What does an SQL validator check?
An SQL validator checks query syntax and structural correctness, including clause order, alias scope, JOIN structure, and aggregate rules. It helps catch errors before execution.
SQL validation examples
See How Easily AI Validates and Fixes SQL
Explore common SQL validation errors and review corrected queries before running them in production. Each example includes an invalid SQL query, a step-by-step explanation of the issues, and a corrected version.
- Compare invalid SQL and corrected SQL side by side
- Understand common SQL syntax and semantic validation errors for all common databases
- Use practical fixes for JOIN, aggregation, alias, and window-function mistakes
- Improve SQL quality before optimization, formatting, or deployment
What these SQL validator examples cover
This page focuses on SQL validation workflows for PostgreSQL queries: syntax checks, clause ordering, alias scope, JOIN correctness, aggregate rules, and window-function usage.
Use these examples to identify and fix invalid SQL quickly before handing queries off to your formatter, optimizer, or execution pipeline.
SQL validator examples
Review common SQL validation failures and corrected PostgreSQL queries. Each example shows the invalid input, precise issue list, and a fixed query.
Example 1: Missing FROM clause
Invalid SQL input
SELECT
user_id,
email
users
WHERE
is_active = true;Validator output
❌ Validation errors
SELECT
user_id,
email
-- 1. Missing FROM before the source table:
users
WHERE
is_active = true;💬 Explanation
| # | Explanation |
|---|---|
| 1 | The SELECT statement is missing FROM users. PostgreSQL requires FROM to define the row source before WHERE filters are applied. |
🚀 Corrected SQL query
SELECT
user_id,
email
FROM users
WHERE
is_active = true;Example 2: Trailing comma in SELECT list
Invalid SQL input
SELECT
product_name,
price,
category,
FROM
products;Validator output
❌ Validation errors
SELECT
product_name,
price,
-- 1. Trailing comma before FROM:
category,
FROM
products;💬 Explanation
| # | Explanation |
|---|---|
| 1 | PostgreSQL does not allow a trailing comma after the last projected column. Remove the comma after category before FROM. |
🚀 Corrected SQL query
SELECT
product_name,
price,
category
FROM
products;Example 3: Alias used in WHERE before SELECT evaluation
Invalid SQL input
SELECT
order_id,
(quantity * unit_price) AS total_value
FROM
order_details
WHERE
total_value > 1000;Validator output
❌ Validation errors
SELECT
order_id,
(quantity * unit_price) AS total_value
FROM
order_details
WHERE
-- 1. SELECT alias is not visible in WHERE:
total_value > 1000;💬 Explanation
| # | Explanation |
|---|---|
| 1 | WHERE runs before SELECT aliases are created, so total_value is undefined in this clause. Repeat the expression or use a subquery/CTE. |
🚀 Corrected SQL query
SELECT
order_id,
(quantity * unit_price) AS total_value
FROM
order_details
WHERE
(quantity * unit_price) > 1000;Example 4: JOIN missing target table and alias
Invalid SQL input
SELECT
c.customer_name,
o.order_date
FROM
customers c
JOIN
ON c.id = o.customer_id;Validator output
❌ Validation errors
SELECT
c.customer_name,
-- 1. Alias "o" is referenced but never defined:
o.order_date
FROM
customers c
-- 2. JOIN target table is missing:
JOIN
-- 3. ON cannot appear without a valid JOIN target:
ON c.id = o.customer_id;💬 Explanation
| # | Explanation |
|---|---|
| 1 | o.order_date references alias o, but no table was declared with alias o. |
| 2 | Every JOIN must specify a table or subquery to join. |
| 3 | The ON predicate is only valid after a complete JOIN target declaration, such as JOIN orders o. |
🚀 Corrected SQL query
