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Databricks and Kaggle integration
Save yourself the work of writing custom integrations for Databricks and Kaggle and use n8n instead. Build adaptable and scalable Data & Storage, workflows that work with your technology stack. All within a building experience you will love.
How to connect Databricks and Kaggle
Create a new workflow and add the first step
In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.
Build your own Databricks and Kaggle integration
Create custom Databricks and Kaggle workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.
Databricks supported actions
Execute Query
Execute a SQL query and wait for results
Create Directory
Create a directory in volume
Delete Directory
Delete a directory in volume
Delete File
Delete a file from a volume
Download File
Download file content from a volume
Get File Metadata
Get file metadata from a volume
List Directory
List directory contents in volume
Upload File
Upload a file (up to 5 GiB) to Databricks volumes
Create Conversation Message
Create a new conversation message
Execute Message SQL Query
Execute a SQL query from a message attachment
Get Conversation Message
Get a conversation message by ID
Get Genie Space
Get details of a Genie space
Get Query Results
Get results of a SQL query execution
Start Conversation
Start a new conversation
Query Endpoint
Query a serving endpoint. The input format is automatically detected from the endpoint schema.
Create Catalog
Create a new catalog
Create Function
Create a new function
Create Table
Register a new table
Create Volume
Create a new volume
Delete Catalog
Delete a catalog
Delete Function
Delete a function
Delete Table
Delete a table
Delete Volume
Delete a volume
Get Catalog
Get catalog information
Get Function
Get function information
Get Table
Get table information
Get Volume
Get volume information
List Catalogs
List all catalogs
List Functions
List functions in schema
List Tables
List tables in schema
List Volumes
List volumes in schema
Update Catalog
Update catalog information
Create Index
Create a new vector search index
Get Index
Get details of a vector search index
List Indexes
List all vector search indexes
Query Index
Query a vector search index with text or vectors
Supported API Endpoints for Kaggle
GET
List competitions
List available competitions
kaggle competitions list
GET
List competition files
List competition files
kaggle competitions files
POST
Download competition files
Download competition files
kaggle competitions download
POST
Submit to a competition
Make a new competition submission
kaggle competitions submit
GET
List competition submissions
Show your competition submissions
kaggle competitions submissions
GET
List datasets
List available datasets.
kaggle datasets list
GET
List files
List dataset files.
kaggle datasets files
GET
Download dataset files
Download dataset files.
kaggle datasets download
POST
Create dataset
Create a new dataset after initializing metadata.
/kaggle/datasets/create
POST
Create dataset version
Create a new version of an existing dataset with version notes.
/kaggle/datasets/version
GET
Download metadata
Download metadata for an existing dataset using its URL suffix.
/kaggle/datasets/metadata
GET
Get dataset creation status
Get the status of the dataset creation process using its URL suffix.
/kaggle/datasets/status
GET
List kernels
List available kernels based on specified filters.
/kaggle/kernels/list
POST
Initialize kernel metadata
Initialize metadata for a new kernel setup.
/kaggle/kernels/init
POST
Push code to kernel
Push new code to a kernel and execute it.
/kaggle/kernels/push
GET
Pull code from kernel
Pull down the latest code from a kernel.
/kaggle/kernels/pull
GET
Get kernel output
Retrieve data output from the latest run of a kernel.
/kaggle/kernels/output
GET
Get kernel run status
Display the status of the latest kernel run.
/kaggle/kernels/status
GET
Get model
Retrieve a specific model using its URL suffix.
/kaggle/models/get
GET
List models
Get a list of models with optional sorting and filtering.
/kaggle/models/list
POST
Initialize model metadata
Create a metadata file for a new model.
/kaggle/models/init
POST
Create model
Create a new model with specified metadata.
/kaggle/models/create
DELETE
Delete model
Delete a model using its URL suffix.
/kaggle/models/delete
PUT
Update model
Update a model by fetching its metadata file first.
/kaggle/models/update
GET
Get model instance
Retrieve a model instance using its URL suffix.
/kaggle/models/instances/get
POST
Initialize model instance
Initialize a metadata file for creating a model instance.
/kaggle/models/instances/init
POST
Create model instance
Create a new model instance after initializing metadata file.
/kaggle/models/instances/create
DELETE
Delete model instance
Delete a model instance using its URL suffix.
/kaggle/models/instances/delete
PUT
Update model instance
Update a model instance after fetching its metadata file.
/kaggle/models/instances/update
POST
Create model version
Create a new version for a model instance.
/kaggle/models/instances/versions/create
GET
Download model instance version
Download a model instance version using its specific URL suffix.
/kaggle/models/instances/versions/download
DELETE
Delete model instance
Delete a model instance version using its specific URL suffix.
/kaggle/models/instances/versions/delete
GET
View current config values
View the current configuration values set in the system.
/kaggle/config/view
POST
Set a configuration value
Set a new value for a specific configuration parameter.
/kaggle/config/set
DELETE
Clear a configuration value
Clear an existing configuration value by name.
/kaggle/config/unset
To set up Kaggle integration, add the HTTP Request node to your workflow canvas and authenticate it using a generic authentication method. The HTTP Request node makes custom API calls to Kaggle to query the data you need using the API endpoint URLs you provide.
See the example hereThese API endpoints were generated using n8n
n8n AI workflow transforms web scraping into an intelligent, AI-powered knowledge extraction system that uses vector embeddings to semantically analyze, chunk, store, and retrieve the most relevant API documentation from web pages. Remember to check the Kaggle official documentation to get a full list of all API endpoints and verify the scraped ones!
Databricks and Kaggle integration details
Databricks
Related categories
FAQs
FAQ
Can Databricks connect with Kaggle?
Can I use Databricks’s API with n8n?
Can I use Kaggle’s API with n8n?
Is n8n secure for integrating Databricks and Kaggle?
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