Power CenterTraining

8/10/2019 Power CenterTraining

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Informatica PowerCenter 7.1

Basics

Education ServicesVersion PC7B-20041208

Informatica Corporation, 2003 - 2004. All rights reserved.


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Introduction


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By the end of this course you will:

Understand how to use the major PowerCentercomponents for development

Be able to build basic ETL mappings and mapplets*

Be able to create, run and monitor workflows

Understand available options for loading target data

Be able to troubleshoot most problems

Note: The course does not cover PowerCenter optionalfeatures or XML support.

Course Objectives

* A mapplet is a subset of a mapping


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Founded in 1993

Leader in enterprise solution products

Headquarters in Redwood City, CA

Public company since April 1999 (INFA)

2000+ customers, including over 80% of Fortune 100

Strategic partnerships with IBM, HP, Accenture, SAP,

and many others Worldwide distributorship

About Informatica


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Informatica Products

PowerCenter ETLbatch and real-time data integration

PowerAnalyzer BI reportingweb-browser interface with reports,dashboards, indicators, alerts; handles real-timemetrics

SuperGlue* Centralized metadata browsing cross-enterprise,including PowerCenter, PowerAnalyzer, DBMS,BI tools, and data modeling tools

PowerExchange Data access to mainframe, mid-size system and

complex filesPowerCenterConnect products

Data access to transactional applications andreal-time services

* Uses PowerCenter to extract metadata and PowerAnalyzer to display reports


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www.informatica.comprovides information (under Services) on:

Professional Services

Education Services

my.informatica.comsign up to access:

Technical Support

Product documentation (under Toolsonline documentation) Velocity Methodology (under Services)

Knowledgebase

Webzine

Mapping templates

devnet.informatica.comsign up for Informatica Developers Network

Discussion forums

Web seminars

Technical papers

Informatica Resources


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Informatica offers three distinct Certification titles:

Exam A: Architecture and Administration Exam C: Advanced Administration

Exam A: Architecture and Administration Exam B: Mapping Design Exam D: Advanced Mapping Design

Exams A, B, C, D plus Exam E: Enablement Technologies

For more information and to register to take an exam:http://www.informatica.com/services/Education+Services/Professional+Certification/

Informatica Professional Certification
http://www.informatica.com/services/Education+Services/Professional+Certification/http://www.informatica.com/services/Education+Services/Professional+Certification/


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Extract, Transform and Load

Transaction level data Optimized for transaction

response time

Current

Normalized orDe-normalized data

Operational Systems

MainframeRDBMS Other

Aggregated dataHistorical data

Decision Support

Data

Warehouse

ETL Load

Transform

Extract

Aggregate dataCleanse dataConsolidate dataApply business rulesDe-normalize data


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PowerCenter Client Tools

Repository Designer Workflow Workflow Rep ServerManager Manager Monitor Administration

Console

Manage repository:ConnectionsFolders

ObjectsUsers and groups

Administer repositories on aRepository Server:Create/upgrade/deleteConfigurationStart/stopBackup/restore

Build ETLmappings

Build and startworkflows torun mappings

Monitorand startworkflows


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PowerCenter 7 Architecture

Not Shown: Client ODBC connections from Designer to sources and targets for metadata

TargetsSources

Native Native

TCP/IP

HeterogeneousTargets

Repository

RepositoryServer

RepositoryAgent

TCP/IP

Native

Informatica Server

HeterogeneousSources

Repository Designer Workflow Workflow Rep ServerManager Manager Monitor Administrative

Console


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Distributed Architecture and Platforms

The following components can be distributed across anetwork of host computers: Clients Tools

PowerCenter Servers

Repository Servers Repository Databases

Sources and Targets

Platforms:

Client tools run on Windows Servers run on AIX, HP-UX, Solaris, Redhat Linux, Windows

Repositories on any major RDBMS


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Design and Execution Process

1. Create Source definition(s)

2. Create Target definition(s)

3. Create a Mapping

4. Create a Session Task

5. Create a Workflow with Task components

6. Run the Workflow and verify the results


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Demonstration


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Source Object Definitions


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Source Object Definitions

By the end of this section you will:

Be familiar with the Designer interface

Be familiar with Source Types Be able to create Source Definitions

Understand Source Definition properties

Be able to use the Data Preview option


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Import from:Relational databaseFlat fileXML object

Create manually

Methods of Analyzing Sources

Source Analyzer

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Analyzing Relational Database Sources

TableViewSynonym

Relational DB Source

DEF

Source AnalyzerODBC

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Analyzing Relational Database Sources

Editing Source Definition Properties


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Analyzing Flat File Sources

Mapped DriveNFS MountLocal Directory DEF

Fixed Width Delimited

Flat FileSource Analyzer

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native


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Flat File Wizard

Three-stepwizard

Columns canbe renamed

within wizard Text, Numeric

and Datetimedatatypes are

supported Wizard

guesses

datatype


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Flat File Source Properties


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Analyzing XML Sources

DEF

XML Schema (XSD),DTD or XML File

DATA

Source Analyzer

Repository

RepositoryServer

Repository Agent

TCP/IP

DEF

Native

Mapped DriveNFS MountingLocal Directory


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Using Data Previewer inSource Analyzer

Data Preview ExampleFrom Source Analyzer,select Source drop downmenu, then Preview Data

Enter connection informationin the dialog box

A right mouse click on the object can also be used to preview data


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Metadata Extensions

Allows developers and partners to extend themetadata stored in the Repository

Metadata extensions can be:

User-definedPowerCenter users can define and createtheir own metadata

Vendor-definedThird-party application vendor-createdmetadata lists

For example, applications such as Ariba or PowerCenter Connect

for Siebel can add information such as contacts, version, etc.


