# tRedshiftInput properties for Apache Spark Batch These properties are used to configure tRedshiftInput running in the Spark Batch Job framework. The Spark Batch tRedshiftInput component belongs to the Databases family. The component in this framework is available in all Talend products with Big Data and Talend Data Fabric. ## 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. | | --- | --- | | ![](https://help.qlik.com/talend/en-US/components/7.3/Resources/images/Save_Icon.png) | 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. | | 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](http://docs.aws.amazon.com/redshift/latest/mgmt/managing-clusters-console.html). | | 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, and then in the pop-up dialog box enter the password between double quotes
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](http://docs.aws.amazon.com/redshift/latest/mgmt/managing-clusters-console.html). | | 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](http://docs.aws.amazon.com/redshift/latest/dg/r_Schemas_and_tables.html). | | Additional JDBC Parameters | 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. | | 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:

| | 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 | Select the type of the source of the data to be read.

| | 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.

You can use pushdown predicate in the query to filter the data from the
database. Spark supports the following operators:



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. | ## Advanced settings | 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 | **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 | In the Spark
Configuration tab in the Run
view, define the connection to a given Spark cluster for the whole Job. In
addition, since the Job expects its dependent jar files for execution, you must
specify the directory in the file system to which these jar files are
transferred so that Spark can access these files:



This connection is effective on a per-Job basis. |