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Enables an AI agent to install, configure, and use the dremio-cli Python tool to manage Dremio Software and Cloud from the command line.
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Based on SOC occupation classification
| name | Dremio CLI |
| description | Enables an AI agent to install, configure, and use the dremio-cli Python tool to manage Dremio Software and Cloud from the command line. |
This skill equips you to use the dremio-cli — a Python CLI tool that provides 100% API coverage for both Dremio Software (self-hosted) and Dremio Cloud. Use it to manage catalogs, execute SQL, manage sources/views/jobs, control access, and perform GitOps workflows via Dremio-as-Code.
Requires Python 3.8+.
# Standard install
pip install dremio-cli
# Or use pipx for an isolated environment
pipx install dremio-cli
# Verify
dremio --version
The CLI supports profile-based configuration and environment variables. Ask the user which Dremio edition they use (Software or Cloud) and guide them through setup.
Profiles are stored locally and can be switched between. A user can have multiple profiles for different environments.
dremio profile create --name myprofile --type software \
--base-url https://dremio.company.com \
--username admin --password secret
dremio profile create --name cloud-prod --type cloud \
--base-url https://api.dremio.cloud \
--project-id <project-id> \
--token <pat-token>
For the EU control plane, use
--base-url https://api.eu.dremio.cloud.
# Use a specific profile for a single command
dremio --profile cloud-prod catalog list
# Set a default profile
dremio profile set-default myprofile
The user can also set credentials via environment variables or a .env file:
export DREMIO_BASE_URL=https://dremio.company.com
export DREMIO_USERNAME=admin
export DREMIO_PASSWORD=secret
Agent prompt: "To use the Dremio CLI, I'll need to configure credentials. Are you using Dremio Software or Dremio Cloud? Would you like to create a named profile or set environment variables?"
The CLI supports three output formats. Use --output json when you need to parse results programmatically.
# Table (default, human-readable)
dremio catalog list
# JSON (best for scripting and parsing)
dremio --output json catalog list
# YAML
dremio --output yaml catalog list
Use --verbose for debugging.
dremio catalog list # List all catalog items
dremio catalog get <id> # Get item details by ID
dremio catalog get-by-path <path> # Get item details by path
dremio sql execute "<query>" # Execute a SQL query
dremio sql explain "<query>" # Show execution plan
dremio sql validate "<query>" # Validate SQL syntax
SQL execution is asynchronous on Dremio Software — the CLI handles polling automatically and returns results.
Use --async for long-running queries to return the job ID immediately without waiting.
dremio source list # List all sources
dremio source create --name MyDB \
--type POSTGRES --config-file db.json # Create a source from config
dremio source refresh <id> # Refresh source metadata
dremio view list # List views
dremio view create --path "Analytics.sales_summary" \
--sql "SELECT date, SUM(amount) FROM sales GROUP BY date"
dremio view update <id> # Update a view
dremio job list # List jobs
dremio job list --max-results 10 # List recent jobs (limited)
dremio job get <job-id> # Get job details
dremio job results <job-id> # Get job results
dremio job cancel <job-id> # Cancel a running job
dremio job profile <job-id> \
--download profile.zip # Download job profile
dremio space create --name Analytics # Create a space
dremio folder create --path <path> # Create a folder
dremio grant list <id> # List grants on an object
dremio grant add <id> \
--grantee-type ROLE \
--grantee-id analyst \
--privileges SELECT # Grant access
dremio user list # List users
dremio role list # List roles
dremio wiki set <id> --file README.md # Set wiki content from file
dremio tag set <id> --tags "production,sensitive,pii" # Set tags
| Feature | Software | Cloud |
|---|---|---|
| Catalog Operations | ✅ | ✅ |
| SQL Execution | ✅ | ⚠️ Limited |
| Job Management | ✅ | ✅ |
| View Management | ✅ | ✅ |
| Source Management | ✅ | ✅ |
| Space/Folder Mgmt | ✅ | ✅ |
| Tags & Wiki | ✅ | ✅ |
| Grant Management | ✅ | ✅ |
| User Management | ✅ | ⚠️ Via Console |
| Role Management | ✅ | ⚠️ Via Console |
| Table Operations | ✅ | ✅ |
The CLI includes a sync feature for managing Dremio catalog objects (Spaces, Folders, Views) as local files — enabling GitOps workflows.
Create a dremio.yaml in your project root:
version: "1.0"
scope:
path: "dremio-catalog.finance" # Dremio path to sync
type: "SPACE" # SPACE or ICEBERGCATALOG
ignore:
- "*.tmp"
# Pull current state from Dremio into local files
dremio sync pull
# Edit views locally (SQL + YAML pairs)
# Then push changes back to Dremio
dremio sync push
Pulling creates a directory structure mirroring Dremio with .sql and .yaml file pairs for each view.
Each view is defined by a YAML file that can include SQL, tags, wiki, access control, governance policies, and reflections:
name: revenue_report
type: VIRTUAL_DATASET
path: ["dremio-catalog", "finance", "reports", "revenue_report"]
sql: |
SELECT region, sum(amount) as total
FROM "dremio-catalog".finance.stg_sales
GROUP BY region
dependencies:
- "stg_sales"
tags: ["finance", "official"]
description: "docs/revenue_report.md"
access_control:
roles:
- name: "finance_managers"
privileges: ["SELECT"]
users:
- name: "auditor@example.com"
privileges: ["SELECT", "ALTER"]
Note: Governance policies (RBAC, row access, masking) and reflections are NOT automatically pulled — they must be manually defined in YAML. Full DAC docs: https://github.com/developer-advocacy-dremio/dremio-python-cli/blob/main/dremio-cli/docs/dac.md
# 1. Create a source
dremio source create --name MyDB --type POSTGRES --config-file db.json
# 2. Create a space
dremio space create --name Analytics
# 3. Create a view
dremio view create --path "Analytics.sales_summary" \
--sql "SELECT date, SUM(amount) FROM sales GROUP BY date"
# 4. Grant access
dremio grant add <view-id> --grantee-type ROLE \
--grantee-id analyst --privileges SELECT
dremio job list --max-results 10
dremio job get <job-id>
dremio job profile <job-id> --download profile.zip
dremio wiki set <id> --file README.md
dremio tag set <id> --tags "production,sensitive,pii"
When the user asks you to manage Dremio using the CLI:
dremio --version. If not installed, install with pip install dremio-cli.dremio profile list to see existing profiles. If none exist, guide the user to create one (Software vs Cloud).--output json when you need to parse results.--output json when you need to extract IDs or specific fields from command output.--verbose to debug connectivity or authentication issues.--async for SQL execution when you only need to submit a query and get the job ID back.Enables an AI agent to authenticate with and make curl requests to the Dremio REST API for both Dremio Software and Dremio Cloud.
Guides an AI agent through adding data sources to Dremio by asking the user the right questions, recommending connection settings, and linking to the exact documentation for each connector.
Teaches an AI agent how to create, manage, and maintain Apache Iceberg tables in Dremio — including DML, schema evolution, time travel, table maintenance, partitioning, and versioned catalog workflows.
Teaches an AI agent data modeling best practices in a Dremio lakehouse — medallion architecture, views vs tables, reflections strategy, partitioning, dimensional modeling, and semantic layer design.
Enables an AI agent to use dremio-simple-query (lightweight SQL/Arrow Flight) and DremioFrame (full dataframe builder with ingestion, modeling, and admin) to interact with Dremio from Python.
Teaches an AI agent the Dremio SQL dialect — unique syntax, Iceberg DML, reflections DDL, versioned queries, RBAC commands, and links to the full SQL reference docs.