tTachyonConfiguration
Defines a connection to Tachyon storage system and enables the reuse of the
configuration in the same Job.
You define a connection to Tachyon in tTachyonConfiguration and configure the file system
related components to reused this connection. At runtime, the Spark
cluster to be used reads this configuration to connect to
Tachyon.
Depending on the Talend solution you
are using, this component can be used in one, some or all of the following Job
frameworks:
-
Spark Batch: see tTachyonConfiguration properties for Apache Spark Batch.
The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data. -
Spark Streaming: see tTachyonConfiguration properties for Apache Spark Streaming.
The component in this framework is available only if you have subscribed to Talend Real-time Big Data Platform or Talend Data
Fabric.
tTachyonConfiguration properties for Apache Spark Batch
These properties are used to configure tTachyonConfiguration running in the Spark Batch Job framework.
The Spark Batch
tTachyonConfiguration component belongs to the Storage family.
The component in this framework is available only if you have subscribed to one
of the
Talend
solutions with Big Data.
Basic settings
|
Tachyon master URI |
Enter the address of the master server of the Tachyon cluster to be used. This information can be found in the conf/tachyon-env.sh file of your Tachyon system. For details about the version compatibility between Tachyon and Spark, see Tachyon |
|
UnderFS username |
Enter the credential required by the file system (underlayer storage system in terms of Tachyon) used by your Tachyon cluster. The default file system is HDFS. This information can be found in the conf/tachyon-env.sh file of your Tachyon system. |
Usage
|
Usage rule |
This component is used with no need to be connected to other components. You need to drop tTachyonConfiguration along with the file system related Subjob to be run in the This component, along with the Spark Batch component Palette it belongs to, appears only Note that in this documentation, unless otherwise |
|
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:
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.
tTachyonConfiguration properties for Apache Spark Streaming
These properties are used to configure tTachyonConfiguration running in the Spark Streaming Job framework.
The Spark Streaming
tTachyonConfiguration component belongs to the Storage 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
|
Tachyon master URI |
Enter the address of the master server of the Tachyon cluster to be used. This information can be found in the conf/tachyon-env.sh file of your Tachyon system. For details about the version compatibility between Tachyon and Spark, see Tachyon |
|
UnderFS username |
Enter the credential required by the file system (underlayer storage system in terms of Tachyon) used by your Tachyon cluster. The default file system is HDFS. This information can be found in the conf/tachyon-env.sh file of your Tachyon system. |
Usage
|
Usage rule |
This component is used with no need to be connected to other components. You need to drop tTachyonConfiguration along with the file system related Subjob to be run in the 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 |
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:
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.