August 16, 2023

tRedshiftOutput – Docs for ESB 6.x

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tRedshiftOutput

Writes, updates, modifies or deletes the data in a database.

tRedshiftOutput executes the action
defined on the table and/or on the data of a table, according to the
input flow from the previous component.

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

tRedshiftOutput Standard properties

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

The Standard
tRedshiftOutput component belongs to the Cloud and the Databases families.

The component in this framework is generally available.

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.

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 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.

Host

Hostname or IP address of the database server.

Port

Listening port number of the database server.

Database

Database name.

Schema

Exact name of the schema.

Username and Password

Database 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.

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.

Table

Name of the table to which the data will 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 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, the operation will stop.

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.

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. The schema is either Built-In or stored remotely in the Repository.

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. Related topic: see
Talend Studio

User Guide.

 

Repository: You have already created
the schema and stored it in the Repository. You can reuse it in various projects and
Job designs. Related topic: see
Talend Studio

User Guide.

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 through a Row > Rejects link.

Advanced settings

Extend Insert

Select this check box to carry out a bulk insert of a defined set of
lines instead of inserting lines one by one. The gain in system
performance is considerable.

Number of rows per insert: enter the
number of rows to be inserted per operation. Note that the higher the
value specified, the lower performance levels shall be due to the
increase in memory demands.

Note:

This option is not compatible with the Reject link. You should therefore clear the check
box if you are using a Row >
Rejects link with this component.

Use Batch

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

Note:

This check box is available only when you have selected the
Update or the Delete option in the Action on data field.

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.

Commit every

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

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.

Use field options

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

tStat
Catcher Statistics

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

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 covers all possible
SQL database queries. It allows you to carry out actions on a table or on
the data of a table in an Amazon Redshift database. It enables you to create
a reject flow, with a Row > Rejects link filtering the data in error. For a
usage example, see Scenario: Retrieving data in error with a Reject link.

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 Scenario: Reading data from databases through context-based dynamic connections and Scenario: 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).

Related scenarios

For a related scenario, see Scenario: Handling data with Redshift.

tRedshiftOutput properties for Apache Spark Batch

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

The Spark Batch
tRedshiftOutput component belongs to the Databases family.

The component in this framework is available only if you have subscribed to one
of the
Talend
 solutions with Big Data.

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.

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 click the relevant 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, 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.

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.

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.

Table

Enter the name of the table to which the data will be written. Note that only one table
can be written at a time.

If this table does not exist, you need to select Create
from the Save mode list to allow tRedshiftOutput to create it.

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. The schema is either Built-In or stored remotely in the Repository.

 

Built-In: You create and store the
schema locally for this component only. Related topic: see
Talend Studio

User Guide.

 

Repository: You have already created
the schema and stored it in the Repository. You can reuse it in various projects and
Job designs. Related topic: see
Talend Studio

User Guide.

 

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.

Save mode

Select the actions you want tRedshiftOutput to perform on
the specified table.

  • Create: tRedshiftOutput creates the specified table and writes data in this
    table.

  • Append: tRedshiftOutput appends data to an existing table.

  • Overwrite: tRedshiftOutput overwrites the data of the specified table.

    This overwrite impacts the availability of the target table. For this reason, if
    you need to keep this table highly available, you need to select the Use staging table check box in the Advanced settings tab to make tRedshiftOutput create and write data in a staging table and upon
    the success of this write, replace the target table with the staging one. With the
    staging table enabled, in case the write fails, the target table can be quickly
    restored.

Advanced settings

Distribution style

Select the distribution style to be applied by tRedshiftOutput on the data to be written.

For further information about each of the distribution style, see Distribution styles.

Define sort key

Select this check box to sort the data to be written based on given columns of the data.

Once selecting it, you need to select the column(s) to be used as the key(s) of the sort.
For further information about the different type of sort keys, see Choosing
sort keys.

Use staging table

Select the Use staging table check box to make tRedshiftOutput create and write data in a staging table and upon
the success of this write, replace the target table with the staging one.

This feature is available only when you have selected Overwrite from the Save mode list and is
recommended when you need to keep the target table of the overwrite highly available.

Define pre-actions

Select this check box and in the field that is displayed, add a semicolon-separated(;)
list of SQL statements that are executed before tRedshiftOutput starts to write data.

For example, using the following statement, you remove all of the rows from the Movie table that meet the condition over the Movie and the Director
tables.

Define post-actions

Select this check box and in the field that is displayed, add a semicolon-separated(;)
list of SQL statements that are executed after tRedshiftOutput has successfully written data.

