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Embedding Data Watermarks

Updated on 2025-02-18 GMT+08:00

This section describes how to embed data watermarks. Data watermarking applies to the following scenarios:

  • Data forwarding process standardization

    Unauthorized users need to be approved when they forward data from enterprises for external usage. After the approval, the watermark technology is used to generate files that can be used outside enterprises.

  • Digital right protection

    To associate databases with their owners, embed watermarks representing ownerships in relational databases. In this way, enterprises' digital rights can be protected.

  • Quick source tracing of leaked data

    To locate security vulnerabilities, unseal the leaked data files, check whether watermarks exist based on the file integrity and watermark traces, and identify watermark information such as data source addresses, distribution units, owners, and distribution time.

Watermark Use Process

Figure 1 shows the process of using watermarks.

Figure 1 Watermark use process

Constraints

  • Only the MRS Doris and MRS Hive data sources support data watermark tasks.
  • Watermarks cannot be embedded into a primary key.
  • If a watermark is embedded in a numeric integer field, the data may be modified. Embed watermarks into a field whose value can be changed.
  • If Dataset Scope is set to Incremental for a data watermark embedding task, Timestamp or Date needs to be selected for Time Field.
  • The MRS Doris data source supports watermarks only for fields of the string type, including Varchar, Text, and String. Ensure that the table to which watermarks are to be embedded contains fields of the string type.
  • In addition to the MRS Doris data source, you need to prepare a MRS cluster that contains Hadoop, Spark, and Yarn components for running data watermarking tasks.

Prerequisites

An MRS Hive or MRS Doris connection has been created. For details, see Creating a DataArts Studio Data Connection.

Creating a Data Watermark Embedding Task

  1. On the DataArts Studio console, locate a workspace and click DataArts Security.
  2. Choose Data Watermark Embedding from the left navigation bar, and click Create in the upper part of the displayed page.

    Figure 2 Creating a data watermark embedding task

  3. In the displayed dialog box, set the parameters listed in Table 1.

    Table 1 Basic settings

    Parameter

    Description

    *Task

    Name of the watermark embedding task. The name can only contain letters, digits, underscores (_), and hyphens (-), and can contain a maximum of 64 characters.

    To facilitate the management of the watermark embedding task, you are advised to include the object into which you want to embed the watermark and the watermark ID in the name.

    Description

    A description of the task

    *Watermark ID

    Watermark ID that will be embedded by the system into data tables. The watermark ID can contain a maximum of 16 characters.

    *Error Correction Level

    The higher the level, the more bits of watermark information, and the lower bit error rate during source tracing. Note that a higher error correction level requires a larger amount of data to ensure the integrity of embedded information. The default value is 1.

    *Watermark Version

    V1: Watermarks depend on primary keys, and the embedding speed is fast. If primary keys are attacked, source tracing may fail.

    V2: Watermarks do not depend on primary keys. They are related only to embed columns. The embedding speed is slow and the robustness is enhanced.

    Figure 3 Configuring basic information

  4. Click Next to configure the source and target end parameters listed in Table 2.

    Table 2 Source and target end parameters

    Parameter

    Description

    Source Settings

    *Data Source Type

    Currently, the value can only be MRS Hive.

    *Data Connection

    Select a data connection. If no data connection is available, create one by referring to Creating a DataArts Studio Data Connection.

    *HTTP/HTTPS Port

    MRS: required for the Doris data source type. How to obtain: 1. Log in to MRS FusionInsight Manager of the DORIS cluster. 2. Choose Cluster > Service > Doris > Configuration. 3. If Kerberos authentication is enabled for the cluster, enter the value of https_port. Otherwise, enter the value of http_port.

    *Database

    Select the databases and tables into which you want to embed the watermark.

    • Click Configure to select databases and tables.
    • Click Clear to delete the selected databases and data tables.

    *Source Table

    *Watermark Embedding Bar

    Select a field type from the drop-down list as the embedding bar. For example, the value can be a number or a character.

    Note that when Watermark Version is set to V1, the primary key column cannot be selected.

    *Dataset Scope

    If Dataset Scope is set to Incremental, you can set Time Field to Timestamp or Date.

    Generally, the watermark embedding task is scheduled once if this parameter is set to All and is scheduled periodically if this parameter is set to Incremental.

    *Time Field

    If Dataset Scope is set to Incremental, you can set this parameter to Timestamp or Date.

    Target End Settings

    *Data Source Type

    Currently, the value can only be MRS Hive.

    *Data Connection

    Select a data connection. If no data connection is available, create one by referring to Creating a DataArts Studio Data Connection.

    *HTTP/HTTPS Port

    MRS: required for the Doris data source type. How to obtain: 1. Log in to MRS FusionInsight Manager of the DORIS cluster. 2. Choose Cluster > Services > Doris and click Configurations. 3. If Kerberos authentication is enabled for the cluster, enter the value of https_port. Otherwise, enter the value of http_port.

    *Database

    Select the database where the watermark table is stored from the drop-down list.

    *Target Table

    Enter a unique table name. The table is automatically created when the table name entered does not exist.

    Click Test. Otherwise, the next operation is not allowed.

    Figure 4 Configuring source and target information

  5. Click Next and configure scheduling.

    • If Dataset Scope is set to All, Repeat can be only set to Once.
    • If Dataset Scope is set to Incremental, Repeat can be set to Once or On Schedule.

    If you set Repeat to On Schedule, set the parameters listed in Table 3.

    Table 3 Parameters for periodic scheduling

    Parameter

    Description

    *Date

    Period during which the task takes effect.

    *Cycle

    The frequency at which a task is executed. The options are:

    • minutes: Select the scheduling start time and end time, and set the interval in minutes.
    • hours: Select the scheduling start time and end time, and set the interval in hours.
    • Day: Set the scheduling time everyday.
    • Week: Select a day in a week and set the specific time to start scheduling.
    • Month: Select a day in a month and set the specific time to start scheduling.

    For example, you can set Cycle to Week, Time to 15:52, and Time Range to Tuesday. In this case, the task is executed at 15:52 every Tuesday within the configured date range.

    Start now

    If you select Start now, the task is scheduled immediately.

    Figure 5 Configuring scheduling

  6. Click OK.

Related Operations

  • Editing a task: On the Data Watermark Embedding page, locate a task and click Edit in the Operation column.

    A task in the Scheduling state cannot be edited.

  • Deleting tasks: On the Data Watermark Embedding page, locate a task, click More in the Operation column, and select Delete. To delete multiple tasks at a time, select the tasks and click Delete above the task list.

    A task in the Scheduling state cannot be deleted.

    NOTE:

    The deletion operation cannot be undone. Exercise caution when performing this operation.

  • Running or scheduling a task: On the Data Watermark Embedding page, locate a task and click Run in the Operation column or click More in the Operation column and select Start.

    You can determine whether a task is scheduled once or repeatedly based on the scheduling period.

  • Viewing running instance logs: On the Data Watermark Embedding page, locate a task and click to expand instances. Then click View Log.

    If a task fails to be executed, you can locate the failure cause based on logs, rectify the fault, and try the task again. If the fault persists, contact technical support.

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