Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

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

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.

Available only for Spark V1.4. and onwards.

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.

Driver Class

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.

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.

Usage rule

This component is used with no need to be connected to other components.

The configuration in a tJDBCConfiguration
component applies only on the JDBC related components in the same Job. In other words,
the JDBC components used in a child or a parent Job that is called via tRunJob cannot reuse this configuration.

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.

Property type

Either Built-In or Repository.

Built-In: No property data stored centrally.

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

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.

Driver Class

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.

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.

Usage rule

This component is used with no need to be connected to other components.

The configuration in a tJDBCConfiguration
component applies only on the JDBC related components in the same Job. In other words,
the JDBC components used in a child or a parent Job that is called via tRunJob cannot reuse this configuration.

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.