Preface
Transformations
- Active and passive transformations
- Transformation types
- Licensed transformations
- Generate configured transformations
  - Prompts to generate configured transformations
- Incoming fields
  - Field name conflicts
    - Creating a field name conflict resolution
  - Field rules
- Data object preview
- Variable fields
- Transformation caches
- Expression editor
- Expression macros
- Generate an expression
  - Rules and guidelines for generating expressions
  - Prompts to generate expressions
- File lists
- Configuration for multibyte hierarchical data
Source transformation
- Source object
- Object Missing
- Database sources
- Web service sources
- Partitions
  - Partitioning rules and guidelines
  - Partitioning examples
- Reading hierarchical data in advanced mode
- Reading documents in advanced mode
- Configuration for multibyte hierarchical data
- Source fields
  - Editing native data types in complex file sources
  - Editing transformation data types
Target transformation
- Target object
  - Target file creation on advanced clusters
- File targets
- Database targets
- Web service targets
  - Web service operations for targets
  - Field mapping for web service targets
- Partitions
- Writing hierarchical data in advanced mode
- Configuration for multibyte hierarchical data
- Target fields
- Target transformation field mappings
- Configuring a Target transformation
Access Policy transformation
- Data access policies overview
- Before you begin
- Adding an Access Policy transformation to a mapping
- Configuring an Access Policy transformation
- Access policy transformation best practices
- Using parameters in Access Policy transformations
- Access Policy transformation example
- Unmasking protected data
Aggregator transformation
- Group by fields
- Sorted data
- Aggregate fields
- Advanced properties
- Hierarchical data in advanced mode
- Aggregator transformation example
B2B transformation
- B2B Incoming Fields
- B2B settings
- Output fields
- Field mapping
- Advanced settings
Chunking transformation
- Chunking methods
- Text processing functions
- Output fields
Cleanse transformation
- Cleanse transformation configuration
  - Cleanse asset considerations
  - Synchronizing data quality assets
- Cleanse transformation field mappings
- Cleanse transformation output fields
- Advanced properties
Data Masking transformation
- Masking techniques
- Configuration properties for masking techniques
- Credit card masking
- Email masking
  - Advanced email masking
- IP address masking
- Key masking
- Phone number masking
- Random masking
- Social Insurance number masking
- Social Security number masking
- Custom substitution masking
- Dependent masking
  - Dependent masking parameters
- Substitution masking
- URL address masking
- Mask rule parameter
- Mask rule parameter example
  - Create a mapping with parameters
  - Run the mapping
- Creating a Data Masking transformation
- Consistent masked output
  - Rules and guidelines
  - Example
- Data Masking transformation example
Data Services transformation
- Dynamic service name
- Status tracing messages
- Data Services properties
- Data Services transformation input fields
- Data Services transformation output fields
- Data Services transformation field mapping
Deduplicate transformation
- Deduplication and consolidation operations
- Identity population data
- Groups in duplicate analysis
  - Example: Selecting a group key column
- Deduplicate transformation configuration
- Deduplicate transformation field mappings
- Metadata fields on the Deduplicate transformation
- Link scores and driver scores
- Deduplicate transformation output fields
- Advanced properties
Expression transformation
- Expression fields
- Window functions
- Advanced properties
- Hierarchical data in advanced mode
Filter transformation
- Filter conditions
- Advanced properties
- Hierarchical data in advanced mode
Hierarchy Builder transformation
- Configure output settings
- Hierarchical schemas
- Join and map fields for data conversion
  - Joining incoming data
  - Mapping relational fields to hierarchy fields
- Configure advanced properties
- Configuration for multibyte hierarchical data
- Hierarchy Builder transformation example
Hierarchy Parser transformation
- Using a Hierarchy Parser transformation
- Hierarchy Parser rules and guidelines
- Choosing a sample or schema file
- Hierarchical schemas
- Input settings
  - Selecting a hierarchical schema
  - Creating a hierarchical schema from sample
- Input field selection
- Field mapping
  - Selecting the elements to convert
- Output fields
- Selecting an output group
- Configuration for multibyte hierarchical data
- Hierarchy Parser transformation example
Hierarchy Processor transformation
- Hierarchy Processor transformation overview
- Processing relational output
- Processing hierarchical output
- Processing flattened output
Input transformation
- Input fields
Java transformation
- Defining a Java transformation
- Classpath configuration
- Java transformation fields
- Configuring Java transformation properties
- Developing the Java code
- Compiling the code
  - Viewing the full class code
- Troubleshooting a Java transformation
  - Finding the source of compilation errors
  - Identifying the error type
- Java transformation example
Java transformation API reference
- failSession
- generateRow
- getInRowType
- incrementErrorCount
- invokeJExpression
- isNull
- logError
- logInfo
- setNull
- setOutRowType
Joiner transformation
- Join condition
- Join type
- Advanced properties
