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    Dataphin:Configure the Microsoft SQL Server Input Component

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    Dataphin:Configure the Microsoft SQL Server Input Component

    Last Updated:Jun 08, 2026

    The Microsoft SQL Server input component reads data from a SQL Server data source. To sync data to another destination, configure this input component first, then set up the destination.

    Prerequisites

    Procedure

    1. On the Dataphin homepage, click Develop > Data Integration.

    2. On the Integration page, select a Project. In Dev-Prod mode, also select an environment.

    3. In the left navigation pane, click Batch Pipeline, then click the target offline pipeline from the Batch Pipeline list.

    4. In the upper-right corner, click Component Library to open the Component Library panel.

    5. In the Component Library panel, click Input, then drag the Microsoft SQL Server component onto the canvas.

    6. Click the image icon on the component card to open the Microsoft SQL Server Input Configuration dialog box.

    7. In the Microsoft SQL Server Input Configuration dialog box, configure the following parameters.

      Parameter

      Description

      Step Name

      Auto-generated. You can customize it. Naming rules:

      • Only Chinese characters, letters, underscores (_), and digits are allowed.

      • Maximum length: 64 characters.

      Datasource

      All SQL Server data sources, regardless of permission level. Click the image icon to copy the name.

      Time Zone

      Read-only. Dataphin processes time-formatted data using the time zone of the selected data source.

      Note

      For tasks created before V5.1.2, choose between Data Source Default Configuration and Channel Configuration Time Zone (default: Channel Configuration Time Zone).

      • Data Source Default Configuration: Uses the data source's default time zone.

      • Channel Configuration Time Zone: Uses the time zone from Properties > Channel Configuration.

      Schema (Optional)

      Schema of the source table. Supports cross-schema selection. Defaults to the data source's configured schema.

      Source Table Count

      Options: Single Table or Multiple Tables.

      • Single Table: Sync from one source table to one destination table.

      • Multiple Tables: Sync from multiple source tables to one destination table using the union algorithm.

      Table Matching Method

      Choose Generic Rule or Database Regex.

      Note

      Available only when Source Table Count is set to Multiple Tables.

      Table

      Select the source table:

      • Single Table: Search by keyword or enter the exact name and click Exact Search. Dataphin validates the table after selection. Click the image icon to copy the table name.

      • Multiple Tables: Enter an expression based on the selected table matching method.

        • Generic Rule: Filter tables by enumeration, range patterns, or combinations. Example: table_[001-100];table_102;.

        • Database Regex: Enter a regular expression supported by your database. Dataphin dynamically matches tables at runtime based on this regex.

        Click Exact Search to preview matched tables in the Confirm Match Details dialog box.

      Shard Key (Optional)

      Column used to partition data for concurrent reads. A primary key or indexed column performs best.

      Important

      For date-time columns, Dataphin splits by the full time range and concurrency setting. This does not guarantee even distribution.

      Batch Read Size (Optional)

      Records per batch (for example, 1024). Larger values reduce network round-trips.

      Input Filter (Optional)

      Filter condition for input data, for example: ds=${bizdate}. Input Filter use cases:

      • A fixed subset of data.

      • Parameter-based filtering.

      Hint (Optional)

      • Overrides the query optimizer's default execution plan for table or view access.

      • Place hints after the table name in the FROM clause, inside parentheses. Separate multiple hints with commas. Example:

        SELECT * FROM MyTable WITH (INDEX(IX_MyIndex), NOLOCK)

      Output Fields

      All fields from the selected table after filter conditions are applied. Available actions:

      • Field Management: Remove unneeded fields:

        • Remove individual fields: Click the sgaga icon in the Actions column.

        • Batch removal: Click Field Management. In the Field Management dialog box, select fields and click the image left-shift icon to move them to the unselected list, then click OK.

          image..png

      • Batch Add: Click Batch Add to add fields in JSON, TEXT, or DDL format.

        Note

        Batch-added fields overwrite existing field configurations.

        • JSON format example:

          // Example:
[
    {
        "index": 1,
        "name": "Id",
        "type": "int(10)",
        "mapType": "Long",
        "comment": ""
    },
    {
        "index": 2,
        "name": "Data",
        "type": "nvarchar(100)",
        "mapType": "String",
        "comment": ""
    }
]
          Note

          index = column number, name = field name, type = field type. For example, "index":3,"name":"user_id","type":"String" imports the fourth column as user_id with type String.

        • TEXT format example:

          // Example:
1,Id,int(10),Long,
2,Data,nvarchar(100),String,
3,RowVersion,timestamp,Bytes,

          • Row delimiter. Default: line feed (\n). Also supports semicolons (;) or periods (.).

          • Column delimiter: separates field names and types. Default: comma (,). Supported: ','. Field types are optional and default to','.

        • DDL format example:

          CREATE TABLE tablename (
	user_id serial,
	username VARCHAR(50),
	password VARCHAR(50),
	email VARCHAR (255),
	created_on TIMESTAMP,
);

      • Create a new output field: Click + Create Output Field. Set Column, Type, Comment, and Mapping Type, then click the image icon to save.

    8. Click OK.