/databricks-dbsql

name: databricks-dbsql
description: >-
  Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities.
  This skill MUST be invoked when the user mentions: "DBSQL", "Databricks SQL",
  "SQL warehouse", "SQL scripting", "stored procedure", "CALL procedure",
  "materialized view", "CREATE MATERIALIZED VIEW", "pipe syntax", "|>",
  "geospatial", "H3", "ST_", "spatial SQL", "collation", "COLLATE",
  "ai_query", "ai_classify", "ai_extract", "ai_gen", "AI function",
  "http_request", "remote_query", "read_files", "Lakehouse Federation",
  "recursive CTE", "WITH RECURSIVE", "multi-statement transaction",
  "temp table", "temporary view", "pipe operator".
  SHOULD also invoke when the user asks about SQL best practices, data modeling
  patterns, or advanced SQL features on Databricks.
compatibility: Requires databricks CLI (>= v1.0.0)
metadata:
  version: "0.1.0"
parent: databricks-core

Databricks SQL (DBSQL) - Advanced Features

Quick Reference

| Feature | Key Syntax | Since | Reference | |---------|-----------|-------|-----------| | SQL Scripting | `BEGIN...END`, `DECLARE`, `IF/WHILE/FOR` | DBR 16.3+ | [references/sql-scripting.md](references/sql-scripting.md) | | Stored Procedures | `CREATE PROCEDURE`, `CALL` | DBR 17.0+ | [references/sql-scripting.md](references/sql-scripting.md) | | Recursive CTEs | `WITH RECURSIVE` | DBR 17.0+ | [references/sql-scripting.md](references/sql-scripting.md) | | Transactions | `BEGIN ATOMIC...END` | Preview | [references/sql-scripting.md](references/sql-scripting.md) | | Materialized Views | `CREATE MATERIALIZED VIEW` | Pro/Serverless | [references/materialized-views-pipes.md](references/materialized-views-pipes.md) | | Temp Tables | `CREATE TEMPORARY TABLE` | All | [references/materialized-views-pipes.md](references/materialized-views-pipes.md) | | Pipe Syntax | `\|>` operator | DBR 16.1+ | [references/materialized-views-pipes.md](references/materialized-views-pipes.md) | | Geospatial (H3) | `h3_longlatash3()`, `h3_polyfillash3()` | DBR 11.2+ | [references/geospatial-collations.md](references/geospatial-collations.md) | | Geospatial (ST) | `ST_Point()`, `ST_Contains()`, 80+ funcs | DBR 16.0+ | [references/geospatial-collations.md](references/geospatial-collations.md) | | Collations | `COLLATE`, `UTF8_LCASE`, locale-aware | DBR 16.1+ | [references/geospatial-collations.md](references/geospatial-collations.md) | | AI Functions | `ai_query()`, `ai_classify()`, 11+ funcs | DBR 15.1+ | [references/ai-functions.md](references/ai-functions.md) | | http_request | `http_request(conn, ...)` | Pro/Serverless | [references/ai-functions.md](references/ai-functions.md) | | remote_query | `SELECT * FROM remote_query(...)` | Pro/Serverless | [references/ai-functions.md](references/ai-functions.md) | | read_files | `SELECT * FROM read_files(...)` | All | [references/ai-functions.md](references/ai-functions.md) | | Data Modeling | Star schema, Liquid Clustering | All | [references/best-practices.md](references/best-practices.md) |

---

Common Patterns

SQL Scripting - Procedural ETL

BEGIN
  DECLARE v_count INT;
  DECLARE v_status STRING DEFAULT 'pending';

  SET v_count = (SELECT COUNT(*) FROM catalog.schema.raw_orders WHERE status = 'new');

  IF v_count > 0 THEN
    INSERT INTO catalog.schema.processed_orders
    SELECT *, current_timestamp() AS processed_at
    FROM catalog.schema.raw_orders
    WHERE status = 'new';

    SET v_status = 'completed';
  ELSE
    SET v_status = 'skipped';
  END IF;

  SELECT v_status AS result, v_count AS rows_processed;
END

Stored Procedure with Error Handling

CREATE OR REPLACE PROCEDURE catalog.schema.upsert_customers(
  IN p_source STRING,
  OUT p_rows_affected INT
)
LANGUAGE SQL
SQL SECURITY INVOKER
BEGIN
  DECLARE EXIT HANDLER FOR SQLEXCEPTION
  BEGIN
    SET p_rows_affected = -1;
    SIGNAL SQLSTATE '45000'
      SET MESSAGE_TEXT = concat('Upsert failed for source: ', p_source);
  END;

  MERGE INTO catalog.schema.dim_customer AS t
  USING (SELECT * FROM identifier(p_source)) AS s
  ON t.customer_id = s.customer_id
  WHEN MATCHED THEN UPDATE SET *
  WHEN NOT MATCHED THEN INSERT *;

  SET p_rows_affected = (SELECT COUNT(*) FROM identifier(p_source));
END;

-- Invoke:
CALL catalog.schema.upsert_customers('catalog.schema.staging_customers', ?);

Materialized View with Scheduled Refresh

CREATE OR REPLACE MATERIALIZED VIEW catalog.schema.daily_revenue
  CLUSTER BY (order_date)
  SCHEDULE EVERY 1 HOUR
  COMMENT 'Hourly-refreshed daily revenue by region'
AS SELECT
    order_date,
    region,
    SUM(amount) AS total_revenue,
    COUNT(DISTINCT customer_id) AS unique_customers
FROM catalog.schema.fact_orders
JOIN catalog.schema.dim_store USING (store_id)
GROUP BY order_date, region;

Pipe Syntax - Readable Transformations

-- Traditional SQL rewritten with pipe syntax
FROM catalog.schema.fact_orders
  |> WHERE order_date >= current_date() - INTERVAL 30 DAYS
  |> AGGREGATE SUM(amount) AS total, COUNT(*) AS cnt GROUP BY region, product_category
  |> WHERE total > 10000
  |> ORDER BY total DESC
  |> LIMIT 20;

AI Functions - Enrich Data with LLMs

-- Classify support tickets
SELECT
  ticket_id,
  description,
  ai_classify(description, ARRAY('billing', 'technical', 'account', 'feature_request')) AS category,
  ai_analyze_sentiment(description) AS sentiment
FROM catalog.schema.support_tickets
LIMIT 100;

-- Extract entities from text
SELECT
  doc_id,
  ai_extract(content, ARRAY('person_name', 'company', 'dollar_amount')) AS entities
FROM catalog.schema.contracts;

-- General-purpose AI query with structured output
SELECT ai_query(
  'databricks-meta-llama-3-3-70b-instruct',
  concat('Summarize this customer feedback in JSON with keys: topic, sentiment, action_items. Feedback: ', feedback),
  returnType => 'STRUCT<topic STRING, sentiment STRING, action_items ARRAY<STRING>>'
) AS analysis
FROM catalog.schema.customer_feedback
LIMIT 50;

Geos