- Hierarchical data in advanced mode
- Creating a Joiner transformation
- Joiner transformation example
Labeler transformation
- Labeler transformation configuration
- Labeler transformation field mappings
- Labeler transformation output fields
Lookup transformation
- Lookup object
  - Lookup object properties
    - Multiple match policy restrictions
  - Custom queries
- Lookup condition
- Lookup return fields
- Advanced properties
- Lookup SQL overrides
- Lookup source filter
- Dynamic lookup cache
- Persistent lookup cache
  - Rebuilding the lookup cache
- Unconnected lookups
  - Configuring an unconnected Lookup transformation
  - Calling an unconnected lookup from another transformation
- Connected Lookup example
- Dynamic Lookup example
- Unconnected Lookup example
Machine Learning transformation
- Deploying the model as a REST endpoint
- Accessing the machine learning model
- Mapping fields to the request schema
  - Mapping hierarchical fields
  - Request mapping options
- Viewing response fields
- Configuring bulk requests
  - Bulk request options
- Configuring an API proxy
- Troubleshooting
- Error handling
- Machine Learning transformation example
Mapplet transformation
- Mapplet transformation configuration
- Selecting a mapplet
- Mapplet transformation field mappings
- Mapplet parameters
- Mapplet transformation output fields
- Mapplet transformation names
- Synchronizing a mapplet
Normalizer transformation
- Normalized fields
- Normalizer field mapping
  - Normalizer field mapping options
- Advanced properties
- Target configuration for Normalizer transformations
- Normalizer field rule for parameterized sources
- Mapping example with a Normalizer and Aggregator
Output transformation
- Output fields
  - Generating output fields based on incoming fields
- Field mapping
Parse transformation
- Parse transformation configuration
- Parse transformation field mappings
- Parse transformation output fields
- Advanced properties
Python transformation
- Install and configure Python
- Python transformation fields
- Active and passive Python transformations
- Resource files
- Developing the Python code
  - Creating Python code snippets
  - Referencing a resource file
- Example: Add an ID column to nonpartitioned data
- Example: Use partitions to find the highest salary
- Example: Operationalize a pre-trained model
Rank transformation
- Ranking string values
- Rank caches
- Defining a Rank transformation
- Rank transformation fields
- Defining rank properties
- Defining rank groups
- Advanced properties
- Hierarchical data in advanced mode
- Rank transformation example
Router transformation
- Working with groups
  - Guidelines for connecting output groups
- Group filter conditions
  - Configuring a group filter condition
- Advanced properties
- Hierarchical data in advanced mode
- Router transformation examples
Rule Specification transformation
- Rule Specification transformation configuration
- Rule Specification transformation field mappings
- Rule Specification transformation output fields
- Advanced properties
Sequence transformation
- Sequence transformation uses
- Sequence output fields
- Sequence properties
  - Disabling incoming fields
- Hierarchical data in advanced mode
- Sequence transformation rules and guidelines
- Sequence transformation example
Sorter transformation
- Sort conditions
- Sorter caches
- Advanced properties
- Hierarchical data in advanced mode
- Sorter transformation example
SQL transformation
- Stored procedure or function processing
- Connected or unconnected SQL transformation for stored procedure processing
- Unconnected SQL transformations
- Query processing
- SQL transformation configuration
Structure Parser transformation
- Processing input from a Hadoop Files source
- Processing input from a flat file source
  - Configuring the flat file source
  - Configuring the Structure Parser transformation to access flat files
- Structure Parser field mapping
- Output fields
- Advanced properties
- Structure Parser transformation configuration
- Rules and guidelines for the Structure Parser transformation
- Structure Parser transformation example
Transaction Control transformation
- Transaction control condition
- Downstream effects of the Transaction Control transformation
  - Sample transaction control mappings with multiple targets
- Guidelines for using Transaction Control transformations in mappings
- Advanced properties
Union transformation
- Comparison to Joiner transformation
- Planning to use a Union transformation
- Input groups
- Output fields
- Field mappings
- Advanced properties
- Union Transformation example
Vector Embedding transformation
- Vector embedding models
- Built-in vector embedding techniques
- Vector embedding output fields
Velocity transformation
- Velocity transformation input format
  - Source configuration for file sources
- Velocity template
- Testing the template
- Velocity transformation output
  - Target configuration for file targets
- Velocity transformation parsers
- Examples
  - XML conversion example
  - JSON conversion example
Verifier transformation
- Address Reference Data
- Verifier transformation configuration
- Verifier transformation field mappings
  - Understanding input and output mappings
- Verifier transformation output fields
- Advanced properties
Web Services transformation
- Create a Web Services consumer connection
- Define a business service
- Configure the Web Services transformation
- Web Services transformation example
- Configuration for multibyte hierarchical data

