> ## Documentation Index
> Fetch the complete documentation index at: https://docs.planasonix.com/llms.txt
> Use this file to discover all available pages before exploring further.

# SQL assistance

> Get AI-powered help writing and optimizing SQL queries.

SQL assistance helps you author queries inside Planasonix nodes—warehouse transforms, inline filters, and reverse ETL source SQL—without switching to a separate IDE. You stay inside the product while Copilot suggests syntax, patterns, and fixes.

## SQL generation

Select a SQL editor surface (for example, a transform or warehouse query node) and open **Ask Copilot**. Describe the result shape you need:

* Target columns and types
* Join keys across tables or stages
* Filters (`last 7 days`, `active customers only`)
* Dialect-specific functions (Snowflake, BigQuery, Redshift, etc.)

Copilot returns a draft query using the dialect detected from the connection. Replace table names with your actual schema objects and run **Preview** to validate row counts.

For **Custom SQL** nodes, Copilot generates **PostgreSQL-compatible** SQL that runs on the local DataFusion engine. Ask for common patterns like CTEs, window functions, deduplication, or pivoting via `CASE WHEN` and Copilot will use the right syntax.

<Tip>
  Name the warehouse dialect in your prompt when you use uncommon functions so the assistant picks the right built-ins. For Custom SQL nodes, standard PostgreSQL syntax is always used.
</Tip>

## Optimization suggestions

Ask Copilot to **optimize** a query you already wrote. Typical suggestions include:

* Pushing filters closer to scans
* Replacing correlated subqueries with joins or window functions where appropriate
* Pruning unused columns before expensive joins
* Adding clustering or partition predicates your tables support

Treat suggestions as hypotheses: measure with the warehouse query profile before accepting changes on heavy jobs.

<Tabs>
  <Tab title="Cost-focused">
    Request “lower bytes scanned” or “reduce spill to disk” when your profile shows large scans.
  </Tab>

  <Tab title="Latency-focused">
    Ask to “reduce latency for an interactive preview” when the query backs a dashboard or notebook.
  </Tab>

  <Tab title="Correctness-first">
    Say “do not change results” when you only want structural cleanup, not semantic changes.
  </Tab>
</Tabs>

## Error explanation

Paste compiler or runtime errors into chat (redact internal hostnames if policy requires). Copilot maps common messages to fixes:

* Type mismatches in `JOIN` or `UNION`
* Missing aliases in nested selects
* Invalid identifier quoting per dialect
* Permission errors surfaced as SQL exceptions

Cross-check explanations against your warehouse’s error reference; vendor messages evolve across versions.

<AccordionGroup>
  <Accordion title="Sample data">
    If you paste sample rows, mask direct identifiers. Prefer synthetic values that preserve shape but not real customer data.
  </Accordion>

  <Accordion title="Large scripts">
    For long scripts, point Copilot to the failing stanza only; smaller snippets get more accurate line-level guidance.
  </Accordion>
</AccordionGroup>

## Guardrails

You remain accountable for access controls and row-level security. Copilot does not bypass database grants. Generated SQL that references restricted objects still fails at execution until credentials allow access.

## Related topics

<CardGroup cols={2}>
  <Card title="AI Copilot overview" icon="sparkles" href="/ai-copilot/overview">
    Feature gating and API key models.
  </Card>

  <Card title="Pipelines" icon="diagram-project" href="/pipelines/overview">
    Where SQL nodes fit in the broader canvas.
  </Card>
</CardGroup>