Databricks Unity Catalog

Quick Start

Volume File Operations (MCP Tools)

# List files in a volume
list_volume_files(volume_path="/Volumes/catalog/schema/volume/folder/")

# Upload file to volume
upload_to_volume(
    local_path="/tmp/data.csv",
    volume_path="/Volumes/catalog/schema/volume/data.csv"
)

# Download file from volume
download_from_volume(
    volume_path="/Volumes/catalog/schema/volume/data.csv",
    local_path="/tmp/downloaded.csv"
)

# Create directory
create_volume_directory(volume_path="/Volumes/catalog/schema/volume/new_folder")

Enable System Tables Access

-- Grant access to system tables
GRANT USE CATALOG ON CATALOG system TO `data_engineers`;
GRANT USE SCHEMA ON SCHEMA system.access TO `data_engineers`;
GRANT SELECT ON SCHEMA system.access TO `data_engineers`;

Common Queries

-- Table lineage: What tables feed into this table?
SELECT source_table_full_name, source_column_name
FROM system.access.table_lineage
WHERE target_table_full_name = 'catalog.schema.table'
  AND event_date >= current_date() - 7;

-- Audit: Recent permission changes
SELECT event_time, user_identity.email, action_name, request_params
FROM system.access.audit
WHERE action_name LIKE '%GRANT%' OR action_name LIKE '%REVOKE%'
ORDER BY event_time DESC
LIMIT 100;

-- Billing: DBU usage by workspace
SELECT workspace_id, sku_name, SUM(usage_quantity) AS total_dbus
FROM system.billing.usage
WHERE usage_date >= current_date() - 30
GROUP BY workspace_id, sku_name;

MCP Tool Integration

Use mcp__databricks__execute_sql for system table queries:

# Query lineage
mcp__databricks__execute_sql(
    sql_query="""
        SELECT source_table_full_name, target_table_full_name
        FROM system.access.table_lineage
        WHERE event_date >= current_date() - 7
    """,
    catalog="system"
)

Best Practices

1. Filter by date - System tables can be large; always use date filters
2. Use appropriate retention - Check your workspace's retention settings
3. Grant minimal access - System tables contain sensitive metadata
4. Schedule reports - Create scheduled queries for regular monitoring

Related Skills

• databricks-spark-declarative-pipelines - for pipelines that write to Unity Catalog tables
• databricks-jobs - for job execution data visible in system tables
• databricks-synthetic-data-generation - for generating data stored in Unity Catalog Volumes
• databricks-aibi-dashboards - for building dashboards on top of Unity Catalog data

Resources

• Unity Catalog System Tables
• Audit Log Reference