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Databricks REST API

Unified analytics platform for big data and AI workloads

Databricks is a unified data analytics platform built on Apache Spark that enables data engineering, collaborative data science, and machine learning at scale. The REST API provides programmatic access to workspaces, clusters, jobs, notebooks, and Delta Lake operations, allowing developers to automate data pipelines, manage infrastructure, and integrate ML workflows into existing applications.

Base URL https://.cloud.databricks.com/api/2.0

API Endpoints

Method	Endpoint	Description
GET	`/clusters/list`	List all clusters in the workspace
POST	`/clusters/create`	Create a new Spark cluster with specified configuration
POST	`/clusters/start`	Start a terminated cluster by cluster ID
POST	`/clusters/delete`	Terminate and delete a cluster permanently
GET	`/jobs/list`	List all jobs configured in the workspace
POST	`/jobs/create`	Create a new job with tasks, schedule, and cluster configuration
POST	`/jobs/run-now`	Trigger an immediate run of an existing job
GET	`/jobs/runs/get`	Get details and status of a specific job run
GET	`/workspace/list`	List workspace objects like notebooks, directories, and libraries
POST	`/workspace/import`	Import a notebook or directory into the workspace
POST	`/workspace/export`	Export a notebook in specified format (SOURCE, HTML, DBC)
GET	`/dbfs/list`	List files and directories in Databricks File System
POST	`/dbfs/put`	Upload a file to DBFS with specified path
POST	`/sql/statements`	Execute SQL queries on SQL warehouses and retrieve results
GET	`/unity-catalog/schemas`	List schemas in Unity Catalog metastore

Code Examples

curl -X GET 'https://your-instance.cloud.databricks.com/api/2.0/clusters/list' \
  -H 'Authorization: Bearer dapi1234567890abcdef' \
  -H 'Content-Type: application/json'

const response = await fetch('https://your-instance.cloud.databricks.com/api/2.0/clusters/list', {
  method: 'GET',
  headers: {
    'Authorization': 'Bearer dapi1234567890abcdef',
    'Content-Type': 'application/json'
  }
});
const clusters = await response.json();
console.log(clusters);

import requests

url = 'https://your-instance.cloud.databricks.com/api/2.0/clusters/list'
headers = {
    'Authorization': 'Bearer dapi1234567890abcdef',
    'Content-Type': 'application/json'
}

response = requests.get(url, headers=headers)
clusters = response.json()
print(clusters)

Use Databricks from Claude / Cursor / ChatGPT

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execute_databricks_query Execute SQL queries on Databricks SQL warehouses and return structured results for data analysis

manage_databricks_cluster Create, start, stop, or configure Spark clusters for running data workloads

run_databricks_job Trigger and monitor job executions for automated data pipelines and ML workflows

access_delta_tables Read from and write to Delta Lake tables with schema evolution and time travel capabilities

manage_workspace_notebooks Import, export, and execute notebooks programmatically for collaborative data science

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Databricks REST API

API Endpoints

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Code Examples

Use Databricks from Claude / Cursor / ChatGPT

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