# tPatternUnmasking properties for Apache Spark Streaming (deprecated) Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated) This content is deprecated. These properties are used to configure tPatternUnmasking running in the Spark Streaming Job framework. Information noteDeprecation: Spark Streaming is deprecated beginning with the R2026-09 release. Use Spark Structured Streaming instead. The Spark Streaming tPatternUnmasking component belongs to the Data Quality family. ## Basic settings | Properties | Description | | --- | --- | | Schema and
Edit Schema | | | Modifications | Define in the table what fields to unmask and how to
unmask them:

Use the same settings for the Field
type, Values,
Path, Range and
Date Range columns as the ones used for
masking the input data with the tPatternMasking
component.


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

Each column is processed sequentially, meaning that data
unmasking operations will be performed on the data from the first
column, the second column, and so on.

In a colum, each data field is a fixed length field,
except the last data field.

For fixed length fields, each value must contain the
same number of characters, for example: "30001,30002,30003" or "FR,EN".

In a column, the last Enumeration or Enumeration
from file data field is a variable length field.

For variable length fields, each value might not always
contain the same number of characters, for example: "30001,300023,30003" or "FR,ENG".

Field type: Select
the field type the data belongs to.



In the Values,
Path, Range and Date Range, values must be enclosed in double
quotes.

When the input data is invalid, meaning that a value
does not match the pattern defined in the component, the generated value is
null. | ## Advanced settings | Properties | Description | | --- | --- | | 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. | | FF1 settings | Password or 256-bit key for FF1 methods: To unmask data,
the FF1 with AES and FF1 with SHA-2 methods require the password or secret key
specified in Password or 256-bit key for FF1 methods
when the data was masked with the tPatternMasking component.


Use tweaks: If tweaks have been generated while masking the data,
select this check box. When selected, the Column containing
tweaks list is displayed. A tweak allows to unmask all
data of a record.


Column containing the tweaks: Available when the Use tweaks
check box is selected. Select the column that contains the tweaks. If you do
not see it, make sure you have declared in the input component the tweaks
generated by the masking component.



Key derivation function
: Select the same key derivation function as to mask
the data. By default, PBKDF2 with 300,000 iterations
is selected. | | Seed for random
generator | Set a random number if you want to generate the same sample of
substitute data in each execution of the Job. The seed is not set by default.

If you do not set the seed, the component
creates a new random seed for each Job execution. Repeating the execution with a
different seed will result in a different sample being generated. | | Encoding | Select the encoding from the list or select Custom and define it manually. If you select Custom and leave the field empty, the supported
encodings depend on the JVM that you are using. This field is compulsory for the file
encoding. | | Output the original row | Select this check box to output original data rows in addition to the
substitute data. Outputting both the original and substitute data can be useful in debug
or test processes. | | Null input returns null | This check box is selected by
default. When selected, the component outputs null when
input values are null.

When cleared, and when the input data is null, the input data
are sent to the "Invalid" output flow.

From Talend Studio
R2024-08 onwards, when Null input returns null is selected
and the input data is null, the masking function is not applied,
null is returned and the input data are sent to the main flow. | | Empty input returns an empty output | When this check box is selected, empty values are left unchanged in
the output data. Otherwise, the selected functions are applied to the input
data. | | Send invalid data to "Invalid" output
flow | This check box is selected by default.




Invalid data are any values that do not match the pattern. | ## Usage | Usage guidance | Description | | --- | --- | | **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:



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