# tDataUnmasking properties for Apache Spark Structured Streaming [Preview](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/Introduction/feature-preview-program-overview.htm) These properties are used to configure tDataUnmasking running in the Spark Structured Streaming Job framework. The Spark Structured Streaming tDataUnmasking component belongs to the Data Quality family. This component is supported on Local Spark 3.5.x and Databricks/EMR with Spark 3.x. Information noteNote: This component does not support dynamic schema. This component is available in Talend Real-Time Big Data Platform and Talend Data Fabric. ## Basic settings | Properties | Description | | --- | --- | | 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 contains one read-only column, ORIGINAL_MARK. This column identifies by true or false if the record is an original record or a substitute record respectively.
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.

| | Modifications | Define in the table what fields to unmask and how to
unmask them:

Input Column:
Select the column from the input flow that contains the data to be
unmasked.

You can unmask all data masked with tDataMasking using the FF1 with AES or
FF1 with SHA-2 method combined with a user-defined password.

These modifications are based on the function you select
in the Function column.

Category: select
a category of unmasking functions from the list.

Function:
Select the function that will unmask data.

The functions you can select from the Function list
depend on the data type of the input column.

Method: From
this list, select the Format-Preserving Encryption (FPE) algorithm that
was used to mask data, FF1 with
AES or FF1 with
SHA-2:

The FF1 with AES
method is based on the Advanced Encryption Standard in CBC mode. The
FF1 with SHA-2 method
depends on the secure hash function HMAC-256.

Java 8u161 is the minimum required version to use the
FF1 with AES method. To be
able to use this FPE method with Java versions earlier than 8u161,
download the Java Cryptography Extension (JCE) unlimited strength
jurisdiction policy files from Oracle website.

To unmask data, the FF1 with AES and
FF1 with SHA-2 methods require the password specified
in Password or 256-bit key for FF1 methods when the data
was masked with the tDataMasking component.

When using the Character
handling functions, such as Replace all,
Replace characters between two positions,
Replace all digits with FPE methods, you must select
an alphabet.

From the Alphabet list, select the alphabet used
to mask data with the tDataMasking component.

Extra Parameter: This field is used
by some of the functions, it will be disabled when not applicable. When applicable,
enter a number or a letter to decide the behavior of the function you have
selected.

Keep
format: this function is only used on Strings. Select this check box to
keep the input format when using the Bank Account
Unmasking, Credit Card
Unmasking, Phone Unmasking and
SSN Unmasking categories. That is to say, if
there are spaces, dots ('.'), hyphens ('-') or slashes ('/') in the input, those
characters are kept in the output. If you select this check box when using Phone Unmasking functions, the characters that are not
numbers from the input are copied to the output as is. | ## Usage | Usage guidance | Description | | --- | --- | | **Usage rule** | This component is used as an intermediate step.

This component, along with the Spark Structured Streaming component Palette it belongs to,
appears only when you are creating a Spark Structured Streaming Job. | | Spark Connection | You need to use the Structured Streaming Configuration
tab in the Run view to define the connection to a Spark cluster for
the whole Job.

This connection is effective on a per-Job basis. |