tKinesisOutput - 6.1

Talend Components Reference Guide

EnrichVersion
6.1
EnrichProdName
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
Talend Data Integration
Talend Data Management Platform
Talend Data Services Platform
Talend ESB
Talend MDM Platform
Talend Open Studio for Big Data
Talend Open Studio for Data Integration
Talend Open Studio for Data Quality
Talend Open Studio for ESB
Talend Open Studio for MDM
Talend Real-Time Big Data Platform
task
Data Governance
Data Quality and Preparation
Design and Development
EnrichPlatform
Talend Studio

Warning

The streaming version of this component is available in the Palette of the studio on the condition that you have subscribed to Talend Real-time Big Data Platform or Talend Data Fabric.

Function

tKinesisOutput receives serialized messages from its preceding component and publishes these messages to an existing Amazon Kinesis stream.

Purpose

The tKinesisOutput component acts as data producer to put data to an Amazon Kinesis stream for real-time ingestion.

tKinesisOutput properties in Spark Streaming Jobs

Warning

The streaming version of this component is available in the Palette of the studio on the condition that you have subscribed to Talend Real-time Big Data Platform or Talend Data Fabric.

Component Family

Messaging / Kinesis

 

Basic settings

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.

The schema of this component is read-only. You can click Edit schema to view the schema.

The read-only serializedValue column is used to carry the body of the message to be added to Kinesis. Note that you must use a Write component such as tWriteJSONField to define a same serializedValue column in the input schema in order to send serialized data to this read-only column.

The other columns are automatically retrieved from the schema of its preceding component. They are added as header to the message to be outputted.

 

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 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.

 

Stream name

Enter the name of the Kinesis stream you want to add data to.

 

Endpoint URL

Enter the endpoint of the Kinesis service to be used. For example, https://kinesis.us-east-1.amazonaws.com. More valid Kinesis endpoint URLs can be found at http://docs.aws.amazon.com/general/latest/gr/rande.html#ak_region.

 

Number of shard

Enter the number of partitions (shards in terms of Kinesis) to be created in the target Kinesis stream.

Advanced settings

Connection pool

In this area, you configure the connection pool used to control the number of connections that stay open simultaneously. Generally speaking, 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) allowed in the connection pool.

  • Max number of idle connections: enter the maximum number of idle connections (connections not used) allowed 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 in Spark Streaming Jobs

In a Talend Spark Streaming Job, it is used as an end component and requires an input link. The other components used along with it must be Spark Streaming components, too. They generate native Spark code that can be executed directly in a Spark cluster.

This component needs a Write component such as tWriteJSONField to define a serializedValue column in the input schema to send serialized data.

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.

Log4j

If you are using a subscription-based version of the Studio, the activity of this component can be logged using the log4j feature. For more information on this feature, see Talend Studio User Guide.

For more information on the log4j logging levels, see the Apache documentation at http://logging.apache.org/log4j/1.2/apidocs/org/apache/log4j/Level.html.

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, one and only one file system related component from the Storage family is required in the same Job so that Spark can use this component to connect to the file system to which the jar files dependent on the Job are transferred:

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. For details, see https://help.talend.com/display/KB/How+to+install+external+modules+in+the+Talend+products or the section describing how to configure the Studio in the Talend Installation Guide.

Related scenarios

No scenario is available for the Spark Streaming version of this component yet.