tDataMasking properties for Apache Spark Batch
These properties are used to configure tDataMasking running in the Spark Batch Job framework.
The Spark Batch tDataMasking 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 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:
Information noteRemember: When you select the Dynamic data type, remember
that:
The output schema of this component contains
read-only columns:
|
|
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 change and how to change them: Input Column: Select the column from the input flow that contains the data to be masked. The supported data types are: Date, Double, Float, Integer, Long and String. These modifications are based on the function you select in the Function column.
Category: select a category of
masking functions from the list.
Function: Select the function that will hide or obfuscate the original data with substitutes. For example, you can replace digits or letters with the substitute of your choice, replace values with synonyms from an index file or nullify values. The functions you can select from the Function list depend on the data type of the input column. For example, if the column type is Long, you can use the Numeric variance function. If the column type is String, the Numeric variance function will not be available. Also, the Function list for a Date column is date-specific, it allows you to decide the type of modification you want to do on date values. Method: Select the Basic method or one FF1 algorithm (Format-Preserving Encryption (FPE)), FF1 with AES or FF1 with SHA-2: The Basic method is the default algorithm. Information noteNote: As the masking methods are stronger, it is recommended to use the FF1
algorithms rather than the Basic method.
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. Information noteNote: 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.
The FF1 with AES and FF1 with SHA-2 methods require a password to be specified in the Password or 256-bit key for FF1 methods field of the Advanced settings to generate unique masked values. The Alphabet list is only available for functions that use Format-Preserving Encryption algorithms. 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. Characters that belong to the selected alphabets are masked with characters from the same character type within the selected alphabet. When selecting the Best guess alphabet, masked values contain characters from all alphabets represented in the input values. Best guess is the default alphabet. Any unrecognized character is copied to the output as is. 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. When you set Function to
Generate from file/list, define the file path in Extra
Parameter. Set the file path as follows:
Keep format: this function is only used on Strings. Select this check box to keep the input format when using the Generate account number and keep original country, Generate credit card number and keep original bank, Bank Account Masking, Credit Card Masking, Phone Masking and SSN Masking functions or 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 Masking functions, the characters that are not numbers from the input are copied to the output as is. |
Advanced settings
FF1 settings |
Password or 256-bit key for FF1 methods: Set the password or secret key required for the FF1 with AES and FF1 with SHA-2 methods to generate unique masked values. If the password is not set, a random password is created at each Job execution. When using the FF1 with AES and FF1 with SHA-2 methods and a password, the seed from the Seed for random generator field is not used.
You can get the 256-bit key using:
Use tweaks with FF1 Encryption: Select this check box to use tweaks. A unique tweak is generated for each record and applies to all data of a record. If bijective masking is necessary, do not use this feature. For more information about tweaks, see the data masking functions. Use a column containing the tweaks: Available when Use tweaks with FF1 Encryption check box is selected. Select this check box to use an input column as the input for tweaks which must be 32 digit hexadecimal strings. Column containing the tweaks: Available when the Use a column containing the tweaks check box is selected. Select the column that contains the tweaks. Key derivation function : Select the key derivation function. Jobs created from Talend Studio 8.0 R2022-04 run using PBKDF2 with 300,000 iterations. When you import a Job prior to Talend Studio 8.0 R2022-04, you can run the Job using 300,000 iterations. The results will be different than using 65,536 iterations. |
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. This field is of Long type. The value range is [-263, 263-1].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 masking
function applies:
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.
|
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:
This connection is effective on a per-Job basis. |