This document describes a DataStage job design to solve a scenario problem. The design includes: 1) A job with a seq file input, aggregator stage to count rows by key, and filter stage to output rows by count. 2) The aggregator stage groups data by the "No" column and calculates row counts for each key. 3) The filter stage outputs rows where count equals 1 and where count is greater than 1 to separate files.

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Monday, February 03, 2014
DataStage Scenario Problem ­­> DataStage Scenario ­ Problem2
Solution Design :
a) Job Design :
Below is the design which can achieve the output as we needed. Here, we are reading seq file as a input, then data is passing through Aggregator
and Filter stage to achieve the output.
DataStage Scenario ­ Design 2 ­ job1
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2. b) Aggregator Stage Properties
Input data contains only one column "No" , In Aggregator stage, we have group the data on the "No" column and calculate the rows for each Key (
No ).
When we have used the "Count Rows" aggregation type, it will generate a new column which contain the count for each Key (No). Here we have
given the column name ­ "count" and assigned to output as below.
c) Filter Stage Properties
In Filter stage, we put 2 where condition count=1 and count>1. and assigned different output files to both conditions.
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3. Assigned the data ( column No ) to output tab.
d) Output File
We got two output from the jobs
i) Contains where count=1 ( unique values in input )
ii) Contains where count>1 ( dups values in input )
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