tPredict properties for Apache Spark Batch

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.

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.

Depending on the model you select to use, a corresponding read-only column is automatically added to the schema and is used to carry the result records of the prediction.

Define a storage configuration component

Select the configuration component to be used to provide the configuration information for the connection to the target file system such as HDFS.

If you leave this check box clear, the target file system is the local system.

The configuration component to be used must be present in the same Job. For example, if you have dropped a tHDFSConfiguration component in the Job, you can select it to write the result in a given HDFS system.

The Define a storage configuration component check box is displayed when you select this radio box. Select it to connect to the filesystem to be used.

Model type

Select the type of the model you want tPredict to use. This automatically adds a read-only column to the schema of tPredict to carry the result records of the prediction.

Model on filesystem

Select this radio box if the model to be used is stored on a file system. The button for browsing does not work with the Spark Local mode; if you are using the Spark Yarn or the Spark Standalone mode, ensure that you have properly configured the connection in a configuration component in the same Job, such as tHDFSConfiguration.

In the HDFS folder field that is displayed, enter the HDFS URI in which this model is stored.

The Define a storage configuration component check box is displayed when you select this radio box. Select it to connect to the filesystem to be used.

Model computed in the current Job

Select this radio box and then select the model training component that is used in the same Job to create the model to be used.

If you are using tNaiveBayesModel or tKMeansModel in the Job or subJob, clear the Save the model on file system check box in tNaiveBayesModel or tKMeansModel. For more information, see Using tPredict with other Machine Learning components.

Usage rule

This component is used as an intermediate step.

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.