Dataphin:Configure the DM (DAMENG) input component

Prerequisites

• A DaMeng data source is created. For more information, see Create a DaMeng (DM) data source.

• The account used to configure the DaMeng input component properties must have the read-through permission on the data source. If you do not have the permission, you need to request the data source permission. For more information, see Request, renew, and return data source permissions.

Procedure

1. In the top navigation bar of the Dataphin homepage, choose Development > Data Integration.

2. In the top navigation bar of the integration page, select a project (In the Dev-Prod mode, you need to select an environment).

3. In the left-side navigation pane, click Batch Pipeline. In the Batch Pipeline list, click the offline pipeline that you want to develop to open its configuration page.

4. Click Component Library in the upper-right corner of the page to open the Component Library panel.

5. In the left-side navigation pane of the Component Library panel, select Inputs. Find the DM component in the input component list on the right and drag it to the canvas.

6. Click the icon in the DM input component card to open the DaMeng Input Configuration dialog box.

7. In the DaMeng Input Configuration dialog box, configure the parameters.

   Parameter	Description
   Step Name	The name of the DaMeng input component. Dataphin automatically generates a step name, which you can modify based on your business scenario. The name must meet the following requirements: It can contain only Chinese characters, letters, underscores (_), and digits. It cannot exceed 64 characters in length.
   Datasource	The data source dropdown list displays all DM type data sources in the current Dataphin, including those for which you have the read-through permission and those for which you do not. Click the icon to copy the current data source name. For data sources for which you do not have the read-through permission, you can click Request next to the data source to request the read-through permission. For more information, see Request, renew, and return data source permissions. If you do not have a DM (DaMeng) type data source, click Create Data Source to create one. For more information, see Create a DaMeng (DM) data source.
   Source Table Quantity	Based on your actual scenario requirements, select a single table or multiple tables with the same structure as input. Source Table Quantity includes Single Table and Multiple Tables: Single Table: Applicable to scenarios where business data from one table is synchronized to one target table. Multiple Tables: Applicable to scenarios where business data from multiple tables is synchronized to the same target table. When data from multiple tables is written to the same data table, the union algorithm is used.
   Table	Select the source table: If you selected Single Table for Source Table Quantity, you can enter a table name keyword to search or enter the exact table name and click Exact Match. After you select a table, the system automatically checks the table status. Click the icon to copy the name of the currently selected table. If you selected Multiple Tables for Source Table Quantity, perform the following operations to add tables. In the input box, enter a table expression to filter tables with the same structure. The system supports enumeration form, regular expression-like form, and a mixture of both. For example, table_[001-100];table_102. Click Exact Match. In the Confirm Matching Details dialog box, view the list of matched tables. Click OK.
   Shard Key (optional)	The system shards data based on the configured shard key field, which can be used with the concurrent configuration to implement concurrent reading. You can use a column in the source data table as the shard key. We recommend that you use the primary key or a column with an index as the shard key to ensure transmission performance. Important When you select a date-time type, the system identifies the maximum and minimum values, and performs forced sharding based on the total time range and concurrency. Even distribution is not guaranteed.
   Batch Read Count (optional)	The number of records to read at one time. When reading data from the source database, you can configure a specific batch read count (such as 1,024 records) instead of reading records one by one. This reduces the number of interactions with the data source, improves I/O efficiency, and reduces network latency.
   Input Filter (optional)	Enter the filter information for the input fields. For example, ds=${bizdate}. Input Filter is applicable to the following two scenarios: Fixed part of data. Parameter filtering.
   Output Fields	The Output Fields section displays all fields from the selected table and those that match the filter conditions. You can perform the following operations: Field Management: If you do not need to output certain fields to downstream components, you can delete these fields: Single field deletion scenario: If you need to delete a small number of fields, you can click the icon in the Operation column to delete the unnecessary fields. Batch field deletion scenario: If you need to delete many fields, you can click Field Management. In the Field Management dialog box, select multiple fields, click the left move icon to move the selected input fields to the unselected input fields, and then click OK to complete the batch deletion of fields. Batch Add: Click Batch Add to support batch configuration in JSON, TEXT format, and DDL format. Note After you complete the batch addition and click OK, the system will overwrite the configured field information. Batch configuration in JSON format, for example: // Example: [{ "index": 1, "name": "id", "type": "int(10)", "mapType": "Long", "comment": "comment1" }, { "index": 2, "name": "user_name", "type": "varchar(255)", "mapType": "String", "comment": "comment2" }] Note index indicates the column number of the specified object, name indicates the field name after import, and type indicates the field type after import. For example, "index":3,"name":"user_id","type":"String" indicates importing the 4th column from the file, with the field name as user_id and the field type as String. Batch configuration in TEXT format, for example: // Example: 1,id,int(10),Long,comment1 2,user_name,varchar(255),Long,comment2 The row delimiter is used to separate the information of each field. The default is a line feed (\n). It supports line feed (\n), semicolon (;), and period (.). The column delimiter is used to separate the field name and field type. The default is a comma (,). It supports','. The field type can be omitted, with the default being','. Batch configuration in DDL format, for example: CREATE TABLE tablename ( user_id serial, username VARCHAR(50), password VARCHAR(50), email VARCHAR (255), created_on TIMESTAMP, ); Create New Output Field: Click + Create New Output Field, and fill in Column, Type, Remarks, and select Mapping Type as prompted. After completing the configuration for the current row, click the icon to save.

8. Click OK to complete the property configuration of the DM (DaMeng) input component.