tVerifyEmail properties for Apache Spark Batch - 7.0

Email validation

author
Talend Documentation Team
EnrichVersion
7.0
EnrichProdName
Talend Big Data Platform
Talend Data Fabric
Talend Data Management Platform
Talend Data Services Platform
Talend MDM Platform
Talend Real-Time Big Data Platform
task
Data Governance > Third-party systems > Data Quality components > Validation components > Email validation components
Data Quality and Preparation > Third-party systems > Data Quality components > Validation components > Email validation components
Design and Development > Third-party systems > Data Quality components > Validation components > Email validation components
EnrichPlatform
Talend Studio

These properties are used to configure tVerifyEmail running in the Spark Batch Job framework.

The Spark Batch tVerifyEmail component belongs to the Data Quality family.

The component in this framework is available in all Talend Platform products with Big Data and in Talend Data Fabric.

Basic settings

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.

 

Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.

Edit Schema

Click Edit schema to make changes to the schema. Note that if you make changes, the schema automatically becomes built-in.

The output schema of tVerifyEmail has different read-only columns depending on the options you select in the component Basic settings view. Read-only output columns include:

VerificationLevel: provides you with the verification status of the processed email addresses as the following:

-VALID: means that the email address comply with the defined rule.

-INVALID: means that the email address does not comply with the defined rule.

-CORRECTED: means that the input email does not comply with the defined rule and has been corrected by using the content of the selected columns. This column is available only when you select the Use column content option in the LOCAL Part Options section.

-VERIFIED: means that the email address does exist at the domain. This column is available only when you select the Check with mail server callback option.

-REJECTED: means that the email address does not exist at the domain. This column is available only when you select the Check with mail server callback option.

Suggested_Email: provides you with a suggested content for the email part before the @ sign. The email string is built up from the columns you select from the Use column content view.

Column to validate

Select from the list the column you want to validate with tVerifyEmail.

Check the entire email with regular expression

Select this check box if you want to match the complete email address against a specific regular expression.

Complete regular expression: enter the regular expression against which you want to match email addresses.

This match is done as a first step to optimize the matching process and exclude addresses that have problems before going any further to match the local and domain parts of email addresses.

LOCAL Part Options

Fields in this section will vary according to what option you select. "LOCAL part" in an email address refers to the string before the @ sign.

-Use regular expression: enter in the Pattern field the expression against which you want to check the local part of the email address.

-Use simplified pattern: enter in the Pattern field the simplified pattern against which you want to check the local part of the email address. Select the Show syntax of simplified pattern option to display the syntax to use for simplified patterns. For more information about the syntax, see Simplified pattern syntax for tVerifyEmail.

-Use column content: use the fields in this view to decide the content against which you want to check the local part of the email. If the local part does not match what you have defined, it will be rewritten by using the content of the fields.

-Enable case-sensitive pattern matching: select this check box to enable a case sensitive pattern matching of the local part of email addresses. You can use case sensitive pattern matching with each of the above options.

DOMAIN Part Options

Fields in this view will vary according to what option you select.

-Check the Top-level Domains and the following ones: select this check box to verify the part of the email address which follows the last dot. You can use the Additional Top-level Domains table to add additional top-level domains against which you want to validate email addresses.

-Check domains with a black list: select this option to verify the domains you define in the Domain list table as black listed.

-Check domains with a white list: select this option to verify the domains you define in the Domain List table as white listed.

Global Variables

Global Variables

ERROR_MESSAGE: the error message generated by the component when an error occurs. This is an After variable and it returns a string. This variable functions only if the Die on error check box is cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl + Space to access the variable list and choose the variable to use from it.

For further information about variables, see Talend Studio User Guide.

Usage

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

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:
  • Yarn mode (Yarn client or Yarn cluster):
    • When using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab.

    • When using HDInsight, specify the blob to be used for Job deployment in the Windows Azure Storage configuration area in the Spark configuration tab.

    • When using Altus, specify the S3 bucket or the Azure Data Lake store (technical preview) for Job deployment in the Spark configuration tab.
    • When using other distributions, use the configuration component corresponding to the file system your cluster is using. Typically, this system is HDFS and so use tHDFSConfiguration.

  • Standalone mode: use the configuration component corresponding to the file system your cluster is using, such as tHDFSConfiguration or tS3Configuration.

This connection is effective on a per-Job basis.