databricks

name	databricks
description	Databricks REST API and SQL reference for Rocky's warehouse adapter. Use when implementing SQL execution, Unity Catalog management, workspace bindings, authentication, permission reconciliation, or any Databricks integration in the rocky-databricks crate.

Databricks API Reference for Rocky

SQL Statement Execution API

Primary execution path for all SQL. No SDK needed — pure REST.

Submit Statement

POST https://{host}/api/2.0/sql/statements
Authorization: Bearer {token}
Content-Type: application/json

{
  "warehouse_id": "{warehouse_id}",
  "statement": "SELECT * FROM catalog.schema.table LIMIT 10",
  "wait_timeout": "30s",
  "disposition": "INLINE",
  "format": "JSON_ARRAY"
}

warehouse_id is extracted from the HTTP path: /sql/1.0/warehouses/{warehouse_id}

Response (immediate if fast):

{
  "statement_id": "abc-123",
  "status": { "state": "SUCCEEDED" },
  "manifest": {
    "schema": {
      "columns": [
        { "name": "col1", "type_name": "STRING", "position": 0 }
      ]
    },
    "total_row_count": 10
  },
  "result": {
    "data_array": [["value1"], ["value2"]]
  }
}

Poll Statement (if not immediately complete)

GET https://{host}/api/2.0/sql/statements/{statement_id}
Authorization: Bearer {token}

States: PENDING → RUNNING → SUCCEEDED | FAILED | CANCELED | CLOSED

Poll strategy: 100ms → 200ms → 500ms → 1s → 2s (exponential backoff, cap at 2s)

Cancel Statement

POST https://{host}/api/2.0/sql/statements/{statement_id}/cancel

Important Notes

• wait_timeout: "0s" returns immediately with PENDING — useful for fire-and-forget
• wait_timeout: "30s" waits up to 30s inline before returning — avoids polling for fast queries
• disposition: "INLINE" returns data in response body (good for small results)
• disposition: "EXTERNAL_LINKS" returns presigned URLs for large results (future: Arrow Flight)
• Max statement size: 100KB
• Max concurrent statements per warehouse: varies by warehouse size

Authentication

PAT (Personal Access Token)

Authorization: Bearer {DATABRICKS_TOKEN}

OAuth M2M (Service Principal)

Token request:

POST https://{host}/oidc/v1/token
Content-Type: application/x-www-form-urlencoded

grant_type=client_credentials&
client_id={DATABRICKS_CLIENT_ID}&
client_secret={DATABRICKS_CLIENT_SECRET}&
scope=all-apis

Response:

{
  "access_token": "eyJ...",
  "token_type": "Bearer",
  "expires_in": 3600
}

Implementation:

• Cache the token
• Refresh when expires_in is within 60s of expiry
• Use the access_token as Authorization: Bearer {access_token}

Auto-Detection Logic

if DATABRICKS_TOKEN is set and non-empty:
    use PAT auth
else if DATABRICKS_CLIENT_ID and DATABRICKS_CLIENT_SECRET are set:
    use OAuth M2M
else:
    error: no auth configured

Unity Catalog APIs

Catalog Isolation

PATCH https://{host}/api/2.1/unity-catalog/catalogs/{catalog_name}
Authorization: Bearer {token}
Content-Type: application/json

{
  "isolation_mode": "ISOLATED"
}

Workspace Bindings

Get current bindings:

GET https://{host}/api/2.1/unity-catalog/bindings/catalog/{catalog_name}

Response:

{
  "bindings": [
    { "workspace_id": 12345, "binding_type": "BINDING_TYPE_READ_WRITE" }
  ]
}

Update bindings (add/remove):

PATCH https://{host}/api/2.1/unity-catalog/bindings/catalog/{catalog_name}
Content-Type: application/json

{
  "add": [
    { "workspace_id": 67890, "binding_type": "BINDING_TYPE_READ_WRITE" }
  ],
  "remove": [
    { "workspace_id": 11111 }
  ]
}

SQL Statements Rocky Must Generate

Catalog Lifecycle

-- Create
CREATE CATALOG IF NOT EXISTS <catalog>

-- Tag (keys/values come from [governance.tags] in rocky.toml; 'managed_by' is always set)
ALTER CATALOG <catalog> SET TAGS (
    'managed_by' = '<pipeline_name>'
    -- plus any tags declared under [governance.tags]
)

-- Inspect
DESCRIBE CATALOG <catalog>
-- Returns rows: (info_name, info_value) — check for 'Catalog Name' row

