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Sql Correctness | Skills Pool

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Sql Correctness

SQL evaluation criteria for Databricks. Load when the trace contains execute_sql tool calls or SQL code in responses. Covers syntax validity, Unity Catalog patterns, and Databricks-specific SQL features.

databricks-solutions1,258 スター2026/03/16

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カテゴリ: デバッグ

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SQL Correctness Rubric

When evaluating SQL in agent traces, check these dimensions:

1. Unity Catalog Namespace

Must use 3-level namespace: catalog.schema.table
Never use unqualified table names
Catalog/schema should match the user's context (not hardcoded main.default unless appropriate)

2. Modern DDL Syntax

Use CREATE OR REPLACE instead of DROP IF EXISTS + CREATE
Use ALTER TABLE ... SET TBLPROPERTIES for table properties
Use COMMENT ON for documentation

3. Tool Selection

Must use mcp__databricks__execute_sql for SQL execution
Must NOT use Bash with databricks sql CLI as a workaround
Must NOT use notebook execution for simple queries

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Sql Correctness

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作者: databricks-solutions
スター: 1,258
更新日: 2026/03/16
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01SQL Correctness Rubric

4. Databricks SQL Features

Use Delta-specific syntax where appropriate (MERGE INTO, OPTIMIZE, VACUUM)
Use IDENTIFIER() function for dynamic table references
Use SELECT * FROM read_files() for file ingestion, not COPY INTO (unless streaming)

5. Syntax Validity

SQL must be syntactically valid for Databricks SQL (Spark SQL dialect)
String literals use single quotes, identifiers use backticks if needed
Semicolons at statement boundaries

6. Safety

No string interpolation for user-provided values in SQL
Use parameterized queries where applicable
No DROP operations unless explicitly requested

See detailed patterns for specific syntax examples.

02

1. Unity Catalog Namespace

032. Modern DDL Syntax

043. Tool Selection

054. Databricks SQL Features

065. Syntax Validity

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