Transformations

Back Next

Step 2. Configure field selection criteria

When you configure a field rule, you specify the field selection criteria to determine which incoming fields apply to the field rule.

You can choose one of the following field selection criteria:

All Fields: Includes all of the incoming fields. You can rename the incoming fields in bulk when you use this option in combination with the
Includes
operator.
Named Fields: Includes or excludes the incoming fields that you specify. Use the
Named Fields
selection criteria to specify individual incoming fields to rename or to include or exclude from the incoming transformation. When you enter the field selection criteria details, you can review all of the incoming fields and select the fields to include or exclude. You can add a field that exists in the source if it does not display in the list. You can also create a parameter to represent a field to include or exclude.
Fields by Data Type: Includes or excludes incoming fields with the data types that you specify. When you enter the field selection criteria details, you can select the data types that you want to include or exclude.
Fields by Text or Pattern: Includes or excludes incoming fields by prefix, suffix, or pattern. You can use this option to select fields that you renamed earlier in the data flow. When you enter the field selection criteria details, you can select a prefix, suffix, or pattern, and define the rule to use.

When you select the prefix option or suffix option, you enter the text to use as the prefix or suffix. For example, to find all fields that start with the string, "Cust," enter
Cust
as the prefix.

When you select the pattern option, you can enter a regular expression or you can use a parameter for the pattern. The expression must use perl compatible regular expression syntax. For example, to find all fields that start with the strings "Cust" or "Addr," enter the pattern
Cust.*|Addr.*
. To find all fields that contain the string "Cust" or "CUST" anywhere in the field name, enter the pattern
.*Cust.*|.*CUST.*
. For more information about perl compatible regular expression syntax, see the help for the REG_EXTRACT function in
Function Reference
.

The following image shows the selection of the

Fields by Data Types

field selection criteria:

The following image shows the selection of the

date/time

data type for the field selection criteria details:

Field rules

Download Guide

Watch

Comments

Cloud Data Integration Homepage

0 COMMENTS

We’d like to hear from you! Log in to comment.

Daniel Sullivan - January 02, 2025

Note that the field selection criteria doesn't allow for inline modifiers (e.g. '(?i)' to make all following matches case insensitive), I believe due to web console client side validation, not due to an inherit limitation of the underlying engine. However, the Rename pattern matching does allow for that ( I think because the validation for the pattern regex is done server side?)

So, I wanted to do a long pattern rename of reserved column names for Oracle, so I made a number of separate include statements (to overcome length limitations) like this:

Field Selection Criteria:

^[a-dA-D].*

Rename Pattern:

^(?i)(ACCESS|ADD|ALL|ALTER|AND|ANY|AS|ASC|AUDIT|BETWEEN|BY|CHAR|CHECK|CLUSTER|COLUMN|COLUMN_VALUE|COMMENT|COMPRESS|CONNECT|CREATE|CURRENT|DATE|DECIMAL|DEFAULT|DELETE|DESC|DISTINCT|DROP)$/$1_whs

Informatica Documentation Team - January 02, 2025

Hi Daniel Sullivan,

Thanks for reaching out! We'll pass this query along to our development and QA teams and get back to you shortly.

Rename Saved Search

Table of Contents

Transformations

Transformations

Step 2. Configure field selection criteria

Step 2. Configure field selection criteria