July 30, 2023

tTeradataOutput – Docs for ESB 7.x

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tTeradataOutput

Executes the action defined on the table and/or on the data contained in the table,
based on the flow incoming from the preceding component in the job.

tTeradataOutput writes, updates, makes
changes or suppresses entries in a database.

Depending on the Talend
product you are using, this component can be used in one, some or all of the following
Job frameworks:

tTeradataOutput Standard properties

These properties are used to configure tTeradataOutput running in the Standard Job framework.

The Standard
tTeradataOutput component belongs to the Databases family.

The component in this framework is available in all Talend
products.

Note: This component is a specific version of a dynamic database
connector. The properties related to database settings vary depending on your database
type selection. For more information about dynamic database connectors, see Dynamic database components.

Basic settings

Database

Select a type of database from the list and click
Apply.

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.

Note: When a Job contains the parent Job and the child Job, if you
need to share an existing connection between the two levels, for example, to share the
connection created by the parent Job with the child Job, you have to:

  1. In the parent level, register the database connection
    to be shared in the Basic
    settings     view of the connection component which creates that very database
    connection.

  2. In the child level, use a dedicated connection
    component to read that registered database connection.

For an example about how to share a database connection
across Job levels, see

Talend Studio
 User Guide.

tTeradataOutput_1.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.

Host

Database server IP address

Database

Name of the database

Username and
Password

DB user authentication data.

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.

Table

Name of the table to be written. Note that only one table can be
written at a time.

Action on table

Note:

The Action on table list will
not be available if you select the Enable
parallel execution check box in the Advanced settings view.

On the table defined, you can perform one of the following
operations:

None: No operation is carried out.

Drop and create a table: The table
is removed and created again.

Create a table: The table does not
exist and gets created.

Create a table if not exists: The
table is created if it does not exist.

Drop a table if exists and create:
The table is removed if it already exists and created again.

Clear a table: The table content is
deleted.

Create

This is not visible by default, until you choose to create a table
from the Action on table drop-down
list. The table to be created may be:

– SET TABLE: tables which do not
allow to duplicate

– MULTI SET TABLE: tables
allowing duplicate rows.

Action on data

On the data of the table defined, you can perform:

Insert: Add new entries to the table. If
duplicates are found, job stops.

Update: Make changes to existing
entries.

Insert or update: Insert a new record. If
the record with the given reference already exists, an update would be made.

Update or insert: Update the record with the
given reference. If the record does not exist, a new record would be inserted.

Delete: Remove entries corresponding to
the input flow.

Warning:

It is necessary to specify at least one
column as a primary key on which the Update and Delete operations are based. You can do that
by clicking Edit Schema and
selecting the check box(es) next to the column(s) you want
to set as primary key(s). For an advanced use, click the
Advanced settings view
where you can simultaneously define primary keys for the
Update and Delete operations. To do that:
Select the Use field
options check box and then in the Key in update column, select the
check boxes next to the column names you want to use as a
base for the Update operation. Do the same in the Key in delete column for the
Delete operation.

Note:

The dynamic schema feature can be used in the
following modes: Insert;
Update; Insert or update; Update or insert; Delete.

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.

This
component offers the advantage of the dynamic schema feature. This allows you to
retrieve unknown columns from source files or to copy batches of columns from a source
without mapping each column individually. For further information about dynamic schemas,
see
Talend Studio

User Guide.

This
dynamic schema feature is designed for the purpose of retrieving unknown columns of a
table and is recommended to be used for this purpose only; it is not recommended for the
use of creating tables.

 

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.

When the schema to be reused has default values that are
integers or functions, ensure that these default values are not enclosed within
quotation marks. If they are, you must remove the quotation marks manually.

You can find more details about how to
verify default values in retrieved schema in Talend Help Center (https://help.talend.com).

 

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.

Die on error

This check box is selected by default. Clear the check box to skip
the row on error and complete the process for error-free rows. If
needed, you can retrieve the rows on error via a Row > Rejects link.

Advanced settings

Additional JDBC parameters

Specify additional connection properties for the DB connection you
are creating. This option is not available if you have selected the
Use an existing connection
check box in the Basic
settings.

This is intended to allow specific character set support. E.G.:
CHARSET=KANJISJIS_OS to get support of Japanese characters.

Note:

You can press Ctrl+Space to
access a list of predefined global variables.

Commit every

Enter the number of rows to be completed before committing batches
of rows together into the DB. This option ensures transaction
quality (but not rollback) and, above all, better performance at
execution.

This option is not available if you have selected the Use an existing connection check box in
the Basic settings view.

