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, allowing users to perform a wide range of operations on various Dataiku DSS resources. Specifically, for the Connection resource and the List Connections Names operation, the node fetches and lists all connection names available on the Dataiku DSS instance.
This functionality is useful when you want to retrieve an overview or inventory of all connections configured in your Dataiku DSS environment, for example, to dynamically select a connection for further processing or auditing purposes.
Practical Example
- You want to list all connection names to display them in a dropdown for user selection in a workflow.
- You need to audit or verify existing connections before creating new ones or updating existing configurations.
Properties
| Name | Meaning |
|---|---|
| Query Parameters | A collection of optional key-value parameters to filter or modify the API request. Options include: Active (boolean), Activity (string), All Users (boolean), Archive Path (string), Catalog Name (string), Code Env Name (string), Column Name (string), Columns (string), Connected (boolean), Connection Name (string), Container Execution Configuration Name (string), Deletion Mode (string), Destination ID (string), Drop Data (boolean), Export Analysis Models (boolean), Export Managed (boolean), Export Saved Models (boolean), Export Uploads (boolean), File Part (string), Filter (string), Folder ID (string), Folder Reference (string), Force Rebuild Env (boolean), Foreign (boolean), Format (string), Format Params (string), Full Class Name (string), Full Reguess (boolean), Include All Partitions (boolean), Include Libs (boolean), Limit (number, min 1, default 50), Max Dataset Count (number), Metric Lookup (string), Min Timestamp (number), Name (string), Only Monitored (boolean), Page (number), Partition (string), Partitions (string), Path (string), Peek (boolean), Prediction Type (string), Project Folder ID (string), Project Key (string), Published Project Key (string), Published Service ID (string), Purpose (string), Remote (string), Remove Intermediate (boolean), Reassign To (string), Results per Page (number), Rule ID (string), Schema Name (string), Step ID (string), Sub-Folder Name (string), Tags (string), Target Variable (string), Time Series Identifiers (string), Time Variable (string), Trigger ID (string), Trigger Run ID (string), Trust For Everybody (boolean), Type (string), Versions (string), Wait (boolean), With Scenarios (boolean). |
Note: The "Query Parameters" property allows flexible filtering or pagination options depending on the API endpoint's capabilities.
Output
The output is a JSON array where each item corresponds to a connection name retrieved from the Dataiku DSS instance.
- The
jsonfield contains the parsed response from the API listing connection names. - If the operation involves downloading files or binary data (not applicable here), the node would provide binary data accordingly.
For the List Connections Names operation, the output will be a JSON object or array containing the names of connections, suitable for use in subsequent workflow steps.
Dependencies
- Requires an active connection to a Dataiku DSS instance.
- Requires valid API credentials (an API key credential) for authentication against the Dataiku DSS API.
- The node uses HTTP requests to communicate with the Dataiku 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 the API key credential for Dataiku DSS is properly configured in n8n.
- Required Parameter Missing: The node validates required parameters such as project keys or connection names depending on the operation. Make sure to provide all mandatory inputs.
- API Request Failures: Network issues, incorrect server URLs, or invalid API keys can cause request failures. Verify the Dataiku DSS server URL and API key validity.
- Unexpected Response Format: If the API returns unexpected data or errors, check the Dataiku DSS API documentation for changes or deprecations.
- Large Result Sets: When listing many connections, consider using pagination parameters (
limit,page) in query parameters to avoid timeouts or large payloads.
Links and References
This summary focuses on the Connection resource and the List Connections Names operation, describing how the node constructs the API request, handles input properties, and formats the output accordingly.