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Metadata Extensions

Can be reusable or non-reusable

Can promote non-reusable metadata extensions toreusable; this is irreversible (except by Administrator)

Reusable metadata extensions are associated withall repository objects of that object type

A non-reusable metadata extensions is associatedwith a single repository object

Administrator or Super User privileges are requiredfor managing reusable metadata extensions


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ExampleMetadata Extension for a Source

Sample User DefinedMetadata, e.g. contact

information, business user


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Target Object Definitions


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Target Object Definitions

By the end of this section you will:

Be familiar with Target Definition types

Know the supported methods of creating TargetDefinitions

Understand individual Target Definition properties


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Creating Target Definitions

Methods of creating Target Definitions

Import from relational database

Import from XML object

Create automatically from a source definition

Create manually (flat file or relational database)


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Import Definition from Relational Database

Can obtain existing object definitions from a databasesystem catalog or data dictionary

Table

ViewSynonym

WarehouseDesigner

Relational DB

DEF

ODBC

Repository

RepositoryServer

Repository AgentTCP/IP

DEF

Native


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Import Definition from XML Object

Can infer existing object definitions from a databasesystem catalog or data dictionary

WarehouseDesigner

Repository

RepositoryServer

Repository AgentTCP/IP

DEF

Native

DEF

DTD, XML Schema orXML File

DATA

Mapped DriveNFS MountingLocal Directory


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Target Definition Properties


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Heterogeneous Targets

By the end of this section you will be familiar with:

Heterogeneous target types

Heterogeneous target limitations

Target conversions


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Definition: Heterogeneous Targets

Supported target definition types:

Relational database

Flat file

XML

Targets supported by PowerCenter Connects

Heterogeneous targets are targets within a singleSession Task that have different types or have differentdatabase connections


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Step One: Identify Different Target Types

Oracle table

Flat file

Oracle tableTables are EITHER in twodifferent databases, orrequire different (schema-specific) connect strings

One target is a flat file load


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Step Two: Different Database Connections

The two databaseconnections aredifferent

Flat file requiresseparate locationinformation


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Target Type Override (Conversion)

Example: Mapping has SQL Server target definitions.Session Task can be set to load Oracle tables instead,using an Oracle database connection.

The following overrides are supported:

Relational target to flat file target

Relational target to any other relational database type

CAUTION: If target definition datatypes are not compatible with datatypes innewly selected database type, modify the target definition


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Lab 1Define Sources and Targets


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Transformation Basic Concepts


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Transformations Objects Used in This Class

Source Qualifier: reads data from flat file & relational sourcesExpression: performs row-level calculations

Filter: drops rows conditionally

Sorter: sorts data

Aggregator:performs aggregate calculations

Joiner: joins heterogeneous sources

Lookup: looks up values and passes them to other objects

Update Strategy: tags rows for insert, update, delete, rejectRouter: splits rows conditionally

Sequence Generator: generates unique ID values


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Other Transformation Objects

Normalizer: normalizes records from relational or VSAM sources

Rank: filters the top or bottom range of records

Union: merges data from multiple pipelines into one pipeline

Transaction Control: allows user-defined commits

Stored Procedure: calls a database stored procedureExternal Procedure : calls compiled code for each row

Custom: calls compiled code for multiple rows

Midstream XML Parser: reads XML from database table or message queue

Midstream XML Generator: writes XML to database table or message queue

More Source Qualifiers: read from XML, message queues andapplications


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Transformation Views

A transformation hasthree views:

Iconizedshows thetransformation in relation

to the rest of themapping

Normalshows the flowof data through thetransformation

Editshowstransformation ports(= table columns)and properties;allows editing


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Expression Transformation

Ports Mixed

Variables allowed

Create expression in anoutput or variable port

Usage

Perform majority ofdata manipulation

Perform calculations using non-aggregate functions(row level)

Click here to invoke theExpression Editor


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Expression Validation

The Validate or OK button in the Expression Editor will:

Parse the current expression

Remote port searching (resolves references to ports inother transformations)

Parse default values

Check spelling, correct number of arguments in functions,other syntactical errors


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Character Functions Used to manipulate character data

CHRCODE returns the numeric value(ASCII or Unicode) of the first character of

the string passed to this function

CONCAT is for backward compatibility only.Use || instead

ASCIICHRCHRCODECONCATINITCAPINSTRLENGTH

LOWERLPADLTRIMREPLACECHRREPLACESTRRPAD

RTRIMSUBSTRUPPER

Informatica FunctionsCharacter


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TO_CHAR (numeric)

TO_DATETO_DECIMALTO_FLOATTO_INTEGER

Informatica FunctionsConversion

Conversion Functions Used to convert datatypes


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Informatica FunctionsData Cleansing

INSTRIS_DATEIS_NUMBERIS_SPACESISNULLLTRIMMETAPHONE

REPLACECHRREPLACESTRRTRIMSOUNDEXSUBSTRTO_CHARTO_DATE

TO_DECIMALTO_FLOATTO_INTEGER

Used to process data during datacleansing

METAPHONE and SOUNDEX createindexes based on Englishpronunciation (2 different standards)


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Date Functions

Used to round, truncate, orcompare dates; extract one part

of a date; or perform arithmeticon a date

To pass a string to a datefunction, first use the TO_DATE

function to convert it to andate/time datatype

ADD_TO_DATEDATE_COMPAREDATE_DIFFGET_DATE_PARTLAST_DAYROUND (Date)SET_DATE_PARTTO_CHAR (Date)TRUNC (Date)

Informatica FunctionsDate


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Numerical Functions Used to perform mathematical

operations on numeric data

ABSCEILCUMEEXPFLOORLNLOGMODMOVINGAVGMOVINGSUMPOWERROUNDSIGN

SQRTTRUNC

COSCOSHSINSINH

TANTANH

Scientific Functions

Used to calculategeometric values

of numeric data

Informatica FunctionsNumerical and Scientific


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Informatica FunctionsSpecial and Test

ABORTDECODEERROR

IIFLOOKUP

IIF(Condition,True,False)

IS_DATE

IS_NUMBERIS_SPACESISNULL

Test Functions

Used to test if a lookup result is null

Used to validate data

Special Functions

Used to handle specific conditionswithin a session; search for certainvalues; test conditional statements


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Variable Ports

Use to simplify complex expressions e.g. create and store a depreciation formula to be

referenced more than once

Use in another variable port or an output port expression

Local to the transformation (a variable port cannot also be aninput or output port)