Note:

If you have selected Drop and create
table, Create
table, Create table if does
not exist or Drop table if
exists and create from the Action on table list in the Basic settings view, you need to
enter 0 in this field to
ensure the validity of the SQL statements. For more information
about the validity of the SQL statements in Teradata Database,
see teradata.

Additional Columns

This option is not offered if you create (with or without drop)
the DB table. This option allows you to call SQL functions to
perform actions on columns, which are not insert, nor update or
delete actions, or action that require particular preprocessing.

 

Name: Type in the name of the
schema column to be altered or inserted as new column

 

SQL expression: Type in the SQL
statement to be executed in order to alter or insert the relevant
column data.

 

Position: Select Before, Replace or After
following the action to be performed on the reference column.

 

Reference column: Type in a
column of reference that the tDBOutput can use to place or replace the new or
altered column.

Query band

Select this check box to use the Teradata Query Banding feature to add metadata to the query
to be processed, such as the user running the query. This can help you, for example,
identify the origin of this query.

Once selecting the check box, the Query Band parameters
table is displayed, in which you need to enter the metadata information to be added. This
information takes the form of key/value pairs, for example, DpID in the Key column and Finance in the Value
column.

This check box actually generates the SET QUERY_BAND FOR SESSION statement with the key/value
pairs declared in the Query Band parameters table. For
further information about this statement, see https://docs.teradata.com/search/all?query=End+logging+syntax.

This check box is not available when you have selected the Using an
existing connection check box. In this situation, if you need to use the
Query Band feature, set it in the Advanced settings tab of
the Teradata connection component to be used.

Use field options

Select this check box to customize a request, especially when
there is double action on data.

Debug query mode

Select this check box to display each step during processing entries
in a database.

tStatCatcher Statistics

Select this check box to collect log data at the component
level.

Use Batch

Select this check box to activate the batch mode for data processing.

Batch Size

Specify the number of records to be processed in each batch.

This field appears only when the Use batch mode
check box is selected.

Enable parallel execution

Select this check box to perform high-speed data processing, by treating
multiple data flows simultaneously. Note that this feature depends on the database or
the application ability to handle multiple inserts in parallel as well as the number of
CPU affected. In the Number of parallel executions
field, either:

  • Enter the number of parallel executions desired.
  • Press Ctrl + Space and select the
    appropriate context variable from the list. For further information, see
    Talend Studio User Guide    .

Note that when parallel execution is enabled, it is not possible to use global
variables to retrieve return values in a subjob.

  • The Action on
    table     field is not available with the
    parallelization function. Therefore, you must use a tCreateTable component if you
    want to create a table.
  • When parallel execution is enabled, it is not
    possible to use global variables to retrieve return values in a
    subjob.

Global Variables

Global Variables

NB_LINE: the number of rows processed. This is an After
variable and it returns an integer.

NB_LINE_UPDATED: the number of rows updated. This is an
After variable and it returns an integer.

NB_LINE_INSERTED: the number of rows inserted. This is an
After variable and it returns an integer.

NB_LINE_DELETED: the number of rows deleted. This is an
After variable and it returns an integer.

NB_LINE_REJECTED: the number of rows rejected. This is an
After variable and it returns an integer.

ERROR_MESSAGE: the error message generated by the
component when an error occurs. This is an After variable and it returns a string. This
variable functions only if the Die on error check box is
cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable
functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl +
Space to access the variable list and choose the variable to use from it.

For further information about variables, see
Talend Studio

User Guide.

Usage

Usage rule

This component offers the flexibility benefit of the DB query and
covers all of the SQL queries possible.

This component must be used as an output component. It allows you to carry out actions
on a table or on the data of a table in a Teradata database. It also
allows you to create a reject flow using a Row
> Rejects link to filter data in error.

Dynamic settings

Click the [+] button to add a row in the table
and fill the Code field with a context
variable to choose your database connection dynamically from multiple
connections planned in your Job. This feature is useful when you need to
access database tables having the same data structure but in different
databases, especially when you are working in an environment where you
cannot change your Job settings, for example, when your Job has to be
deployed and executed independent of Talend Studio.

The Dynamic settings table is
available only when the Use an existing
connection check box is selected in the Basic settings view. Once a dynamic parameter is
defined, the Component List box in the
Basic settings view becomes unusable.

For examples on using dynamic parameters, see Reading data from databases through context-based dynamic connections and Reading data from different MySQL databases using dynamically loaded connection parameters. For more information on Dynamic
settings and context variables, see Talend Studio
User Guide.
Limitation

Due to license incompatibility, one or more JARs required to use
this component are not provided. You can install the missing JARs for this particular
component by clicking the Install button
on the Component tab view. You can also
find out and add all missing JARs easily on the Modules tab in the
Integration
 perspective of your studio. You can find more details about how to install external modules in
Talend Help Center (https://help.talend.com).

tTeradataOutput MapReduce properties (deprecated)

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

The MapReduce
tTeradataOutput component belongs to the Databases family.

