Access
Key

Enter the access key ID that uniquely identifies an AWS
Account. For further information about how to get your Access Key and Secret Key,
see Getting Your AWS Access
Keys.

Secret
Key

Enter the secret access key, constituting the security
credentials in combination with the access Key.

To enter the secret key, click the […] button next to
the secret key field, and then in the pop-up dialog box enter the password between double
quotes and click OK to save the settings.

Inherit credentials from AWS role

Select this check box to leverage the instance profile
credentials. These credentials can be used on Amazon EC2 instances, and are delivered
through the Amazon EC2 metadata service. To use this option, your Job must be running
within Amazon EC2 or other services that can leverage IAM Roles for access to resources.
For more information, see Using an IAM Role to Grant Permissions to
Applications Running on Amazon EC2 Instances.

Assume role

If you temporarily need some access permissions associated
to an AWS IAM role that is not granted to your user account, select this check box to
assume that role. Then specify the values for the following parameters to create a new
assumed role session.

Use End Point

Select this check box and in the Server Url field
displayed, specify the Web service URL of the DynamoDB database service.

Region

Specify the AWS region by selecting a region name from the
list or entering a region between double quotation marks (e.g. “us-east-1”) in the list. For more information about the AWS
Region, see Regions and Endpoints.

Action on table

Select an operation to be performed on the table defined.

• Default: No operation is carried out.

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

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

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

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

Action on data

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

• Insert: Insert new items from
  the input flow.

• Update: Update existing items
  according to the input flow.

• Delete: Remove existing items
  according 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.

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.

If a column stores JSON documents, select JSON from the DB
Type drop-down list.

Table Name

Specify the name of table to be written.

Partition Key

Specify the partition key of the specified table.

Sort Key

Specify the sorted key of the specified table.

STS Endpoint

Select this check box and in the field displayed, specify the
AWS Security Token Service endpoint, for example, sts.amazonaws.com, where session credentials are retrieved from.

This check box is available only when the Assume role check box is selected.

Read Capacity Unit

Specify the number of read capacity units. For more information, see
Amazon DynamoDB Provisioned Throughput.

Write Capacity Unit

Specify the number of write capacity units. For more information, see
Amazon DynamoDB Provisioned Throughput.

tStatCatcher Statistics

Select this check box to gather the Job processing metadata at the Job level
as well as at each component level.

Global Variables

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

QUERY: the query statement being processed. This is a Flow
variable and it returns a string.

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 rule

This component is usually used as an end component of a Job or
subJob and it always needs an input link.

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.

Access
Key

Enter the access key ID that uniquely identifies an AWS
Account. For further information about how to get your Access Key and Secret Key,
see Getting Your AWS Access
Keys.

Secret
Key

Enter the secret access key, constituting the security
credentials in combination with the access Key.

To enter the secret key, click the […] button next to
the secret key field, and then in the pop-up dialog box enter the password between double
quotes and click OK to save the settings.

Use End Point

Select this check box and in the Server Url field
displayed, specify the Web service URL of the DynamoDB database service.

Region

Specify the AWS region by selecting a region name from the
list or entering a region between double quotation marks (e.g. “us-east-1”) in the list. For more information about the AWS
Region, see Regions and Endpoints.

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

Specify the name of the table in which you need to write data. This table must already
exist.

Die on error

Select the check box to stop the execution of the Job when an error
occurs.

Throughput write percent

Enter, without using quotation marks, the percentage (expressed in decimal) to be used of
the write capacity pre-defined in Amazon. For further information about this write capacity,
see Provision throughput for write.

Advanced properties

Add properties to define extra operations you need tDynamoDBOutput to perform when writing data.

This table is present for future evolution of the component and using it requires the
high-level knowledge of DynamoDB development. Currently, there are no interesting user
configurable properties.

Usage rule

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

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

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.

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.

Access
Key

Enter the access key ID that uniquely identifies an AWS
Account. For further information about how to get your Access Key and Secret Key,
see Getting Your AWS Access
Keys.

Secret
Key

Enter the secret access key, constituting the security
credentials in combination with the access Key.

To enter the secret key, click the […] button next to
the secret key field, and then in the pop-up dialog box enter the password between double
quotes and click OK to save the settings.

Use End Point

Select this check box and in the Server Url field
displayed, specify the Web service URL of the DynamoDB database service.

Region

Specify the AWS region by selecting a region name from the
list or entering a region between double quotation marks (e.g. “us-east-1”) in the list. For more information about the AWS
Region, see Regions and Endpoints.

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

Specify the name of the table in which you need to write data. This table must already
exist.

Die on error

Select the check box to stop the execution of the Job when an error
occurs.

Throughput write percent

Enter, without using quotation marks, the percentage (expressed in decimal) to be used of
the write capacity pre-defined in Amazon. For further information about this write capacity,
see Provision throughput for write.

Advanced properties

Add properties to define extra operations you need tDynamoDBOutput to perform when writing data.

This table is present for future evolution of the component and using it requires the
high-level knowledge of DynamoDB development. Currently, there are no interesting user
configurable properties.

Usage rule

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

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

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.