tMatchPredict properties for Apache Spark Batch

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.

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 Sync columns to retrieve the schema from the previous component connected in the Job.

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.

The output schema of this component has read-only columns in its output links:

LABEL: used only with the Suspect duplicates output link. It holds the prediction labels.

COUNT: used only with the Exact duplicates output link. It holds the number of exact duplicates.

GROUPID: used only with the Suspect duplicates output link. It holds the group identifiers.

CONFIDENCE_SCORE: indicates the confidence score of a prediction for a pair or cluster. If you set a Clustering classes label, a confidence score is computed for each pair in the cluster. The confidence score in the output column is the lowest one.

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.

Pairing

From the Input type list, select:

paired: to use as input the suspect duplicates generated by the tMatchPairing component.

unpaired: to use as input new data set which has not been paired by tMatchPairing.

Pairing model folder: (available only with the unpaired input type) Set the path to the folder which has the model files generated by the tMatchPairing component.

The button for browsing does not work with the Spark Local mode; if you are using the other Spark Yarn modes that the Studio supports with your distribution, ensure that you have correctly configured the connection in a configuration component in the same Job, such as tHDFSConfiguration. Use the configuration component depending on the filesystem to be used.

For further information, see tMatchPairing.

Matching

Matching model location: Select from the list where to get the model file generated by the classification Job with the tMatchModel component:

- from file system: Set the path to the folder where the model file is generated by the classification component. For further information, see tMatchModel.

- from current Job: Set the name of the model file generated by the classification component. You can use this option only if the classification Job with the tMatchModel component is integrated in the Job with the tMatchPredict component.

Matching model folder: Set the path to the folder which has the model files generated by the tMatchModel component.

The button for browsing does not work with the Spark Local mode; if you are using the other Spark Yarn modes that the Studio supports with your distribution, ensure that you have correctly configured the connection in a configuration component in the same Job, such as tHDFSConfiguration. Use the configuration component depending on the filesystem to be used.

For further information, see tMatchModel.

Clustering classes

In the table, add one or more labels used on the sample suspects generated by tMatchPairing.

The component then groups suspect records which match the label(s) set in the table.

If you labeled a sample of suspect records using Talend Data Stewardship, add the answer(s) defined in the Grouping campaign to the table.

The field is case-sensitive.

Set Checkpoint Interval

Set the frequency of checkpoints. It is recommended to leave the default value (2).

Before setting a value for this parameter, activate checkpointing and set the checkpoint directory in the Spark Configuration tab of the Run view.

For further information about checkpointing, see Logging and checkpointing the activities of your Apache Spark Job.

For further information about checkpointing the activities of your Apache Spark Job, see the documentation on Talend Help Center (https://help.talend.com).

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 Batch Connection

This connection is effective on a per-Job basis.