The component in this framework is available in all subscription-based Talend products with Big Data
and Talend Data Fabric.

The MapReduce framework is deprecated from Talend 7.3 onwards. Use Talend Jobs for Apache Spark to accomplish your integration tasks.

Basic settings

Property type

Either Built-in or
Repository
.

 

Built-in: No property data stored
centrally.

 

Repository: Select the repository
file in which the properties are stored. The fields that follow are
completed automatically using the data retrieved.

tTeradataOutput_1.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.

Host

Database server IP address

Database

Name of the database

Username and
Password

DB user authentication data.

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.

Table

Name of the table to be written. Note that only one table can be
written at a time.

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.

When the schema to be reused has default values that are
integers or functions, ensure that these default values are not enclosed within
quotation marks. If they are, you must remove the quotation marks manually.

You can find more details about how to
verify default values in retrieved schema in Talend Help Center (https://help.talend.com).

 

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.

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.

Advanced settings

Additional JDBC parameters

Specify additional connection properties for the DB connection you are creating.

This is intended to allow specific character set support. E.G.:
CHARSET=KANJISJIS_OS to get support of Japanese characters.

Note:

You can press Ctrl+Space to
access a list of predefined global variables.

Use Batch

Select this check box to activate the batch mode for data processing.

Batch Size

Specify the number of records to be processed in each batch.

This field appears only when the Use batch mode
check box is selected.

Usage

Usage rule

In a
Talend
 Map/Reduce Job, it is used as an end component and requires
a transformation component as input 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.

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

Due to license incompatibility, one or more JARs required to use
this component are not provided. You can install the missing JARs for this particular
component by clicking the Install button
on the Component tab view. You can also
find out and add all missing JARs easily on the Modules tab in the
Integration
 perspective of your studio. You can find more details about how to install external modules in
Talend Help Center (https://help.talend.com).

Related scenarios

No scenario is available for the Map/Reduce version of this component yet.

tTeradataOutput properties for Apache Spark Batch

These properties are used to configure tTeradataOutput running in the Spark Batch Job framework.

The Spark Batch
tTeradataOutput component belongs to the Databases family.

The component in this framework is available in all subscription-based 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.

Use an existing configuration

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

tTeradataOutput_1.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.

Host

Database server IP address

Database

Name of the database

Username and
Password

DB user authentication data.

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.

Table

Name of the table to be written. Note that only one table can be
written at a time.

Action on table

On the table defined, you can perform one of the following
operations:

None: No operation is carried out.

Drop and create a table: The table
is removed and created again.

Create a table: The table does not
exist and gets created.

Create a table if not exists: The
table is created if it does not exist.

Drop a table if exists and create:
The table is removed if it already exists and created again.

Clear a table: The table content is
deleted.

Action on data

On the data of the table defined, you can perform:

Insert: Add new entries to the table. If
duplicates are found, job stops.

Update: Make changes to existing
entries.

Insert or update: Insert a new record. If
the record with the given reference already exists, an update would be made.

Update or insert: Update the record with the
given reference. If the record does not exist, a new record would be inserted.

Delete: Remove entries corresponding to
the input flow.

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.

When the schema to be reused has default values that are
integers or functions, ensure that these default values are not enclosed within
quotation marks. If they are, you must remove the quotation marks manually.

You can find more details about how to
verify default values in retrieved schema in Talend Help Center (https://help.talend.com).

 

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.

Die on error

This check box is selected by default. Clear the check box to skip
the row on error and complete the process for error-free rows. If
needed, you can retrieve the rows on error via a Row > Rejects link.

Advanced settings

Additional JDBC parameters

Specify additional connection properties for the DB connection you
are creating. This option is not available if you have selected the
Use an existing connection
check box in the Basic
settings.

This is intended to allow specific character set support. E.G.:
CHARSET=KANJISJIS_OS to get support of Japanese characters.

Note:

You can press Ctrl+Space to
access a list of predefined global variables.

Use batch per partition

Select this check box to activate the batch mode for data processing.

Batch size

Specify the number of records to be processed in each batch.

This field appears only when the Use batch mode
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

Usage rule

This component is used as an end component and requires an input link.

This component should use a tTeradataConfiguration
component present in the same Job to connect to Oracle. You need to select the Use an existing configuration check box and then select the tTeradataConfiguration component to be used.

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:

  • Yarn mode (Yarn client or Yarn cluster):

    • When using Google Dataproc, specify a bucket in the
      Google Storage staging bucket
      field in the Spark configuration
      tab.

