Actions364
- Continuous Activity Actions
- Dataset Actions
- Get Last Metric Values
- Get Metadata
- Get Schema
- Get Single Metric History
- List Datasets
- List Partitions
- Compute Metrics
- Create Dataset
- Create Managed Dataset
- Delete Data
- Delete Dataset
- Execute Tables Import
- Get Column Lineage
- Get Data
- Get Data - Alternative Version
- Get Dataset Settings
- Get Full Info
- List Tables
- List Tables Schemas
- Prepare Tables Import
- Run Checks
- Set Metadata
- Set Schema
- Synchronize Hive Metastore
- Update Dataset Settings
- Update From Hive Metastore
- API Service Actions
- Bundles Automation-Side Actions
- Bundles Design-Side Actions
- Connection Actions
- Dashboard Actions
- Data Collection Actions
- Data Quality Actions
- Compute Rules on Specific Partition
- Create Data Quality Rules Configuration
- Delete Rule
- Get Data Quality Project Current Status
- Get Data Quality Project Timeline
- Get Data Quality Rules Configuration
- Get Dataset Current Status
- Get Dataset Current Status per Partition
- Get Last Outcome on Specific Partition
- Get Last Rule Results
- Get Rule History
- Update Rule Configuration
- DSS Administration Actions
- Job Actions
- Library Actions
- Dataset Statistic Actions
- Discussion Actions
- Flow Documentation Actions
- Insight Actions
- Internal Metric Actions
- LLM Mesh Actions
- Machine Learning - Lab Actions
- Delete Visual Analysis
- Deploy Trained Model to Flow
- Download Model Documentation of Trained Model
- Generate Model Documentation From Custom Template
- Start Training ML Task
- Update User Metadata for Trained Model
- Update Visual Analysis
- Adjust Forecasting Parameters and Algorithm
- Compute Partial Dependencies of Trained Model
- Compute Subpopulation Analysis of Trained Model
- Create ML Task
- Create Visual Analysis
- Create Visual Analysis and ML Task
- Generate Model Documentation From Default Template
- Generate Model Documentation From File Template
- Get ML Task Settings
- Get ML Task Status
- Get Model Snippet
- Get Partial Dependencies of Trained Model
- Get Scoring Jar of Trained Model
- Get Scoring PMML of Trained Model
- Get Subpopulation Analysis of Trained Model
- Get Trained Model Details
- Get Visual Analysis
- List ML Tasks of Project
- List ML Tasks of Visual Analyses
- List Visual Analyses
- Reguess ML Task
- Machine Learning - Saved Model Actions
- Compute Partial Dependencies of Version
- Get Version Scoring PMML
- Get Version Snippet
- Import MLflow Version From File or Path
- List Saved Models
- List Versions
- Set Version Active
- Compute Subpopulation Analysis of Version
- Create Saved Model
- Delete Version
- Download Model Documentation of Version
- Evaluate MLflow Model Version
- Generate Model Documentation From Custom Template
- Generate Model Documentation From Default Template
- Generate Model Documentation From File Template
- Get MLflow Model Version Metadata
- Get Partial Dependencies of Version
- Get Saved Model
- Get Subpopulation Analysis of Version
- Get Version Details
- Get Version Scoring Jar
- Set Version User Meta
- Update Saved Model
- Long Task Actions
- Machine Learning - Experiment Tracking Actions
- Macro Actions
- Plugin Actions
- Download Plugin
- Fetch From Git Remote
- Get File Detail From Plugin
- Get Git Remote Info
- Get Plugin Settings
- Install Plugin From Git
- Install Plugin From Store
- List Files in Plugin
- List Git Branches
- List Plugin Usages
- Move File or Folder in Plugin
- Add Folder to Plugin
- Create Development Plugin
- Create Plugin Code Env
- Delete File From Plugin
- Delete Git Remote Info
- Delete Plugin
- Download File From Plugin
- Move Plugin to Dev Environment
- Pull From Git Remote
- Push to Git Remote
- Rename File or Folder in Plugin
- Reset to Local Head State
- Reset to Remote Head State
- Set Git Remote Info
- Set Plugin Settings
- Update Plugin Code Env
- Update Plugin From Git
- Update Plugin From Store
- Update Plugin From Zip Archive
- Upload File to Plugin
- Upload Plugin
- Project Deployer Actions
- Get Deployment Settings
- Get Deployment Status
- Create Deployment
- Create Infra
- Create Project
- Delete Bundle
- Delete Deployment
- Delete Infra
- Delete Project
