group name and the filter conditions

Step 4: Connect two group to corresponding target table.

Remove footer from your file

Scenario 5: How to remove footer from your file ?

For example the file content looks like as below:-

some Header here
col1 col2 col3 col4
data1 data2 data3 data4
data5 data6 data7 data8
data1 data2 data3 data4
data1 data2 data3 data4
footer

Just we have to remove footer from the file.

Solution:

Step1: Drag the source to mapping area.

Step2: After that connect a filter or router transformation.

Step3: In filter write the condition like in the picture

Scenario6:

Get the first top five salaries with out using rank transformation

Step 4:Finally pass it over to target.

Remove header from your file

Scenario 6: How to remove header from a file ?

Solution

Step1: After mapping go to workflow and scheduled it.
Step2: Just double click on the session and go to mapping option.

Step3: Select the source and go to the set file properties.

flat file properties

Step4:Chose the advance option. Set number of initial rows skip: 1 ( it can be more as per requirement )

Aggregating rows on group count basis

Scenario 13: There are 4 departments in Emp table. The first one with 100,2nd with 5, 3rd with 30 and 4th dept has 12 employees. Extract those dept numbers which has more than 5 employees in it, to a target table.

Solution:

Put the source to mapping and connect the ports to aggregator transformation

Make 4 output ports in aggregator as in the picture above : count_d10, count_d20, count_d30, count_d40.
For each port write expression like in the picture below.