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Variable Ports (contd)

Use for temporary storage

Variable ports can remember values across rows; useful for comparing

values Variables are initialized (numeric to 0, string to ) when the Mapping

logic is processed

Variables Ports are not visible in Normal view, only in Edit view


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Default ValuesTwo Usages

For input and I/O ports, default values are used to replacenullvalues

For output ports, default values are used to handle transformationcalculation errors (not-null handling)

Default

value for theselectedport

Selectedport Validate the

defaultvalueexpression

ISNULL functionis not required


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Informatica Datatypes

Transformation datatypes allow mix and matchof source and target database types When connecting ports, native and transformation datatypes must be compatible

(or must be explicitly converted)

NATIVE DATATYPES TRANSFORMATION DATATYPES

Specific to the source and targetdatabase types

PowerCenter internal datatypes

Display in source and target tableswithin Mapping Designer

Display in transformations withinMapping Designer

Native NativeTransformation


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Datatype Conversions within PowerCenter

Data can be converted from one datatype to another by: Passing data between ports with different datatypes

Passing data from an expression to a port

Using transformation functions

Using transformation arithmetic operators

Only conversions supported are:

Numeric datatypes Other numeric datatypes

Numeric datatypes String

Date/Time Date or String

For further information, see the PowerCenter Client Help > Index> port-to-port data conversion


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Mappings


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Mappings


The Mapping Designer interface

Transformation objects and views

Source Qualifier transformation

The Expression transformation

Mapping validation


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Mapping Designer

Iconized Mapping

Mapping List

Transformation Toolbar


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Source Qualifier Transformation

Ports All input/output

Usage Convert datatypes For relational sources:

Modify SQL statementUser Defined JoinSource Filter

Sorted portsSelect DISTINCTPre/Post SQL

Represents the source record set queried by the

Server. Mandatory in Mappings using relational orflat file sources


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Source Qualifier Properties

User can modify SQL SELECT statement (DB sources)

Source Qualifier can join homogenous tables

User can modify WHERE clause

User can modify join statement

User can specify ORDER BY (manually orautomatically)

Pre- and post-SQL can be provided

SQL properties do not apply to flat file sources


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Pre-SQL and Post-SQL Rules

Can use any command that is valid for the databasetype; no nested comments

Use a semi-colon (;) to separate multiple statements

Informatica Server ignores semi-colons within singlequotes, double quotes or within /* ...*/

To use a semi-colon outside of quotes or comments,escape it with a back slash (\)


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Mapping Validation


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Connection Validation

Examples of invalid connections in a Mapping:

Connecting ports with incompatible datatypes

Connecting output ports to a Source

Connecting a Source to anything but a SourceQualifier or Normalizer transformation

Connecting an output port to an output port oran input port to another input port

i i i


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Mapping Validation

Mappings must:

Be valid for a Session to run

Be end-to-end complete and contain valid expressions

Pass all data flow rules

Mappings are always validated when saved; can be validatedwithout being saved

Output Window displays reason for invalidity


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Lab 2Create a Mapping


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Workflows


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W kfl M I f


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Workflow Manager Interface

TaskTool Bar

OutputWindow

NavigatorWindow

Workspace

StatusBar

WorkflowDesignerTools

W kfl M T l


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Workflow Designer Maps the execution order and dependencies of Sessions,

Tasks and Worklets, for the Informatica Server

Task Developer Create Session, Shell Command and Email tasks

Tasks created in the Task Developer are reusable

Worklet Designer

Creates objects that represent a set of tasks

Worklet objects are reusable

Workflow Manager Tools

W kfl St t


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Workflow Structure

A Workf lowis set of instructions for the InformaticaServer to perform data transformation and load

Combines the logic of Session Tasks, other types ofTasks and Worklets

The simplest Workflow is composed of a Start Task, a

Link and one other Task

StartTask

SessionTask

Link


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Reusable Tasks

R bl T k


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Reusable Tasks

Three types of reusableTasks

SessionSet of instructionsto execute a specificMapping

CommandSpecific shellcommands to run duringany Workflow

EmailSends email during

the Workflow

R bl T k


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Reusable Tasks

Use the Task Developertocreate reusable tasks

These tasks will then appearin the Navigator and can bedragged and dropped intoany workflow

R bl T k i W kfl


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Reusable Tasks in a Workflow

In a workflow, a reusable task is representedwith the symbol

ReusableNon-reusable

C d T k


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Command Task

Specify one or more Unix shell or DOS commands torun duringthe Workflow

Runs in the Informatica Server (UNIX or Windows)environment

Command task status (successful completion orfailure) is held in the pre-defined task variable$command_task_name.STATUS

Each Command Task shell command can executebefore the Session begins or after the InformaticaServer executes a Session

Command Task


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Command Task

Specify one (or more) Unix shell or DOS (NT, Win2000)commands to run at a specific point in the workflow

Becomes a component of a workflow (or worklet)

If created in the Task Developer, the Command task is

reusable If created in the Workflow Designer, the Command task is

not reusable

Commands can also be invoked under the Components

tab of a Session task to run pre- or post-session

Command Task (contd)


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Add Cmd

Remove Cmd

Email Task


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Email Task

Configure to have the Informatica Server to send emailat any point in the Workflow

Becomes a component in a Workflow (or Worklet)

If configured in the Task Developer, the Email Task is

reusable (optional) Emails can also be invoked under the Componentstab

of a Session task to run pre- or post-session

Email Task (contd)


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Email Task (contd)


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Assignment Task


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Assignment Task

Assigns a value to a Workflow Variable Variables are defined in the Workflow object

Expressions Tab

General Tab

Timer Task


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Timer Task

Waits for a specified period of time to execute thenext Task

General Tab

Absolute Time

Datetime Variable

Relative Time

Timer Tab

Control Task


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Control Task

Stop or ABORT the Workflow

GeneralTab

Properties Tab

Event Wait Task


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Event Wait Task

Pauses processing of the pipeline until aspecified event occurs

Events can be:

Pre-definedfile watch

User-definedcreated by an Event Raise task elsewhere inthe workflow

Event Wait Task (contd)


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Event Wait Task (cont d)

General TabProperties Tab


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Session Task


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Session Task

Server instructions to run the logic of ONE specific mappinge.g. source and target data location specifications, memoryallocation, optional Mapping overrides, scheduling, processing andload instructions

Becomes a component of a

Workflow (or Worklet) If configured in the Task

Developer, the SessionTask is reusable (optional)

Additional Workflow Tasks


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Eight additional Tasks are available in the Workflow Designer (covered

later)

Command

Email

Decision

Assignment

Timer

Control

Event Wait

Event Raise

Additional Workflow Tasks

Sample Workflow


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Sample Workflow

Start Task(required)

Session 1

Session 2

Command

Task

Sequential and Concurrent Workflows


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Sequential and Concurrent Workflows

Sequential

Concurrent Combined

Note: Although only session tasks are shown, can be any tasks


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Workflow Properties


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Workflow Properties

Customize WorkflowProperties

Workflow log displays

May be reusable ornon-reusable

Select a WorkflowSchedule (optional)

Workflow Scheduler


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Workflow Scheduler

Set and customize workflow-specific schedule

Workflow Metadata Extensions


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Wo ow etadata te s o s

Metadata Extensions providefor additional user data


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Conditional Links


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Optional linkcondition

$taskname.STATUSis a pre-defined

task variable

Workflow Variables 1


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Task-specificvariables

Built-in systemvariables

Used in decision tasks and conditional linksedit task or link:

User-defined variables(see separate slide)

Pre-defined variables

Workflow Variables 2


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User-defined variables are set in Workflow properties,

Variables tabcan persist across sessions

Can be reset inan Assignment task

Workflow Summary


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y

1. Add Sessions and other Tasks to the Workflow

2. Connect all Workflow components with Links

3. Save the Workflow

Sessions in a Workflow can be executed independently

4. Start the Workflow


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Session Tasks


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After this section, you will be familiar with:

How to create and configure Session Tasks

Session Task source and target properties

Creating a Session Task


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Created to execute the logic of a mapping (one

mapping only)

Session Tasks can be created in the Task Developer(reusable) or Workflow Developer (Workflow-specific)

To create a Session Task

Select the Session button from the Task Toolbar

OrSelect menu Tasks | Create and select Session from thedrop-down menu

g

Session TaskProperties and Parameters


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p

Session Task

Sessionparameter

Properties Tab

Parameter file

Session TaskSetting Source Properties


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g

Set

properties

Session Task

Selectsourceinstance

Mapping Tab

Setconnection


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Monitoring Workflows

Monitoring Workflows


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The Workflow Monitor GUI interface

Monitoring views

Server monitoring modes Filtering displayed items

Actions initiated from the Workflow Monitor

Truncating Monitor Logs

Workflow Monitor


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The Workflow Monitor is the tool for monitoring

Workflows and Tasks Choose between two views:

Gantt chart

Task view

Gantt Chart view Task view

Monitoring Current and Past Workflows


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The Workflow Monitor displays only workflowsthat have been run

Displays real-time information from theInformatica Server and the Repository Server

about current workflow runs

Monitoring Operations


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Perform operations in the Workflow Monitor

Stop, Abort, or Restart a Task, Workflow or Worklet Resume a suspended Workflow after a failed Task is

corrected

Reschedule or Unschedule a Workflow

View Session and Workflow logs Abort has a 60 second timeout

If the Server has not completed processing andcommitting data during the timeout period, the threadsand processes associated with the Session are killed

Stopping a Session Task means the Server stops reading data

Monitoring in Task View


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Start CompletionTask Server Workflow Worklet Time Time

Status Bar

Start, Stop, Abort, ResumeTasks,Workflows and Worklets

Filtering in Task View


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Monitoring filterscan be set usingdrop down menus.Minimizes itemsdisplayed in

Task View

Right-click on Session to retrieve theSession Log (from the Server to thelocal PC Client)

Filter Toolbar


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Display recent runs

Filter tasks by specified criteria

Select servers to filter

Select type of tasks to filter

Truncating Workflow Monitor Logs


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Workflow Monitor

Repository Manager

Repository Managers

Truncate Log optionclears the WorkflowMonitor logs


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Lab 3Create and Run a Workflow


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Lab 4Features and Techniques I


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Debugger


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By the end of this section you will be familiar with: Creating a Debug Session

Debugger windows and indicators

Debugger functionality and options Viewing data with the Debugger

Setting and using Breakpoints

Tips for using the Debugger

Debugger Features


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Wizard driven tool that runs a test session View source / target data

View transformation data

Set breakpoints and evaluate expressions

Initialize variables

Manually change variable values

Data can be loaded or discarded

Debug environment can be saved for later use

Debugger Interface


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Target Instancewindow

TransformationInstance

Data window

Flashingyellow

SQLindicator

Debugger Modeindicator

Solid yellowarrow is currenttransformation

indicator

Output WindowDebugger Log

Edit

Breakpoints

Set Breakpoints


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2. Choose global orspecific transformation

3. Choose to break on

data condition or error.Optionally skip rows.

4. Add breakpoint(s)

5. Add data conditions

1. Edit breakpoint

6. Continue (to next breakpoint)

Debugger Tips


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Server must be running before starting a Debug Session When the Debugger is started, a spinning icon displays.

