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 Dataiku resources. Specifically, for the Job resource and the List Latest Jobs operation, it retrieves a list of the most recent jobs within a specified project. This is useful for monitoring job executions, auditing recent activity, or triggering workflows based on job statuses.
Typical use cases include:
- Fetching the latest job runs in a project to analyze their outcomes.
- Automating notifications or alerts based on recent job completions.
- Integrating job status data into dashboards or reports.
Properties
| Name | Meaning |
|---|---|
| Project Key | The unique identifier of the Dataiku project from which to list the latest jobs. |
| Query Parameters | Optional additional parameters to filter or paginate the results. Includes options like: |
| - Active (boolean) | |
| - Activity (string) | |
| - All Users (boolean) | |
| - Limit (number): Max number of results to return (default 50) | |
| - Page (number): Page number for pagination | |
| - Filter (string), Tags (string), and many other optional filters as per the full list above |
The "Query Parameters" collection allows fine-tuning the request by specifying filters such as active status, user scope, pagination limits, and more.
Output
The output is an array of JSON objects representing the latest jobs retrieved from the Dataiku DSS instance for the specified project.
- Each item in the output corresponds to a job object returned by the Dataiku DSS API.
- The exact structure of each job object depends on the Dataiku API response but typically includes job metadata such as job ID, status, start time, end time, and related details.
- If the API returns binary data (not typical for this operation), it would be provided in the
binaryfield, but for listing jobs, the output is JSON only.
Dependencies
- Requires a valid connection to a Dataiku DSS instance.
- Needs an API key credential for authentication with the Dataiku DSS API.
- The node expects the base URL of the Dataiku DSS server and the user API key to be configured in the credentials.
- No additional external dependencies are required beyond the standard n8n environment and the Dataiku DSS API access.
Troubleshooting
- Missing Credentials Error: If the node throws an error about missing API credentials, ensure that the Dataiku DSS API credentials are properly set up in n8n.
- Project Key Required: The operation requires a valid project key; if omitted, the node will throw an error.
- API Errors: Errors from the Dataiku API (e.g., unauthorized, not found) will be surfaced as node errors with messages indicating the issue.
- Empty Results: If no jobs are returned, verify that the project key is correct and that there are recent jobs available.
- Pagination Issues: Use the "Limit" and "Page" query parameters to control the number of results and navigate through pages if the result set is large.
Links and References
- Dataiku DSS API Documentation
- Dataiku DSS Jobs API Reference
- n8n Documentation on Creating Custom Nodes
This summary focuses on the "Job" resource and the "List Latest Jobs" operation as requested, extracting relevant input properties, output format, and usage context from the provided source code and property definitions.