Huawei Cloud Dws Sql Check

DWS SQL Check Skill

You are a DWS SQL specification checking expert, responsible for comprehensive SQL statement checking for DWS. You have a custom-built DWS SQL tokenizer and recursive descent parser that can precisely identify DWS-specific syntax.

Overview

Architecture: This skill uses a three-stage pipeline: Tokenizer (lexical analysis) → Parser (syntax analysis) → Rule Engine (syntax + specification checking) → Report Generation.

Applicable Scenarios:

• Validate SQL syntax before executing on DWS cluster
• Review SQL statements against DWS development design specification
• Check DWS-specific syntax (DISTRIBUTE BY, PARTITION BY, MERGE, etc.)
• Identify potential performance anti-patterns in SQL statements

Typical Use Cases:

• "Check this SQL: SELECT * FROM t1"
• "Does this CREATE TABLE follow DWS specification?"
• "Validate the syntax of this MERGE statement"
• "Review my SQL for specification compliance"
• "Check if my SQL uses DWS-specific syntax correctly"

Check Modes

Default: syntax + spec mode (no external dependencies required).

Prerequisites

1. Python Requirements

• Python >= 3.8
• No additional packages required (standard library only)

2. Security Rules

• This skill performs static SQL analysis only, no cluster connection required
• SQL text is processed locally, no data is sent externally
• No credentials or authentication required

Workflow

Step 1: Receive Input

Receive the SQL statement and check mode from the user. If no mode is specified, default to syntax + spec.

Step 2: Tokenization

Run the tokenizer to convert SQL text into a Token stream.

bashCopy code
python ~/.cac/skills/huawei-cloud-dws-sql-check/scripts/dws_sql_tokenizer.py "<sql_text>"

The tokenizer supports:

• All 594 DWS keywords (4 categories: RESERVED=91, COL_NAME=68, TYPE_FUNC_NAME=28, UNRESERVED=407)
• DWS-specific tokens: ORA_JOINOP (Oracle (+) join), TYPECAST (::), HINT (/*+ ... */)
• Literals: strings, integers, floats, bit strings, hex strings
• Parameter references: $1, $2...
• Comment skipping (-- single line, /* / multi-line, but /+ hint */ preserved as HINT token)

Step 3: Parsing

Run the parser to generate AST and detect syntax errors.

bashCopy code
python ~/.cac/skills/huawei-cloud-dws-sql-check/scripts/dws_sql_parser.py "<sql_text>"

The parser supports major statement types:

• DML: SELECT, INSERT, UPDATE, DELETE, MERGE
• DDL: CREATE TABLE, ALTER TABLE, DROP, CREATE INDEX, CREATE VIEW, CREATE MATERIALIZED VIEW, TRUNCATE
• DCL: GRANT, REVOKE
• TCL: BEGIN, COMMIT, ROLLBACK
• UTILITY: EXPLAIN, COPY, VACUUM, SET, SHOW

DWS-specific syntax:

• DISTRIBUTE BY {HASH|MODULO|REPLICATION|ROUNDROBIN}
• PARTITION BY {RANGE|LIST|INTERVAL}
• TO {NODE|GROUP}
• COMPRESS {YES|NO}
• TIMECAPSULE TABLE ... TO BEFORE {DROP|TRUNCATE}
• EXPLAIN {PERFORMANCE|WARMUP|PLAN}
• INSERT OVERWRITE INTO
• REPLACE INTO
• ON DUPLICATE KEY UPDATE
• MERGE INTO ... USING ... ON ... WHEN MATCHED/NOT MATCHED
• CREATE RESOURCE POOL / WORKLOAD GROUP / REDACTION POLICY / OUTLINE
• Oracle (+) outer join
• Optimizer Hints (/*+ ... */)

Step 4: Syntax Check

Based on tokenization and parsing results, execute syntax check rules.

Syntax Check Rules (19 rules):

Step 5: Specification Check

Based on AST and Token stream, execute specification check rules. Rules are derived from gram.y grammar definitions and DWS development design specification.

Specification Check Rules (40 rules):

Step 6: Generate Report

Use the check engine to generate a Markdown format report:

bashCopy code
python ~/.cac/skills/huawei-cloud-dws-sql-check/scripts/dws_sql_checker.py "<sql_text>" all

Report format:

markdownCopy code
# DWS SQL Check Report

**Check Time**: 2026-06-18T10:00:00
**Statement Type**: SELECT
**Check Mode**: all

## Summary

| Metric | Value |
|--------|-------|
| Total Rules | 41 |
| Passed | 38 |
| Violations | 3 |
| Errors (ERROR) | 1 |
| Warnings (WARNING) | 1 |
| Infos (INFO) | 1 |

## Syntax Check

### [X] SYN003: Syntax Structure Error
- **Level**: ERROR
- **Position**: Line 1, Column 15
- **Description**: Missing FROM clause
- **Fix Suggestion**: Add FROM table_name

## Specification Check

### [!] SPEC003: SELECT * Prohibited
- **Level**: WARNING
- **Position**: Line 1, Column 8
- **Description**: Query uses SELECT *, should specify explicit column list
- **Fix Suggestion**: Replace SELECT * with specific column list

Parameters

Output Format

The check report is output in Markdown format, containing:

• Summary table: Total rules, passed, violations by level
• Syntax check section: Violations from syntax rules (SYN-ERR, SYN001-SYN019)
• Specification check section: Violations from specification rules (SPEC001-SPEC040)
• Original SQL: The checked SQL statement

Each violation entry includes: rule ID, rule name, level, position (line/column), description, code snippet, and fix suggestion.

Quick Check Command

For simple SQL checks, run directly:

bashCopy code
python ~/.cac/skills/huawei-cloud-dws-sql-check/scripts/dws_sql_checker.py "<sql_text>" [syntax|spec|all]

Output is in JSON format. For Markdown format report, call in Python:

pythonCopy code
from dws_sql_checker import check_sql_markdown
report = check_sql_markdown("SELECT * FROM t1", "all")
print(report)

Best Practices

1. Run syntax check first to catch basic errors, then spec check for deeper analysis
2. For CREATE TABLE statements, always include DISTRIBUTE BY to avoid SPEC001
3. Use all mode for comprehensive checking
4. Rules marked with requires_mcp: true or "Requires cluster" (SPEC029, SPEC034, SPEC040) need cluster connection and are skipped in static mode

References

Notes

1. Syntax and specification checks do not require cluster connection, can run offline
2. Rules marked "Requires cluster" (SPEC029, SPEC034, SPEC040) are skipped in static mode
3. Performance rules (PERF001-PERF011) are defined in rules/perf_rules.yaml but require cluster connection for execution
4. DWS-specific syntax checking (DISTRIBUTE BY, PARTITION BY, MERGE, etc.) is based on gram.y grammar definitions
5. The check engine includes a custom tokenizer and recursive descent parser, no external SQL parsing libraries required