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1.What is the Exact difference between BASIC Transformer and NORMAL

Transformer?

A. The Transformer stage is inherent PX functionality,

whereas the BASIC Transformer uses a Server interface to

call a Server Transformer stage. There's severe performance

impact as well as partitioning limitations, but it does

give a PX job some access to existing Server functionality.

2. There ate two types of transformer i. Basic

transformer and ii. Active transformer. Basic transformer

is used for SMP system and not in MPP or cluster. Basic

transformer (BASIC is the language supported by the Data

stage server engine and available in Server job). Where in

Datastage Px the Active transformer get use.

3. Transformer stages are always active stages. The

basic transform stage is part of the Server product, but

the PX engine allows this stage to be called (the opposite,

using a PX stage in Server is not possible)

2.Did sequential stage accepts .xl files ,xml? znd how?

yes it accepts. use fixed line pattern

3.what is main difference between change capture and change apply stages

the stage compares two data set(after and before) and

makes a record of the differences.

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change apply stage combine the changes from the change

capture stage with the original before data set to

reproduce the after data set

4.difference between server shared container and parallel shared container

1. Server shared containers contain server stage types,

parallel shared containers contain parallel stage types.

2. When we go for parallel shared container the logic

can be reusable across many jobs

Introduction

DataStage Enterprise Edition is a package of three products: DataStage Server

Edition, the parallel extender with parallel ETL jobs and the MetaStage product

described on the Metadata Workbench entry. The flagship tool of Enterprise Edition

is parallel ETL jobs.

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History

During the 1990s the data integration vendors such as Ascential and Informatica

were competing to deliver tools that provided a wide range of data connectivity and

transformation functions in a mostly code free environment. Towards the late 1990s

data stores were becoming large, data warehouses and business intelligence wasdemanding larger volumes of data loads. The physical architecture of these loads

was hitting a limit on the volume that a single server could handle and was moving

towards clusters or grids of servers.

The data integration vendors need to be able to integrate data across a massively

scalable architecture to keep up with the increased data volumes.

Ascential started to roll out a parallel capability in the DataStage Server Edition

product called multiple instance jobs. This allowed some additional manual

programming to partition and process data in parallel. In November 2001 they

switched to a buy approach and purchased Torrent Systems for $46 million.

Torrent had the capability to run tools on a massively parallel processing (MPP)

platform.

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Versions

This section lists each major release of DataStage Enterprise Edition and the

enhancements for DataStage parallel jobs. For a list of enhancements to the client

tools see the versions on the DataStage Server Edition page is it is the version that

has been delivered with every release going back to DataStage 1.

All release of DataStage 7 can import and upgrade DataStage 6 export files.

DataStage 8 can only import and upgrade DataStage 7.5.1 or 7.5.2 jobs.

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DataStage 6

Released in September 2002, ten months after the acquisition of Torrent, it was the

first version of DataStage to feature the Parallel Extender (PX), the parallel platform

that allows processes to run in parallel across a multiple processor environment.

New parallel job type with a new set of parallel stages. Some with the same

name as server job stages but with different properties and options.

Server job shared container for parallel jobs.

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CPU based licensing instead of server based licensing.

Support for SAS 6.12 and 8.2.

This release was followed by the client only 6.0.1 release that fixed a number

problems.

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DataStage 7

Release September 2003 it uses much the same architecture of the previous

version with improvements to the usability. This was the first release to have no

server job improvements but many parallel job improvements.

XML Pack 2.0 provides improved XML metadata support for parallel jobs.

National Language Support (NLS) for parallel jobs but not for all parallel

stages.

Parallel shared and local stages.

Enhanced transformer with improved reject row handling, string handling,

timestamp conversion and compile performance.

Modify, Switch and Filter stages added.

Multiple-instance parallel jobs.

Non blocking funnel stage.

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DataStage 7.5

Unknown release date.

Parallel complex flat file stage.

A parallel job message handler for demoting or removing warning messages

from the job log.

Lookup stage changes from a property screen to a drag and drop mappingscreen.

Multi node import of sequential files.

Additional options for sequential file and file set stages such as Read First

Rows, Row Number Column and First Line is Column Names.

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View data support for custom stages.

New Parallel Advanced Job Developers Guide.

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DataStage 7.5.1

Released in March 2005.

New SQL Builder for building SQL query statements from a database plugin

stage.

Command line job search function added.

DataStage parallel jobs for Unix System Services (USS) on the mainframe.

Remote job deployment to deliver and run jobs across a cluster or grid.

Vector support in the parallel transformer stage.

Sybase and ODBC stages added to parallel jobs.

Complex Flat File stage improvements: multiple output links, automatically

generated fillers, MVS dataset support.

Thread based job monitoring for parallel jobs.

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DataStage 7.5X2

Released in December 2004 this was the first release of parallel jobs that could run

on Windows. While the Server runs on all the same Unix and Linux platforms as

7.5.1 it adds the additional platform of Windows 2003 Standard or Enterprise on the

Intel x86 Processor Family.

There were no changes to parallel jobs in this release apart from the capability to

compile and run them on Windows.

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DataStage 8

Released in October 2006 for Windows and April 2007 for Unix this is the first

version to run on the IBM Information Server. There are a number of parallel job

improvements in this release:

Lookup stage now supports two new lookup types: range lookup and caseless

lookup.

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New Slowly Changing Dimension stage.

New QualityStage stages for parallel jobs.

What is the difference between a Filter and a Swit...

________________________________________

A Filter stage is used to filter the incoming data ,for suppose u want to get the

details of customer 20 if u give customer 20 as the constraint in filter it will display

only the customer 20 files and u can also give a reject link,the rest of the records

will go into reject link.

where as in the switch,

we need to give as cases,

like case1,case2.

case1=10;

case2=20;

it will give the outputs of 10 and 20 customer records.

switch will check the cases and execute them.