Spinning stops when the Debugger Server is ready

The flashing yellow/green arrow points to the current active

Source Qualifier. The solid yellow arrow points to the currentTransformation instance

Next Instanceproceeds a single step at a time; onerow moves from transformation to transformation

Step to Instanceexamines one transformation at atime, following successive rows through the sametransformation


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Lab 5The Debugger


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Filter Transformation

Filter Transformation


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Ports All input / output

Specify a Filter condition

Usage Filter rows from

input flow

Drops rows conditionally


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Lab 6Flat File Wizard and Filter

Transformation


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Sorter Transformation



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Can sort data from relational tables or flat files

Sort takes place on the Informatica Server machine

Multiple sort keys are supported

The Sorter transformation is often more efficient thana sort performed on a database with an ORDER BYclause



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Sorts data from any source, at any point in a data flow

Ports Input/Output Define one or more

sort keys Define sort order for

each key

Example of Usage Sort data before

Aggregator to improve

performance

Sort Keys

Sort Order

Sorter Properties


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Cache size can beadjusted. Default is 8 Mb.Ensure sufficient memoryis available on theInformatica Server (elseSession Task will fail)


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Aggregator Transformation



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By the end of this section you will be familiar with: Basic Aggregator functionality

Creating subtotals with the Aggregator

Aggregator expressions Aggregator properties

Using sorted data



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Ports Mixed I/O ports allowed Variable ports allowed Group By allowed

Create expressions invariable and output ports

Usage Standard aggregations

Performs aggregate calculations

Aggregate Expressions


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Conditional Aggregateexpressions are supported: Conditional SUM format: SUM(value, condition)

Aggregatefunctions aresupported only inthe AggregatorTransformation

Aggregator Functions


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Return summary values for non-null data

in selected ports Use only in Aggregator transformations

Use in output ports only

Calculate a single value (and row) for all

records in a group

Only one aggregate function can benested within an aggregate function

Conditional statements can be used with

these functions

AVGCOUNTFIRSTLASTMAXMEDIAN

MINPERCENTILESTDDEVSUMVARIANCE

Aggregator Properties


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Sorted Input Property

Set Aggregatorcache sizes forInformatica Server

machine

Instructs theAggregator toexpect the data

to be sorted

Sorted Data


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The Aggregator can handle sorted or unsorted data

Sorted data can be aggregated more efficiently, decreasing totalprocessing time

The Server will cache data from each group andrelease the cached dataupon reaching the firstrecord of the next group

Data mustbe sorted according to the order of theAggregators Group By ports

Performance gain will depend upon varying factors

Aggregating Unsorted Data


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Unsorteddata

No rows are released from Aggregatoruntil all rows are aggregated

Group By:- store- department- date

Aggregating Sorted Data


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Each separate group (one row) is released assoon as the last row in the group isaggregated

Group By:

- store- department- date

Data sorted by:

- store- department- date

Data Flow RulesTerminology


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Passive transformation Operates on one row of data at a time AND

Cannot change the number of rows on the data flow

Example: Expression transformation

Active transformation

Can operate on groups of data rows AND/OR

Can change the number of rows on the data flow

Examples: Aggregator, Filter, Source Qualifier

Data Flow Rules


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Each Source Qualifier starts a single data stream (data flow)

Transformations can send rows to more than onetransformation (split one data flow into multiple pipelines)

Two or more data flows can meet only if they originate from acommon active transformation

Example holds true with Normalizer instead of Source Qualifier.Exceptions are: Mapplet Input and sorted Joiner transformations

DISALLOWED

TT

Active

ALLOWED

T

Passive

T


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Joiner Transformation


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When to join in Source Qualifier and when in Joinertransformation

Homogeneous joins

Heterogeneous joins

Joiner properties

Joiner conditions

Nested joins

When to Join in Source Qualifier


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If you can perform a join on the source database, then

you can configure it in the Source Qualifier The SQL that the Source Qualifier generates, default or

custom, executes on the source database at runtime

Example: homogeneous join2 database tables in same

database

When You Cannot Join in Source Qualifier


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If you cannotperform a join on the source database, then

you cannotconfigure it in the Source Qualifier

Examples: heterogeneous joins

An Oracle table and a DB2 table

A flat file and a database table

Two flat files

Joiner Transformation


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Active Transformation

Ports All input or input / output

M denotes port comesfrom master source

Examples Join two flat files Join two tables from

different databases

Join a flat file with arelational table

Performs heterogeneous joins on different data

flows

Joiner Conditions


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Multiple join conditions aresupported

Joiner Properties


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Join types: Normal (inner)

Master outer

Detail outer

Full outer

Joiner can accept sorted data (configure the join condition to use thesort origin ports)

Set JoinerCaches


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Mid-Mapping Join (Unsorted)


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The unsorted Joiner does not accept input in thefollowing situations: Both input pipelines begin with the same Source Qualifier

Both input pipelines begin with the same Joiner

The sorted Joiner does not have these restrictions.


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Lab 7Heterogeneous Join, Aggregator, and

Sorter


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Lookup Transformation



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Lookup principles

Lookup properties

Lookup conditions

Lookup techniques

Caching considerations

Persistent caches

How a Lookup Transformation Works

F h i t l l k d i


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For each mapping row, one or more port values are looked up in adatabase table or flat file

If a match is found, one or more table values are returned to themapping. If no match is found, NULL is returned

Lookup value(s)

Return value(s)

Lookup transformation



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Looks up values in a database table or flat file and

provides data to other components in a mapping

Ports Mixed L denotes Lookup port R denotes port used as a

return value (unconnectedLookup onlysee later)

Specify the Lookup Condition

Usage Get related values

Verify if records exists or ifdata has changed

Lookup Conditions


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Multiple conditions are supported


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Lookup Properties contd


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Policy on multiplematch:Use first valueUse last valueReport error


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Lookup Caching Properties (contd)


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Set Lookupcache sizes

Make cachepersistent

Set prefix forpersistent cachefile name

Reloadpersistentcache


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Lab 8Basic Lookup


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Setting Default Target Load Type


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Set Target Load Type defaultWorkflow Manager, Tools | OptionsNormal or Bulk (client choice)Override the default in sessiontarget properties

Target Properties

Edit Tasks: Mappings Tab


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Session Task

Select target

instance

Row loadingoperations

Error handling

pp g

Target load type

WHERE Clause for Update and Delete

PowerCenter uses the primary keys defined in the


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PowerCenter uses the primary keys defined in the

Warehouse Designer to determine the appropriate SQLWHERE clause for updates and deletes