    • When using HDInsight, specify the blob to be used for Job
      deployment in the Windows Azure Storage
      configuration       area in the Spark
      configuration       tab.

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
      configuration       tab.
    • When using Qubole, add a
      tS3Configuration to your Job to write
      your actual business data in the S3 system with Qubole. Without
      tS3Configuration, this business data is
      written in the Qubole HDFS system and destroyed once you shut
      down your cluster.

    • When using on-premise
      distributions, use the configuration component corresponding
      to the file system your cluster is using. Typically, this
      system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the
    configuration component corresponding to the file system your cluster is
    using, such as tHDFSConfiguration or
    tS3Configuration.

    If you are using Databricks without any configuration component present
    in your Job, your business data is written directly in DBFS (Databricks
    Filesystem).

This connection is effective on a per-Job basis.

Related scenarios

For a scenario about how to use the same type of component in a Spark Batch Job, see Writing and reading data from MongoDB using a Spark Batch Job.

tTeradataOutput properties for Apache Spark Streaming

These properties are used to configure tTeradataOutput running in the Spark Streaming Job framework.

The Spark Streaming
tTeradataOutput component belongs to the Databases family.

This component is available in Talend Real Time Big Data Platform 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.

Use an existing configuration

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

tTeradataOutput_1.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.

Host

Database server IP address

Database

Name of the database

Username and
Password

DB user authentication data.

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.

Table

Name of the table to be written. Note that only one table can be
written at a time.

Action on table

On the table defined, you can perform one of the following
operations:

None: No operation is carried out.

Drop and create a table: The table
is removed and created again.

Create a table: The table does not
exist and gets created.

Create a table if not exists: The
table is created if it does not exist.

Drop a table if exists and create:
The table is removed if it already exists and created again.

Clear a table: The table content is
deleted.

Action on data

On the data of the table defined, you can perform:

Insert: Add new entries to the table. If
duplicates are found, job stops.

Update: Make changes to existing
entries.

Insert or update: Insert a new record. If
the record with the given reference already exists, an update would be made.

Update or insert: Update the record with the
given reference. If the record does not exist, a new record would be inserted.

Delete: Remove entries corresponding to
the input flow.

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.

When the schema to be reused has default values that are
integers or functions, ensure that these default values are not enclosed within
quotation marks. If they are, you must remove the quotation marks manually.

You can find more details about how to
verify default values in retrieved schema in Talend Help Center (https://help.talend.com).

 

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.

Die on error

This check box is selected by default. Clear the check box to skip
the row on error and complete the process for error-free rows. If
needed, you can retrieve the rows on error via a Row > Rejects link.

Advanced settings

Additional JDBC parameters

Specify additional connection properties for the DB connection you
are creating. This option is not available if you have selected the
Use an existing connection
check box in the Basic
settings.

This is intended to allow specific character set support. E.G.:
CHARSET=KANJISJIS_OS to get support of Japanese characters.

Note:

You can press Ctrl+Space to
access a list of predefined global variables.

Use batch per partition

Select this check box to activate the batch mode for data processing.

Batch size

Specify the number of records to be processed in each batch.

This field appears only when the Use batch mode
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

Usage rule

This component is used as an end component and requires an input link.

This component should use a tTeradataConfiguration
component present in the same Job to connect to Oracle. You need to select the Use an existing configuration check box and then select the tTeradataConfiguration component to be used.

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:

  • Yarn mode (Yarn client or Yarn cluster):

    • When using Google Dataproc, specify a bucket in the
      Google Storage staging bucket
      field in the Spark configuration
      tab.

    • When using HDInsight, specify the blob to be used for Job
      deployment in the Windows Azure Storage
      configuration       area in the Spark
      configuration       tab.

    • When using Altus, specify the S3 bucket or the Azure
      Data Lake Storage for Job deployment in the Spark
      configuration       tab.
    • When using Qubole, add a
      tS3Configuration to your Job to write
      your actual business data in the S3 system with Qubole. Without
      tS3Configuration, this business data is
      written in the Qubole HDFS system and destroyed once you shut
      down your cluster.

    • When using on-premise
      distributions, use the configuration component corresponding
      to the file system your cluster is using. Typically, this
      system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the
    configuration component corresponding to the file system your cluster is
    using, such as tHDFSConfiguration or
    tS3Configuration.

    If you are using Databricks without any configuration component present
    in your Job, your business data is written directly in DBFS (Databricks
    Filesystem).

This connection is effective on a per-Job basis.

Related scenarios

For a scenario about how to use the same type of component in a Spark Streaming Job, see
Reading and writing data in MongoDB using a Spark Streaming Job.

Document get from Talend https://help.talend.com
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