Peek Stage in DataStage - 3

In today's post, we will discuss a important property of PEEK stage. What if you want to peek some data as well as want to take action or wanna do something with data after peeking. For enabling this, datastage gives you a option to do this.

1. Job Design :

for this demo, we will use below job design to explain, as you can see, There are 2 link coming out from PEEK stage. 

First Link  --> This link contain the PEEK data as per property defined in peek stage. (here you can see 40 rows ( 10 rows from each partition x 4 nodes )

Second Link --> this link contain the Whole stream data.  ( All 100 rows )

Peek Stage in DataStage - 2

Lets continue our journey with PEEK stage, today in this post, I am going to share one more option about PEEK stage. Sending the Peek data into a output file..

1. Job design :  

For this demo job, we will use below job design. You can see we have attached a seq file after the peek stage which will capture the Peeked data

Peek Stage in DataStage - 1

The Peek stage is a Development/Debug stage. It can have a single input link and any number of output links.

The Peek stage lets you print record column values either to the job log or to a separate output link as the stage copies records from its input data set to one or more output data sets.

1. Design :

We are using below design to demonstrate the functionality of PEEK stage in datastage. Job design is having 3 stages, Row Generator , data source, for generating the dummy data for the job. Here, we can use any data source whether it is DB, dataset or flat files. Transformer, just as a stage, creating negative values of source data. Peek for Peeking :-) 

Development/Debug Stage in DataStage

Head stage

The Head Stage is a Development/Debug stage. It can have a single input link and a single output link.

It is one of a number of stages that InfoSphere DataStage provides to help you sample data

The Head Stage selects the first N rows from each partition of an input data set and copies the selected

rows to an output data set. You determine which rows are copied by setting properties which allow you

to specify:

·         The number of rows to copy

·         The partition from which the rows are copied

·         The location of the rows to copy

·         The number of rows to skip before the copying operation begins

This stage is helpful in testing and debugging applications with large data sets. For example, the Partition

property lets you see data from a single partition to determine if the data is being partitioned as you

want it to be. The Skip property lets you access a certain portion of a data set.