Update SQL

UPDATE SET = WHERE =

The only columns updated are those which have values linkedto them

All other columns in the target are unchanged

The WHERE clause can be overridden via Update Override

Delete SQL DELETE from WHERE =

SQL statement used will appear in the Session log file

Constraint-based Loading


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PK1

FK1 PK2

FK2

To maintain referential integrity, primary keys mustbe loaded before their corresponding foreign keyshere in the order Target1, Target2, Target 3

Setting Constraint-based Loading


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Constraint-based LoadingTerminology


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Active transformation

Can operate on groups of data rows and/orcan change the number of rows on the data flow

Examples: Source Qualifier, Aggregator, Joiner, Sorter, Filter

Active source

Active transformation that generates rows Cannot match an output row with a distinct input row

Examples: Source Qualifier, Aggregator, Joiner, Sorter

(The Filter is NOT an active source)

Active group Group of targets in a mapping being fed by the same active

source


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Lab 9Deleting Rows


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Update Strategy Transformation

Used to specify how each individual row will be used to


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Used to specify how each individual row will be used to

update target tables (insert, update, delete, reject)

Ports All input / output Specify the Update

Strategy ExpressionIIF or DECODE logicdetermines how tohandle the record

Example Updating Slowly

Changing Dimensions

Update Strategy Expressions


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IIF ( score > 69, DD_INSERT, DD_DELETE )

Expression is evaluated for each row

Rows are tagged according to the logic of theexpression

Appropriate SQL (DML) is submitted to the targetdatabase: insert, delete or update

DD_REJECT means the row will not have SQL written

for it. Target will not see that row Rejected rows may be forwarded through Mapping


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Lab 10Data Driven Operations


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Lab 11Incremental Update


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Lab 12Features and Techniques II


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Router Transformation

Router Transformation

Rows sent to multiple filter conditions


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Rows sent to multiple filter conditions

Ports All input/output Specify filter conditions

for each Group

Usage Link source data in

one pass to multiplefilter conditions


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Router Transformation in a Mapping


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Sequence Generator

Transformation

Sequence Generator Transformation

Generates unique keys for any port on a row


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Generates unique keys for any port on a row

Ports Two predefined output

ports, NEXTVAL and

CURRVAL No input ports allowed

Usage Generate sequence

numbers

Shareable across mappings

Sequence Generator Properties


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Number ofcached values


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Mapping Parameters and

Variables

Mapping Parameters and Variables

B th d f thi ti ill d t d


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By the end of this section you will understand:

System variables

Mapping parameters and variables

Parameter files

System Variables

SYSDATE Provides current datetime on the

Informatica Server machine


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SESSSTARTTIME

$$$SessStartTime

Returns the system date value on theInformatica Server Used with any function that accepts

transformation date/time datatypes

Not to be used in a SQL override Has a constant value

Returns the system date value as astring. Uses system clock on machinehosting Informatica Server Format of the string is database type

dependent Used in SQL override Has a constant value

Informatica Server machine

Not a static value


Apply to all transformations within one Mapping


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Apply to all transformations within one Mapping

Represent declared values

Variables can change in value during run-time

Parameters remain constant during run-time

Provide increased development flexibility

Defined in Mapping menu

Format is $$VariableName or $$ParameterName

Can be used in pre and post-SQL


Sample declarations


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Declare Mapping Variables and Parametersin the Designer Mappings/Mapplets menu

Set

aggregationtype

Set optionalinitial value

User-definednames

Set datatype


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Parameters & VariablesInitialization Priority


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1. Parameter file

2. Repository value

3. Declared initial value

4. Default value


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Unconnected Lookups

Unconnected Lookups

By the end of this section you will know:


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By the end of this section you will know:

Unconnected Lookup technique

Unconnected Lookup functionality

Difference from Connected Lookup

Unconnected Lookup

Physically unconnected from other transformationsNO data flowarrows leading to or from an unconnected Lookup


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arrows leading to or from an unconnected Lookup Lookup data is called from the point in the Mapping that needs it Lookup function can be set within any transformation that supports

expressions

Function in the Aggregator

calls the unconnected Lookup

Unconnected Lookup Technique

Use lookup lookup function within a conditional statement


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Condition is evaluated for each row but Lookup function

is called only if condition satisfied

IIF ( ISNULL(customer_id),:lkp.MYLOOKUP(order_no))

Condi t ion

Lookup func t ion

Row keys

(passed to Loo kup)

Unconnected Lookup Advantage

Data lookup is performed only for those rows which


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require it. Substantial performance can be gained

EXAMPLE: A Mapping will process 500,000 rows. For twopercent of those rows (10,000) the item_id value is NULL.Item_ID can be derived from the SKU_NUMB.

Net savings = 490,000 lookups

IIF ( ISNULL(item_id), :lkp.MYLOOKUP (sku_numb))

Condi t ion

(true for 2 percent of all rows)

Lookup

(called only when condition is true)

Unconnected Lookup Functionality

OneLookup port valuemay be returned for each Lookup


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Must check aReturn port in the

Ports tab, elsefails at runtime

Connected versus Unconnected Lookups

CONNECTED LOOKUP UNCONNECTED LOOKUP


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Part of the mapping data flow Separate from the mapping dataflow

Returns multiple values (bylinking output ports to anothertransformation)

Returns one value - by checkingthe Return (R) port option for theoutput port that provides the

return value

Executed for every recordpassing through thetransformation

Only executed when the lookupfunction is called

More visible, shows where the

lookup values are used

Less visible, as the lookup is

called from an expression withinanother transformation

Default values are used Default values are ignored


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Lab 14Straight Load


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Lab 15Conditional Lookup


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Mapplets

Mapplets



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Mapplet Designer

Mapplet advantages

Mapplet types

Mapplet rules

Active and Passive Mapplets

Mapplet Parameters and Variables

Mapplet Designer


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MappletInput and OutputTransformation

Icons

Mapplet OutputTransformation

Mapplet Designer Tool

Mapplet Advantages

Useful for repetitive tasks / logic


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Useful for repetitive tasks / logic

Represents a set of transformations

Mapplets are reusable

Use an instance of a Mapplet in a Mapping

Changes to a Mapplet are inherited by all instances

Server expands the Mapplet at runtime

A Mapplet Used in a Mapping


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The Detail Inside the Mapplet