- Get Deployment
- Get Deployment Governance Status
- Get Infra
- Get Infra Settings
- Get Project
- Get Project Settings
- Save Deployment Settings
- Save Infra Settings
- Save Project Settings
- Update Deployment
- Upload Bundle
- SQL Query Actions
- Wiki Actions
- Managed Folder Actions
- Meaning Actions
- Model Comparison Actions
- Notebook Actions
- Project Actions
- Project Folder Actions
- Recipe Actions
- Scenario Actions
- Security Actions
- Streaming Endpoint Actions
- Webapp Actions
- Workspace Actions
Overview
This node integrates with the Dataiku DSS API to perform various operations on different resources within a Dataiku DSS instance. Specifically, for the Long Task resource and the List Tasks in Progress operation, it retrieves a list of long-running tasks currently in progress on the DSS server.
This functionality is useful for monitoring and managing asynchronous or time-consuming tasks that are running in the background of a Dataiku DSS project. For example, users can track the status of data processing jobs, model training tasks, or other automated workflows that take significant time to complete.
Practical examples include:
- Monitoring all active long tasks to check progress or identify stuck tasks.
- Integrating task status checks into automation pipelines to trigger subsequent steps only after certain tasks complete.
- Auditing system usage by listing all ongoing long tasks across projects.
Properties
| Name | Meaning |
|---|---|
| Query Parameters | A collection of optional parameters to filter or modify the request when listing tasks in progress. Possible options include: active (boolean), activity (string), allUsers (boolean), limit (number), page (number), and many others as listed in the provided JSON. These parameters allow fine-grained control over which tasks are returned, such as filtering by activity type, user scope, pagination, and more. |
The full list of query parameters includes many options like active, allUsers, limit, page, filter, tags, type, wait, etc., enabling detailed filtering and pagination of the long tasks.
Output
The node outputs an array of JSON objects representing the tasks currently in progress. Each object corresponds to a long task with its details as returned by the Dataiku DSS API.
If the response contains binary data (not typical for this operation), it would be output as binary data under the binary.data field, but for "List Tasks in Progress" the output is JSON.
Example output structure (simplified):
[
{
"taskId": "string",
"status": "string",
"startTime": "timestamp",
"user": "string",
"activity": "string",
"progress": "number",
...
},
...
]
The exact fields depend on the Dataiku DSS API response for long tasks.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials (an API key) for authentication with the DSS server.
- The node uses HTTP requests to the DSS REST API endpoints.
- No additional external services are required beyond the Dataiku DSS API.
Troubleshooting
- Missing Credentials Error: If the node throws an error about missing credentials, ensure that you have configured the API key credential for the Dataiku DSS instance in n8n.
- Required Parameter Errors: Many operations require specific parameters (e.g., project key, job ID). For "List Tasks in Progress", no mandatory parameters are strictly required, but providing filters may help narrow results.
- API Request Failures: Network issues, incorrect server URL, or invalid API keys will cause request failures. Verify connectivity and credentials.
- Unexpected Response Format: If the API returns unexpected data or errors, check the API version compatibility and the correctness of query parameters.
- Rate Limits or Permissions: Ensure the API key has sufficient permissions to list long tasks and that the DSS instance is not rate-limiting requests.
Links and References
- Dataiku DSS API Documentation
- Dataiku DSS Long Tasks API Reference
- n8n Documentation - Creating Custom Nodes
This summary focuses on the "Long Task" resource and the "List Tasks in Progress" operation, describing how the node constructs the API request, handles input properties, and processes the output accordingly.