20 September, 2018
To overcome the limitations of sequential file, we use Data set
(That is Transformation jobs are dependent on extraction jobs. And loading jobs are dependent on Transformation jobs ).
Virtual :- Data moving through the link is virtual, (temporary) Persistent :- Data created with Data set is persistent, (permanent) In target file, C: /data/output. DS àpersistent àpermanent
Data set is not a single file, but has multiple files
Schema details and address of data à Structure () table definition C:/data/file. ds
Contains data in Native format C:/IBM/Information Server / Server/data set/ file. Ds
Resides in operating system.
Transformation Here are properties Paste the Extraction Target pathColumns àLoad
To view Data set outside the job
Tools Data set Management Shows the list of files Select the file ok Data set Management window opens Here we can view data, copy data, delete data. Data Set version
Step 1: Select the job properties Symbol parameters Add Environmental variable Select APT – WPITE –DS-VERSION –okNow Compile and Run While RUN, We can Select the version Data set operators It does not have an operator generally but uses copy operator To see the operators of each stage : Job properties Generated ASH How to flush Data in the Dataset ? File set :- (.fs extension) File set is a file stage, which is used for staging the data when we design jobs. Similarities between Dataset and file set
Internal use Data that is created with Dataset can be used only for internal use. That is, .ds format is the only w. r. t Dataset file set Creation is same as Dataset creations Sequential Stage Target properties Target properties File =? File update mode:
Create the file, if the target file does not exit Options Clean up on failure = True First line is column name = False Reject mode = Continue Step 1 Select the job properties Symbol parameters Add Environmental variable Select APT – CLOBER – OUTPUT Now compile and Full At Run time APT – CLOBER – OUTPUT = False Aborts APT – CLOBER – OUTPUT = True create file Clean up on failure :- (Works with Append mode) If true = automatically clears partially loaded records, if the job is failed for any restart from the point where it has drooped. Development and Debug Stage Divided into three groups
Row generator It is a development Stage, Which generates Sample data (sys/user defined) And Supports only one output. Column generator It is a development Stage, Which generates columns with Sample data (sys/user defined) And Supports input and output.
Development Stage creates Sample data, Suppose if the Client does not give data, we create the Structure and sample data. Row generator :- (one input) System Generated Right click on Row generator properties No. of Records = 100 okàcolumn load Select the file ok view data User-defined Properties No. of Records columns load click on Serial fileàEdit column Meta data window opens Generator type (cycle / random)
Var char Generator Algorithm = cycle Value = ? (Here values takes n, no. of name) Algorithm = Alphabet String = ? (String data only 1 name, and display each Alphabet ) That is string = abc Output is : a b c Integer
Desired to gain proficiency on DataStage? Explore the blog post on DataStage training to become a pro in DataStage.
Type = Random limit seed signed Data
Column Generator :- (only 1 input /output) Column Generator is associated with
Based on this we can group all Employee into 1 group Right click on column Generator
With in options
Column method = Explicit
Column to Generator = COMPANEY
Column to Generator = COUNTRY
Click, on output options
Left hold the mouse, and drag it and perform Mapping
Ok View data [Mapping is needed for column Generator, because it has both input and output] User-defined C.G
Double click on country
Algorithm = cycle
Value = IBM
Ok For indepth understanding of DataStage click on
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