tMQTTOutput
Acts as publisher to a MQTT topic to stream messages to this topic in real
time.
tMQTTOutput receives
messages constructed in its preceding component and published these messages to a given
MQTT topic.
tMQTTOutput properties for Apache Spark Streaming
These properties are used to configure tMQTTOutput running in the Spark Streaming Job framework.
The Spark Streaming
tMQTTOutput component belongs to the Messaging family.
The streaming version of this component is available in Talend Real Time Big Data Platform and in
Talend Data Fabric.
Basic settings
Broker URL |
Enter the location of the MQTT broker to be used to route the messages to be published to |
Topic |
Enter the name of the topic you want tMQTTOutput to |
Schema and Edit |
A schema is a row description. It defines the number of fields The schema of this component is read-only. You can click This read-only payload column is used by tMQTTOutput to write the body of a MQTT message. Note that you must The other columns are added as header to the message to be outputted. |
QoS |
Enter, without quotation marks around, the numeric level of QoS (Quality of Service) to be This quality level indicates how responsive you want MQTT to be to the message delivery request:
For further explanation about the different levels of QoS, see http://www-01.ibm.com/support/knowledgecenter/SSFKSJ_8.0.0/com.ibm.mq.dev.doc/q029090_.htm. |
Advanced settings
Encoding |
Select the encoding from the list or select Custom and define it manually. This encoding is used by tMQTTOutput to encode the |
Connection pool |
In this area, you configure, for each Spark executor, the connection pool used to control
|
Evict connections |
Select this check box to define criteria to destroy connections in the connection pool. The
|
Usage
Usage rule |
This component is used as a start component and requires an output link. This component, along with the Spark Streaming component Palette it belongs to, appears Note that in this documentation, unless otherwise explicitly stated, a scenario presents |
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:
This connection is effective on a per-Job basis. |
Limitation |
Due to license incompatibility, one or more JARs required to use |
Related scenarios
No scenario is available for the Spark Streaming version of this component
yet.