tJDBCInput MapReduce properties

JDBC

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Talend Documentation Team
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6.5
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Talend Big Data Platform
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Design and Development > Third-party systems > Database components > JDBC components
Data Quality and Preparation > Third-party systems > Database components > JDBC components
Data Governance > Third-party systems > Database components > JDBC components
EnrichPlatform
Talend Studio

These properties are used to configure tJDBCInput running in the MapReduce Job framework.

The MapReduce tJDBCInput component belongs to the MapReduce family.

The component in this framework is available only if you have subscribed to one of the Talend solutions with Big Data.

Basic settings

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

 

Repository: Select the repository file where the properties are stored.

Click this icon to open a database connection wizard and store the database connection parameters you set in the component Basic settings view.

For more information about setting up and storing database connection parameters, see Talend Studio User Guide.

JDBC URL

Specify the JDBC URL of the database to be used. For example, the JDBC URL for the Amazon Redshift database is jdbc:redshift://endpoint:port/database.

Driver JAR

Complete this table to load the driver JARs needed. To do this, click the [+] button under the table to add as many rows as needed, each row for a driver JAR, then select the cell and click the [...] button at the right side of the cell to open the Select Module wizard from which you can select the driver JAR of your interest. For example, the driver jar RedshiftJDBC41-1.1.13.1013.jar for the Redshift database.

Class Name

Enter the class name for the specified driver between double quotation marks. For example, for the RedshiftJDBC41-1.1.13.1013.jar driver, the name to be entered is com.amazon.redshift.jdbc41.Driver.

Username and Password

Specify the JDBC URL of the database to be used. For example, the JDBC URL for the Amazon Redshift database is jdbc:redshift://endpoint:port/database.

To enter the password, click the [...] button next to the password field, and then in the pop-up dialog box enter the password between double quotes and click OK to save the settings.

Schema and Edit schema

A schema is a row description. It defines the number of fields (columns) to Repository. When you create a Spark Job, avoid the reserved word line when naming the fields.

 

Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.

 

Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

  • View schema: choose this option to view the schema only.

  • Change to built-in property: choose this option to change the schema to Built-in for local changes.

  • Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.

Table Name

Type in the name of the table from which you need to read data.

Die on error

Select the check box to stop the execution of the Job when an error occurs.

Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

Query type and Query

Specify the database query statement paying particularly attention to the properly sequence of the fields which must correspond to the schema definition.

If using the dynamic schema feature, the SELECT query must include the * wildcard, to retrieve all of the columns from the table selected.

Usage

Usage rule

In a Talend Map/Reduce Job, it is used as a start component and requires a transformation component as output link. The other components used along with it must be Map/Reduce components, too. They generate native Map/Reduce code that can be executed directly in Hadoop.

For further information about a Talend Map/Reduce Job, see the sections describing how to create, convert and configure a Talend Map/Reduce Job of the Talend Open Studio for Big Data Getting Started Guide .

Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs, and non Map/Reduce Jobs.

Hadoop Connection

You need to use the Hadoop Configuration tab in the Run view to define the connection to a given Hadoop distribution for the whole Job.

This connection is effective on a per-Job basis.

Limitation

We recommend using the following databases with the Map/Reduce version of this component: DB2, Informix, MSSQL, MySQL, Netezza, Oracle, Postgres, Teradata and Vertica.

It may work with other databases as well, but these may not necessarily have been tested.