Do-while node

Node components

Double-click a do-while node to open its internal canvas, which consists of three main parts:

• Start: Marks the entry point of the loop. You cannot edit or delete this node.

• Loop body: A customizable canvas for your tasks. You can click Create Internal Node to add various types of internal nodes, such as Shell, SQL, and Python, to form the repeatable business process.

• End: Evaluates the loop condition. This node is an assignment node in which you can write ODPS SQL, Shell, or Python code. It outputs the string True or False to determine whether the loop continues.

Built-in variables

In the loop body and End node of a do-while node, you can use the following built-in variables to obtain the current loop state and input data:

Example: ${dag.input[0][1]} extracts the value "beijing" from the first row and second column.

Step 1: Configure the loop body (add a Shell node)

1. Create a do-while node in your workflow.

2. Double-click the node to enter its internal canvas. In the loop body area, click Create Internal Node, select Shell, and name it print_loop_times.

3. Right-click the node and select Open Node.

4. Enter the following command in the code editor:

   # Use the built-in variable ${dag.loopTimes} to get the current loop count
   echo "This is loop number: ${dag.loopTimes}"

5. Click the save icon to save the node.

Step 2: Define the exit condition

1. Return to the internal canvas of the do-while node, right-click the End node, and select Open Node.

2. Switch the language to Python.

3. Enter the following Python code:

   # When the loop count is less than 5, output True and continue looping
   # When the loop count reaches 5, output False and exit the loop
   if ${dag.loopTimes} < 5:
       print True
   else:
       print False

4. Save the End node.

Step 3: Deploy, run, and verify

1. Return to the main workflow canvas and click Deploy on the toolbar to deploy the entire workflow.

2. Go to Operation Center and locate the do-while node.

3. Right-click the node and choose Backfill Data > Current Node to start a test run.

4. After the instance runs successfully, right-click the node again and select View Internal Nodes.

5. View the five loop iterations. Expand any iteration (for example, the 5th), right-click the print_loop_times instance inside, and select View Runtime Log. You should see the following output:

   This is loop number: 5

Step 1: Configure the upstream assignment node

1. Create an assignment node (for example, named assign_sql_data) and set it as the upstream of the do-while node.

2. Use ODPS SQL to query data in the node:

   SELECT 'user_A', 'beijing'
   UNION ALL
   SELECT 'user_B', 'shanghai';

3. Save the node. Its outputs parameter will output a two-dimensional array containing two rows of data.

Step 2: Configure the do-while node to consume data

1. In the Schedule Settings panel on the right side of the do-while node, find Input Parameters of This Node.

2. Click Add and configure the following parameter:

   • Parameter Name: input (customizable)

   • Value Source: Select assign_sql_data.outputs

3. In the loop body of the do-while node, create a Shell node and enter the following script to process the current row:

   # Get the data row being processed in the current loop iteration
   echo "Processing data row: ${dag.input[${dag.offset}]}"

4. Open the End node and use Python to define the exit condition:

   # If the number of times executed is less than the total number of data rows, continue looping
   if ${dag.loopTimes} < ${dag.input.length}:
       print True
   else:
       print False

5. Deploy the workflow, and in Operation Center, start the backfill from the assign_sql_data node to ensure data flows correctly into the loop.