tRedshiftInput properties for Apache Spark Batch

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 Centralizing database metadata.

Select the Redshift driver version to be used between Driver v1 or Driver v2.

Use an existing connection

Select this check box and in the Component List drop-down list, select the desired connection component to reuse the connection details you already defined.

Host

Enter the endpoint of the database you need to connect to in Redshift.

Port

Enter the port number of the database you need to connect to in Redshift.

The related information can be found in the Cluster Database Properties area in the Web console of your Redshift.

For further information, see Managing clusters console.

Username and Password

Enter the authentication information to the Redshift database you need to connect to.

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

Database

Enter the name of the database you need to connect to in Redshift.

The related information can be found in the Cluster Database Properties area in the Web console of your Redshift.

For further information, see Managing clusters console.

Schema

Enter the name of the database schema to be used in Redshift. The default schema is called PUBLIC.

A schema in terms of Redshift is similar to a operating system directory. For further information about a Redshift schema, see Schemas.

Set JDBC properties in a string. If you select this option, enter your JDBC parameter string in the Additional JDBC Parameters field; otherwise, enter JDBC properties and property values in the Additional JDBC Parameters table.

This option is only available when you select Driver v2 from the Driver version drop-down list.

Additional JDBC Parameters (field)

Specify additional JDBC properties for the connection you are creating. The properties are separated by ampersand & and each property is a key-value pair. For example, ssl=true & sslfactory=com.amazon.redshift.ssl.NonValidatingFactory, which means the connection will be created using SSL.

This option is only available when you select Driver v1 from the Driver version drop-down list or when you select Driver v2 from the Driver version drop-down list with Use String JDBC parameters selected.

Additional JDBC Parameters (table)

Specify JDBC properties in table rows.

To specify a JDBC property, add a row in the table by clicking the plus button on the bottom of this table, enter the property name in the Key column, and then enter the property value in the Value column.

This table is available when you select Driver v2 from the Driver version drop-down list and clear Use String JDBC parameters option.

S3 configuration

Select the tS3Configuration component from which you want Spark to use the configuration details to connect to S3.

You need drop the tS3Configuration component to be used alongside tRedshiftConfiguration in the same Job so that this tS3Configuration is displayed on the S3 configuration list.

S3 temp path

Enter the location in S3 in which the data to be transferred from or to Redshift is temporarily stored.

This path is independent of the temporary path you need to set in the Basic settings tab of tS3Configuration.

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. 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.

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs.

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

Enter the name of the table from which the data will be read.

This field is only available when you select Table from the Read from drop-down list.

Read from

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.

These fields are only available when you select Query from the Read from drop-down list.

Guess Query

Click the Guess Query button to generate the query which corresponds to your table schema in the Query field.

Trim all the String/Char columns

Select this check box to remove leading whitespace and trailing whitespace from all String/Char columns.

Trim column

This table is filled automatically with the schema being used. Select the check box(es) corresponding to the column(s) to be trimmed.

Usage rule

This component is used as a start component and requires an output link.

This component should use a tRedshiftConfiguration component present in the same Job to connect to Redshift. You need to drop a tRedshiftConfiguration component alongside this component and configure the Basic settings of this component to use tRedshiftConfiguration.

This component, along with the Spark Batch component Palette it belongs to, appears only when you are creating a Spark Batch Job.

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

Spark Connection

This connection is effective on a per-Job basis.