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Oracle Java CAPS Data Integrator User's Guide     Java CAPS Documentation
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Document Information

Designing Data Integrator Projects

About Data Integrator

Extracting, Transforming, Loading: ETL

Oracle Java CAPS Data Integrator Overview

Extracting, Transforming, and Loading: ETL

Oracle Java CAPS Data Integrator Methodology

Oracle Java CAPS Data Integrator Features

Oracle Java CAPS Data Integrator Architecture

Oracle Java CAPS Data Integrator Design-Time Components

Data Integrator Editor

Oracle Java CAPS Data Integrator Project System

Data Integrator Service Engine

ETL Engine

ETL Service Engine

Data Integrator Monitor

Data Integrator Recovery

Creating Oracle Java CAPS Data Integrator Projects

Connecting to Source and Target Databases

Connecting to a JDBC-Compliant Database

Creating and Connecting to Data Mashup Services

Virtual Database Table Metadata Options

Virtual Database Column Properties

Creating a New Data Integrator Project

To Create a New Project

Creating an ETL Collaboration Using the Wizard

Creating a Basic ETL Collaboration

To Create a Basic ETL Collaboration

Creating an Advanced ETL Collaboration

To Create an Advanced ETL Collaboration

Creating an ETL Collaboration for a Master Index Staging Database

To Create an ETL Collaboration for a Master Index Staging Database

Creating a Bulk Loader ETL Collaboration

To Create a Bulk Loader ETL Collaboration

ETL Collaboration Overview

Execution Strategies

Direct/Simple Execution Strategy

One Pass Execution Strategy

Staging Execution Strategy

Pipeline Execution Strategy

Whitespace Considerations

Explicit and Implicit Joins

Runtime Properties

Data Validation Conditions

About the ETL Collaboration Editor

Configuring ETL Collaborations

Joining Source Tables

To Join Source Tables

To Join Source Tables During Mapping

Modifying an Existing Join

To Join Source Tables

Defining Extraction Conditions and Validations

To Define Extraction Conditions and Validation.

Adding Tables to an Existing Collaboration

To Add Tables to a Collaboration

Forcing Execution Strategies for Collaborations

To Force Execution Strategies for Collaborations

Changing the Database URL for Design Time

To Change the Database URL for Design Time

Configuring Source Table Properties

To Configure Source Table Properties

Configuring Target Table Properties

To Configure Target Table Properties

Using Pre-Created Temporary Staging Tables

Using Temporary Staging Tables

Viewing Table or Join Data

To View Table or Join Data

Viewing the SQL Code

To View SQL Code

Viewing Runtime Output Arguments

To View Runtime Output Arguments

Fine-Tuning the ETL Process

Filtering Source Data Using Runtime Inputs

To Filter Source Data Using Runtime Inputs

Setting the Batch Size for Joined Tables

To Set the Batch Size for Joined Tables

Using Table Aliases with Multiple Source Table Views

Grouping Input Data

To Group Input Data

Viewing and Modifying Table Data

To View and Modify Table Data

Grouping Input Data

Oracle Java CAPS Data Integrator supports extracting aggregated data, applying special transformations, and loading them to a target table. Specific transformations are supported for aggregated values such as Minimum, Maximum, Count, Sum, and Average. You can aggregate column(s) based on a selection specified using the Group By Expression option. This option can only be used with Insert/Update statements.

To Group Input Data

  1. Open the collaboration you want to edit.
  2. In the ETL Collaboration Editor, right-click the target table and click Properties.

    The Properties panel appears.

  3. Click the ellipsis button next to the Group By Expression property.

    The Group By Expression dialog box appears.


    Note - The Group By Expression option does not affect Upsert or Delete statements.

    image:Figure shows the Group By Expression window.
  4. Select a column to add to the group by expression, and then click Add Column/Expression.
  5. To add a HAVING clause, click Having.

    The Having Condition window appears.


    image:Figure shows the Having Condition window.
  6. Define the expression that a column must include to be grouped and click OK.
  7. Click OK on the Group By Expression dialog box.