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Unsupported Transformations

You cannot not use the following in a mapplet:


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Normalizer Transformation

XML source definitions

Target definitions

Other mapplets

Mapplet Source Options

Internal Sources


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One or more Source definitions / Source Qualifierswithinthe Mapplet

External Sources

Mapplet contains a Mapplet Input transformation

Receives data from the Mapping it is used in

Mixed Sources

Mapplet contains one or more of either of a Mapplet

Input transformation AND one or more Source Qualifiers

Receives data from the Mapping it is used in, AND fromthe Mapplet


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Data Source Outsidea Mapplet

Source data is definedOUTSIDE the Mapplet logic


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Resulting Mapplet HASinput ports

When used in a Mapping,the Mapplet may occur atany point in mid-flow

OUTSIDE the Mapplet logic

Mapplet

Mapplet Input

Transformation

Data Source I nsidea Mapplet

Source

Qualifier

Source data is definedWITHIN the Mapplet logic


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Resulting Mapplet has noinput ports

When used in a Mapping,the Mapplet is the firstobject in the data flow

Mapplet

No Input transformationis required (or allowed)

Use a Source Qualifier

instead

QualifierWITHIN the Mapplet logic

Mapplet Output Transformation

Use to contain the results of a Mapplet pipeline. MultipleOutput transformations are allowed.


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Passive TransformationConnected

Ports

Input ports only

Usage

Only those ports connected toan Output transformation (fromanother transformation) will

display in the resulting Mapplet One (or more) Mapplet Output

transformations are required inevery Mapplet

Output transformations are allowed.

Mapplet with Multiple Output Groups


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Can output to multiple instances of the same target table

Unmapped Mapplet Output Groups


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Warning:An unlinkedMapplet Output Groupmay invalidate themapping

Active and Passive Mapplets


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Passive Mapplets contain only passive transformations Active Mapplets contain one or more active

transformations

CAUTION: Changing a passive Mapplet into an active Mappletmay invalidate Mappings which use that Mappletso do an impactanalysis in Repository Manager first

Using Active and Passive Mapplets


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Multiple PassiveMapplets can populatethe same targetinstance

Multiple Active Mappletsor Active and PassiveMapplets cannotpopulate the same

target instance

Active

Passive

Mapplet Parameters and Variables


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Same idea as mapping parameters and variables Defined under the

Mapplets | Parameters and Variablesmenu option

A parameter or variable defined in a mapplet is notvisible in any parent mapping

A parameter or variable defined in a mapping is notvisible in any child mapplet


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Lab 17Mapplets


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Reusable Transformations



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By the end of this section you will be familiar with: Transformation Developer

Reusable transformation rules

Promoting transformations to reusable Copying reusable transformations


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Define once, reuse many times


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Reusable Transformations Can be a copy or a shortcut

Edit Ports only in Transformation Developer

Can edit Properties in the mapping

Instances dynamically inherit changes

Caution:changing reusable transformationscan invalidatemappings

Note: Source Qualifier transformations cannotbe made reusable

Promoting a Transformation to Reusable


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Check theMake reusable box

(irreversible)


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Lab 18Reusable Transformations


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Error Logging Objectives


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By the end of this section, you will be familiar with: Setting error logging options

How data rejects and transformation errors are

handled with logging on and off

How to log errors to a flat file or relational table

When and how to use source row logging

Error Types


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Transformation error Data row has only passed partway through the mapping

transformation logic

An error occurs within a transformation

Data reject Data row is fully transformed according to the mapping

logic

Due to a data issue, it cannot be written to the target

A data reject can be forced by an Update Strategy

Error Logging Off/On

Error Type Logging OFF (Default) Logging ON


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Transformationerrors

Written to session logthen discarded

Appended to flat file orrelational tables. Onlyfatal errors written tosession log.

Data rejects Appended to reject file(one .bad file per target)

Written to row errortables or file

Setting Error Log Options

In Session task


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Log Row DataLog Source Row Data

Error Log Type

Error Logging OffSpecifying Reject Files

In Session task


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1 file per target

Error Logging OffTransformation Errors

Details and data are written to session log


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X

X

Transformation Error

Data row is discarded If data flows concatenated, corresponding rows in parallel

flow are also discarded

Error Logging OffData Rejects

Conditions causing data to be rejected include:

T d b i i l i f l


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Target database constraint violations, out-of-space errors, logspace errors, null values not accepted

Data-driven records, containing value 3 or DD_REJECT(the reject has been forced by an Update Strategy)

Target table properties reject truncated/overflowed rows

0,D,1313,D,Regulator System,D,Air Regulators,D,250.00,D,150.00,D1,D,1314,D,Second Stage Regulator,D,Air Regulators,D,365.00,D,265.00,D2,D,1390,D,First Stage Regulator,D,Air Regulators,D,170.00,D,70.00,D3,D,2341,D,Depth/Pressure Gauge,D,Small Instruments,D,105.00,D,5.00,D

Sample reject file

Indicator describes preceding column valueD=Data, O=Overflow, N=Null or T=Truncated

First column:0=INSERT1=UPDATE2=DELETE3=REJECT

Log Row Data

Logs:


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Session metadata

Reader, transformation, writer and user-defined errors

For errors on input, logs row data for Iand I/Oports

For errors on output, logs row data for I/Oand Oports


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Error Logging to a Flat File 1

Creates delimited Flat File with || as column delimiter


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Flat File LogSettings (Defaults

shown)

Logging Errors to a Flat File 2

Format: Session metadata followed by de-normalized error information

Sample session metadata

**********************************************************************


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**********************************************************************Repository GID: 510e6f02-8733-11d7-9db7-00e01823c14d

