Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

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

Use an existing
connection

Select this check box and in the Component List click the relevant connection component to
reuse the connection details you already defined.

JDBC URL

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 Module dialog box from which you can select the driver JAR
to be used. For example, the driver jar RedshiftJDBC41-1.1.13.1013.jar for the Redshift database.

For more information, see Importing a database driver.

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

Enter the authentication information to the 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.

Available only for Spark V1.4. and onwards.

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

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

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.

The result of the query must contain only records that match join key you need to use in
tMap. In other words, you must use the schema of the
main flow to tMap to construct the SQL statement here in
order to load only the matched records into the lookup flow.

This approach ensures that no redundant records are loaded into memory and outputted to
the component that follows.

Guess Query

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

Guess schema

Click the Guess schema button to retrieve the table
schema.

Additional JDBC
parameters

Specify additional connection properties for the database connection you are
creating. The properties are separated by semicolon and each property is a key-value
pair, for example, encryption=1;clientname=Talend.

This field is not available if the Use an existing
connection check box is selected.

Connection pool

In this area, you configure, for each Spark executor, the connection pool used to control
the number of connections that stay open simultaneously. The default values given to the
following connection pool parameters are good enough for most use cases.

• Max total number of connections: enter the maximum number
  of connections (idle or active) that are allowed to stay open simultaneously.

  The default number is 8. If you enter -1, you allow unlimited number of open connections at the same
  time.

• Max waiting time (ms): enter the maximum amount of time
  at the end of which the response to a demand for using a connection should be returned by
  the connection pool. By default, it is -1, that is to say, infinite.

• Min number of idle connections: enter the minimum number
  of idle connections (connections not used) maintained in the connection pool.

• Max number of idle connections: enter the maximum number
  of idle connections (connections not used) maintained in the connection pool.

Evict connections

Select this check box to define criteria to destroy connections in the connection pool. The
following fields are displayed once you have selected it.

• Time between two eviction runs: enter the time interval
  (in milliseconds) at the end of which the component checks the status of the connections and
  destroys the idle ones.

• Min idle time for a connection to be eligible to
  eviction: enter the time interval (in milliseconds) at the end of which the idle
  connections are destroyed.

• Soft min idle time for a connection to be eligible to
  eviction: this parameter works the same way as Min idle
  time for a connection to be eligible to eviction but it keeps the minimum number
  of idle connections, the number you define in the Min number of idle
  connections field.

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 tJDBCConfiguration component present in the same Job to
connect to a database. You need to drop a tJDBCConfiguration component alongside this component and configure the
Basic settings of this component
to use tJDBCConfiguration.

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