Overview

Partially update a job's input configuration. This endpoint is particularly useful for adding new columns to an existing JDBC job without replacing the entire configuration.

Job ID Format

The jobId follows the format: {pipeline_id}_{job_index}

Example: 1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0 (first job in pipeline 1b33ad2f_33d3_4837_9eeb_83c82c8b909d)

Column Selection Behavior

When updating column_include_list, this endpoint uses union logic:

New columns are added to the existing list
Existing columns are preserved
Duplicate columns are automatically handled (not added twice)

This makes it safe to call multiple times without losing previously selected columns.

Request Body

The request body is a JSON object with the fields you want to update. Only the specified fields will be modified.

Field	Type	Description
`column_include_list`	array	List of column names to add to the job (union with existing)
`load_type`	string	Change load type: `full_load`, `incremental`, `incremental_with_qualify`
`incremental_column_name`	string	Column for incremental tracking
`incremental_column_type`	string	Data type of incremental column
`primary_keys`	array	Primary key columns (for `incremental_with_qualify`)
`memory_allocation_mb`	integer	Memory allocation in MB
Any other input field	varies	Other job input configuration fields

Examples

Add New Columns to JDBC Job

Add columns to an existing job's column selection:

PATCH /platform/jobs/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0/input

{
  "column_include_list": ["new_column_1", "new_column_2", "new_column_3"]
}

Response (200 OK):

{
  "status": true,
  "detail": "Successfully updated input fields for job_id 1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0",
  "updated_fields": ["column_include_list"]
}

If the job previously had columns ["id", "name", "email"], after this call it will have: ["id", "name", "email", "new_column_1", "new_column_2", "new_column_3"]

Add Columns and Update Memory

PATCH /platform/jobs/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0/input

{
  "column_include_list": ["address", "phone"],
  "memory_allocation_mb": 4096
}

Response (200 OK):

{
  "status": true,
  "detail": "Successfully updated input fields for job_id 1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0",
  "updated_fields": ["column_include_list", "memory_allocation_mb"]
}

Change Incremental Configuration

Update the incremental column used for tracking:

PATCH /platform/jobs/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0/input

{
  "incremental_column_name": "modified_at",
  "incremental_column_type": "timestamp with time zone"
}

Response (200 OK):

{
  "status": true,
  "detail": "Successfully updated input fields for job_id 1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0",
  "updated_fields": ["incremental_column_name", "incremental_column_type"]
}

Add Primary Keys for Deduplication

Add primary keys when using incremental_with_qualify:

PATCH /platform/jobs/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0/input

{
  "primary_keys": ["id", "tenant_id"]
}

Response (200 OK):

{
  "status": true,
  "detail": "Successfully updated input fields for job_id 1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0",
  "updated_fields": ["primary_keys"]
}

Update Multiple Fields

PATCH /platform/jobs/a9f82c14_7e21_4b5a_8c9d_12345abcdef0_0/input

{
  "column_include_list": ["order_total", "discount_amount"],
  "load_type": "incremental",
  "incremental_column_name": "updated_at",
  "incremental_column_type": "timestamp with time zone"
}

Response (200 OK):

{
  "status": true,
  "detail": "Successfully updated input fields for job_id a9f82c14_7e21_4b5a_8c9d_12345abcdef0_0",
  "updated_fields": ["column_include_list", "load_type", "incremental_column_name", "incremental_column_type"]
}

Error Responses

404 Not Found

{
  "detail": "job_id 1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0 not found"
}

500 Internal Server Error

{
  "detail": "Unable to complete transaction due to database error"
}

Pipeline Refresh

When certain fields are updated (like load_type or incremental configuration), the endpoint automatically triggers a pipeline refresh to update the Airflow DAG configuration. This ensures the pipeline uses the new settings on the next execution.

Fields that trigger pipeline refresh:

load_type
incremental_column_name
incremental_column_type
primary_keys

Use Cases

Adding Columns to Existing Pipeline

When you need to sync additional columns from a source table:

Get the current job configuration to see existing columns
Use PATCH to add the new columns
The next pipeline run will include the new columns

// Step 1: Check existing configuration (optional)
GET /platform/jobs/jdbc/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0

// Step 2: Add new columns
PATCH /platform/jobs/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0/input
{
  "column_include_list": ["new_col_1", "new_col_2"]
}

Switching from Full Load to Incremental

When you want to change a job from full load to incremental:

PATCH /platform/jobs/1b33ad2f_33d3_4837_9eeb_83c82c8b909d_0/input
{
  "load_type": "incremental",
  "incremental_column_name": "updated_at",
  "incremental_column_type": "timestamp with time zone"
}

Note: For more complex sync mode migrations with validation, consider using the POST /platform/jobs/jdbc/:jobId/sync-mode endpoint instead.

Notes

This endpoint uses partial update semantics - only specified fields are modified
The column_include_list field uses union logic - columns are added, not replaced
Changes to certain fields will trigger an automatic pipeline DAG refresh
For replacing the entire job input configuration, use PUT /platform/jobs/:jobId/input instead