Repository: RowErrorLogging

Folder: ErrorLogging

Workflow: w_unitTests

Session: s_customers

Mapping: m_customers

Workflow Run ID: 6079Worklet Run ID: 0

Session Instance ID: 806

Session Start Time: 10/19/2003 11:24:16

Session Start Time (UTC): 1066587856

**********************************************************************

Row data formatTransformation || Transformation Mapplet Name || Transformation Group || PartitionIndex || Transformation Row ID || Error Sequence || Error Timestamp || Error UTCTime || Error Code || Error Message || Error Type || Transformation Data || SourceMapplet Name || Source Name || Source Row ID || Source Row Type || Source Data

Log Source Row Data 1

S t h kb i i t k


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Separate checkbox in session task Logs the source row associated with the error row

Logs metadata about source, e.g. Source Qualifier,

source row id, and source row type

Log Source Row Data 2

Source row logging is not available downstream of anAggregator, Joiner, Sorter (where output rows are not

i l l t d ith i t )


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Source row loggingavailable

Source row loggingnot available

uniquely correlated with input rows)


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Workflow Configuration

Workflow Configuration Objectives

By the end of this section, you will be able to create:


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Workflow Server Connections

Reusable Schedules

Reusable Session Configurations


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Relational Connections (Native )

Create a relational [database] connection Instructions to the Server to locate relational tables

Used in Session Tasks


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Relational Connection Properties

Define nativerelational database

connection


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connection

Optional Environment SQL(executed with each use ofdatabase connection)

User Name/Password

Database connectivityinformation

Rollback Segmentassignment (optional)

FTP Connection

Create an FTP connection

Instructions to the Server to ftp flat files



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External Loader Connection

Create an External Loader connection

Instructs the Server to invoke an external database loader



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Set up reusable schedules to associate with multiple Workflows

Defined at folder level

Must have the Workflow Designer tool open

Reusable Workflow Schedules


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Must have the Workflow Designer tool open

Reusable Workflow Schedules


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Reusable Session Configurations

Session Configuration

Define properties to be reusable across differentsessions


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sessions

Defined at folder level

Must have one of these toolsopen in order to access

Session Configuration (contd)


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Available from menu orTask toolbar

Session Configuration (contd)


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Session TaskConfig Object


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Within Session task properties, choose desired

configuration

Session TaskConfig Object Attributes


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Attributes

may beoverriddenwithin theSession task


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Worklets

Worklets

An object representing a set or grouping of Tasks

Can contain any Task available in the Workflow


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Can contain any Task available in the WorkflowManager

Worklets expand and execute inside a Workflow

A Workflow which contains a Worklet is called theparent Workflow

Worklets CAN be nested

Reusable Workletscreate in the WorkletDesigner

Non-reusable Workletscreate in the WorkflowDesigner

Re-usable Worklet

In the Worklet Designer, select Worklets | Create


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Tasks in a Worklet

WorkletsNode

Using a Reusable Worklet in a Workflow


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Workletused in aWorkflow

Non-Reusable Worklet

1. Create worklet task inWorkflow Designer

2. Right-click on new worklet


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gand select Open Worklet

3. Workspace switches toWorklet Designer

NOTE: Worklet

shows only underWorkflows node


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Lab 21Reusable Worklet and Decision Task


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Lab 22Event Wait with Pre-Defined Event


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Parameters and VariablesReview

Types of Parameters and Variables

TYPE HOW DEFINED WHERE USED EXAMPLES

Mapping/Mapplet

Variables

Mapping/mappletproperties. Reset by

variable functions.

Transformation portexpressions

$$LastUpdateTime$$MaxValue

Mappings


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Mapping/MappletParameters

Mapping/mappletproperties. Constantfor session.

Transformation portexpressions

$$FixedCosts$$DiscountRate

SystemVariables

Built-in, pre-defined. Transformation portexpressions,Workflow decisiontasks andconditional links.

SYSDATESESSSTARTIMEWORKFLOWSTARTTIME

TaskVariables

Built-in, pre-defined. Workflow decisiontasks andconditional links

$session1. Status$session1.ErrorCode

Workflow/

WorkletVariables

Workflow or worklet

properties. Reset inAssignment tasks.

Workflow decision

tasks andconditional links

$$NewStartTime

SessionParameters

Parameter file.Constant for session.

Session properties $DBConnectionORCL$InputFile1

Mappings& Mapplets

Workflows& Worklets


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PowerCenter 7.1 Options andData Access Products

PowerCenter 7.1 Options

N d dd l i f ti lit i l di

Profile wizards, rules definitions, profile results tables,

and standard reportsData Profiling

Allows export/import of metadata to or from businessintelligence tools like Business Objects and CognosMetadata Exchange with BI


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PowerCenter

Real-Time/Web ServicesZL Engine, always-on non-stop sessions, JMS

connectivity, and real-time Web Services provider

Data CleansingName and address cleansing functionality, includingdirectories for US and certain international countries

PartitioningData smart parallelism, pipeline and data parallelism,partitioning

Server engine, metadata repository, unlimited designers,workflow scheduler, all APIs and SDKs, unlimited XML andflat file sourcing and targeting, object export to XML file,LDAP authentication, role-based object-level security,metadata reporter, centralized monitoring

Server group management, automatic workflow distributionacross multiple heterogeneous serversServer Grid

Version control, deployment groups, configurationmanagement, automatic promotion

Team-Based Development

Virtual Classes

Watch for short web-based virtual

classes on most PowerCenterti d XML t


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options and XML support

Data AccessPowerExchange

Provides access to all critical enterprise data systems,including mainframe, midrange relational databases,and file-based systems


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a d e based sys e s

Offers batch, change capture and real-time options

PowerExchange 5.2 provides tight integration withPowerCenter 7.1.1 through the PowerExchange Clientfor PowerCenter

Supporting VSAM, IMS, DB2 (OS/390, AS/400), Oracle, ODBC

Data AccessPowerCenter Connect

PowerCenter Connect options are currently available for:

Transactional Applications Real-time Services


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Transactional ApplicationsHyperion EssbasePeopleSoftSAP R/3SAP BWSASSiebel

HTTPJMSMSMQMQSeriesTIBCOWebMethodsWeb Services

PowerCenter Connect SDK

Allows development of new PowerCenter Connect productsAvailable on the Informatica Developer Network


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