These properties are used to configure tDataMasking running in the Spark Streaming Job framework.
The Spark Streaming tDataMasking component belongs to the Data Quality family.
This component is available in Talend Real Time Big Data Platform and Talend Data Fabric.
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:
Remember: 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.
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
Method: Select the Basic method or one FF1 algorithm (Format-Preserving Encrytion (FPE)), FF1 with AES or FF1 with SHA-2:
The Basic method is the default algorithm.
Note: 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.
Note: 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 for FF1 methods field of the Advanced settings to generate unique masked values.
The Method list is only available for functions that use Format-Preserving Encryption algorithms.
When using the Replace all, Replace characters between two positions, Replace n first digits and Replace n last digits with FPE methods, you can select an alphabet.
Characters that belong to the selected alphabets are masked with characters from the same character type in 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.
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.
Password for FF1 methods
Set the password 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.
|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 functionality. For more information about tweaks, see the data masking functions.
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.
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.
When you set Function to Generate from file/list, define the file path in Extra Parameter.
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.
Should null input return null
This check box is selected by
default. When selected, the component outputs
Should empty input return empty
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.
tStat Catcher Statistics
Select this check box to gather the Job processing metadata at the Job level as well as at each component level.
This component, along with the Spark Streaming component Palette it belongs to, appears only when you are creating a Spark Streaming Job.
This component is used as an intermediate step.
You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job.
This connection is effective on a per-Job basis.
For further information about a Talend Spark Streaming Job, see the sections describing how to create, convert and configure a Talend Spark Streaming Job of the Talend Big Data Getting Started Guide .
Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs.
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.