For example, using the following statement, you grant the Select privilege on the
Movie table to the user ychen.

Define extra copy options

Select this check box and in the field that is displayed, add a semicolon-separated(;)
list of SQL statements that are executed along with the write of the data.

tRedshiftOutput uses the Copy statement of Redshift SQL
to write data. The list of SQL statements you add here is actually appended to the Copy
statement and so only the statements that make sense at the end of this Copy command should
be used. For example, COMPUPDATE that is used to control whether compression encodings are
automatically applied during the execution of a Copy.

For further information about the extra options you can choose, see Optional parameters.

Usage

Usage rule

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

You need to use the Spark Configuration tab in
the Run view to 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: when using Google
    Dataproc, specify a bucket in the Google Storage staging
    bucket     field in the Spark
    configuration     tab; when using other distributions, use a
    tHDFSConfiguration
    component to specify the directory.

  • Standalone mode: you need to choose
    the configuration component depending on the file system you are using, such
    as tHDFSConfiguration
    or tS3Configuration.

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.

tRedshiftOutput properties for Apache Spark Streaming

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

The Spark Streaming
tRedshiftOutput component belongs to the Databases family.

The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or 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.

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 click the relevant 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, 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.

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.

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.

Table

Enter the name of the table to which the data will be written. Note that only one table
can be written at a time.

If this table does not exist, you need to select Create
from the Save mode list to allow tRedshiftOutput to create it.

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. The schema is either Built-In or stored remotely in the Repository.

 

Built-In: You create and store the
schema locally for this component only. Related topic: see
Talend Studio

User Guide.

 

Repository: You have already created
the schema and stored it in the Repository. You can reuse it in various projects and
Job designs. Related topic: see
Talend Studio

User Guide.

 

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.

Save mode

Select the actions you want tRedshiftOutput to perform on
the specified table.

  • Create: tRedshiftOutput creates the specified table and writes data in this
    table.

  • Append: tRedshiftOutput appends data to an existing table.

  • Overwrite: tRedshiftOutput overwrites the data of the specified table.

    This overwrite impacts the availability of the target table. For this reason, if
    you need to keep this table highly available, you need to select the Use staging table check box in the Advanced settings tab to make tRedshiftOutput create and write data in a staging table and upon
    the success of this write, replace the target table with the staging one. With the
    staging table enabled, in case the write fails, the target table can be quickly
    restored.

Advanced settings

Distribution style

Select the distribution style to be applied by tRedshiftOutput on the data to be written.

For further information about each of the distribution style, see Distribution styles.

Define sort key

Select this check box to sort the data to be written based on given columns of the data.

Once selecting it, you need to select the column(s) to be used as the key(s) of the sort.
For further information about the different type of sort keys, see Choosing
sort keys.

Use staging table

Select the Use staging table check box to make tRedshiftOutput create and write data in a staging table and upon
the success of this write, replace the target table with the staging one.

This feature is available only when you have selected Overwrite from the Save mode list and is
recommended when you need to keep the target table of the overwrite highly available.

Define pre-actions

Select this check box and in the field that is displayed, add a semicolon-separated(;)
list of SQL statements that are executed before tRedshiftOutput starts to write data.

For example, using the following statement, you remove all of the rows from the Movie table that meet the condition over the Movie and the Director
tables.

Define post-actions

Select this check box and in the field that is displayed, add a semicolon-separated(;)
list of SQL statements that are executed after tRedshiftOutput has successfully written data.

For example, using the following statement, you grant the Select privilege on the
Movie table to the user ychen.

Define extra copy options

Select this check box and in the field that is displayed, add a semicolon-separated(;)
list of SQL statements that are executed along with the write of the data.

tRedshiftOutput uses the Copy statement of Redshift SQL
to write data. The list of SQL statements you add here is actually appended to the Copy
statement and so only the statements that make sense at the end of this Copy command should
be used. For example, COMPUPDATE that is used to control whether compression encodings are
automatically applied during the execution of a Copy.

For further information about the extra options you can choose, see Optional parameters.

Usage

Usage rule

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

You need to use the Spark Configuration tab in
the Run view to 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: when using Google
    Dataproc, specify a bucket in the Google Storage staging
    bucket     field in the Spark
    configuration     tab; when using other distributions, use a
    tHDFSConfiguration
    component to specify the directory.

  • Standalone mode: you need to choose
    the configuration component depending on the file system you are using, such
    as tHDFSConfiguration
    or tS3Configuration.

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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