-- Discover managed catalogs
SELECT catalog_name
FROM system.information_schema.catalog_tags
WHERE tag_name = 'managed_by' AND tag_value = '<pipeline_name>'

Schema Lifecycle

-- Create
CREATE SCHEMA IF NOT EXISTS <catalog>.<schema>

-- Tag (keys/values come from [governance.tags]; Rocky always sets 'managed_by')
ALTER SCHEMA <catalog>.<schema> SET TAGS (
    'layer' = 'raw',
    'connector' = '<connector>',
    'managed_by' = '<pipeline_name>'
    -- plus any tags declared under [governance.tags]
)

-- List schemas
SHOW SCHEMAS IN <catalog>

Incremental Copy (Core Operation)

Rocky reads the prior watermark (MAX(<timestamp_col>) from the previous run) out of its redb state store and threads it into the generated SQL as a literal — it does not subquery the target table. See rocky-core/src/sql_gen.rs; a regression test asserts the generated SQL does not contain SELECT COALESCE(MAX(...)).

-- Full refresh
SELECT * FROM <source_catalog>.<source_schema>.<table>

-- Incremental (append rows newer than the stored watermark)
SELECT * FROM <source_catalog>.<source_schema>.<table>
WHERE _fivetran_synced > TIMESTAMP '<prior_watermark_literal>'

After the copy, Rocky re-queries MAX(<timestamp_col>) from the source and records it as the next watermark.

Schema Drift Detection

-- Get column info for comparison
DESCRIBE TABLE <catalog>.<schema>.<table>
-- Returns rows: (col_name, data_type, comment)

-- On a SAFE type widening (e.g. INT -> BIGINT): evolve in place
ALTER TABLE <target_catalog>.<target_schema>.<table> ALTER COLUMN <col> TYPE <wider_type>

-- On an UNSAFE type change: drop, then full refresh on next run
DROP TABLE IF EXISTS <target_catalog>.<target_schema>.<table>

The safe-vs-unsafe decision is drift.rs::is_safe_type_widening().

Permission Reconciliation

-- Inspect current grants
SHOW GRANTS ON CATALOG <catalog>
-- Returns rows: (principal, action_type, object_type, object_name)

SHOW GRANTS ON SCHEMA <catalog>.<schema>

-- Grant (principal always backtick-quoted)
GRANT BROWSE ON CATALOG <catalog> TO `<principal>`
GRANT USE CATALOG ON CATALOG <catalog> TO `<principal>`
GRANT SELECT ON CATALOG <catalog> TO `<principal>`
GRANT USE SCHEMA ON SCHEMA <catalog>.<schema> TO `<principal>`

-- Revoke
REVOKE BROWSE ON CATALOG <catalog> FROM `<principal>`

-- Supported permission types for reconciliation:
-- BROWSE, USE CATALOG, USE SCHEMA, SELECT, MANAGE, MODIFY

Data Quality Checks

-- Single table row count
SELECT COUNT(*) FROM <catalog>.<schema>.<table>

-- Batched row counts (UNION ALL, batches of 200)
SELECT 'cat1' AS c, 'sch1' AS s, 'tbl1' AS t, COUNT(*) AS cnt FROM cat1.sch1.tbl1
UNION ALL
SELECT 'cat1' AS c, 'sch1' AS s, 'tbl2' AS t, COUNT(*) AS cnt FROM cat1.sch1.tbl2
UNION ALL
...

-- Column introspection (batched by schema)
SELECT lower(table_schema), lower(table_name), lower(column_name)
FROM <catalog>.information_schema.columns
WHERE table_schema IN ('schema1', 'schema2', ...)
ORDER BY table_schema, table_name, ordinal_position

Validation Rules

SQL identifiers (catalogs, schemas, tables):

^[a-zA-Z0-9_]+$

Reject anything that doesn't match. Never use format!() with unvalidated strings.

Principal names (for GRANT/REVOKE):

^[a-zA-Z0-9_ \-\.@]+$

Always wrap in backticks: `principal_name`

Error Handling

Common Databricks errors to handle:

• TEMPORARILY_UNAVAILABLE (503) — Retry with exponential backoff
• INVALID_PARAMETER_VALUE — Bad SQL or missing object
• RESOURCE_DOES_NOT_EXIST — Table/catalog/schema not found
• PERMISSION_DENIED — Missing privileges
• InvalidOperationHandle — Statement expired, re-submit
• Rate limiting — Warehouse concurrency limit reached, back off

Retry strategy: 3 attempts, exponential backoff (1s → 3s → 9s), only on transient errors (503, rate limit, InvalidOperationHandle).