SELECT
c.customer_name,
o.order_date
FROM
customers c
JOIN
orders o
ON c.id = o.customer_id;Example 5: Aggregation without GROUP BY
Invalid SQL input
SELECT
department,
AVG(salary)
FROM
employees
HAVING
department = 'Sales';Validator output
❌ Validation errors
SELECT
-- 1. Non-aggregated department is selected with AVG without grouping:
department,
AVG(salary)
FROM
employees
HAVING
-- 2. HAVING is used to filter detail rows instead of grouped results:
department = 'Sales';💬 Explanation
| # | Explanation |
|---|---|
| 1 | When aggregate functions are used, non-aggregated columns in SELECT must appear in GROUP BY. |
| 2 | Use WHERE for row-level filtering (pre-aggregation) and HAVING for aggregate/group-level filtering (post-aggregation). |
🚀 Corrected SQL query
SELECT
department,
AVG(salary) AS avg_salary
FROM
employees
WHERE
department = 'Sales'
GROUP BY
department;Example 6: Invalid WHERE inside window OVER clause
Invalid SQL input
SELECT
employee_name,
salary,
department,
SUM(salary) OVER (PARTITION BY department WHERE is_manager = false ORDER BY hire_date) AS running_total
FROM
employees;Validator output
❌ Validation errors
SELECT
employee_name,
salary,
department,
-- 1. OVER(...) does not allow WHERE:
SUM(salary) OVER (PARTITION BY department WHERE is_manager = false ORDER BY hire_date) AS running_total
FROM
employees;💬 Explanation
| # | Explanation |
|---|---|
| 1 | Window definitions only allow PARTITION BY, ORDER BY, and frame clauses. Put conditional logic in FILTER (WHERE ...) or a CASE expression. |
🚀 Corrected SQL query
SELECT
employee_name,
salary,
department,
SUM(salary) FILTER (WHERE NOT is_manager) OVER (
PARTITION BY department
ORDER BY hire_date
ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
) AS running_total
FROM
employees;Example 7: INSERT column/value count mismatch
Invalid SQL input
INSERT INTO users (
username,
email,
is_active
)
VALUES (
'alice',
'alice@example.com'
);Validator output
❌ Validation errors
INSERT INTO users (
username,
email,
is_active
)
VALUES (
-- 1. Only two values for three target columns:
'alice',
'alice@example.com'
);💬 Explanation
| # | Explanation |
|---|---|
| 1 | The INSERT target list has three columns, but VALUES provides only two entries. PostgreSQL raises a column/value count mismatch error. |
🚀 Corrected SQL query
INSERT INTO users (
username,
email,
is_active
)
VALUES (
'alice',
'alice@example.com',
true
);Example 8: CTE referenced without join target
Invalid SQL input
WITH monthly_revenue AS (
SELECT
date_trunc('month', order_date)::date AS sales_month,
SUM(total_amount) AS revenue
FROM orders
GROUP BY 1
)
SELECT
sales_month,
revenue,
region_name
FROM
monthly_revenue
WHERE
region_name = 'North America';Validator output
❌ Validation errors
WITH monthly_revenue AS (
SELECT
date_trunc('month', order_date)::date AS sales_month,
SUM(total_amount) AS revenue
FROM orders
GROUP BY 1
)
SELECT
sales_month,
revenue,
-- 1. region_name is not produced by monthly_revenue:
region_name
FROM
monthly_revenue
WHERE
-- 2. region_name filter references an undefined column:
region_name = 'North America';💬 Explanation
| # | Explanation |
|---|---|
| 1 | The CTE only returns sales_month and revenue; region_name is not part of its schema. |
| 2 | Filters can only reference columns available from the current FROM scope. Add a join to a source that contains region_name. |
🚀 Corrected SQL query
WITH monthly_revenue AS (
SELECT
date_trunc('month', o.order_date)::date AS sales_month,
o.region_name,
SUM(o.total_amount) AS revenue
FROM orders o
GROUP BY
date_trunc('month', o.order_date)::date,
o.region_name
)
SELECT
sales_month,
revenue,
region_name
FROM
monthly_revenue
WHERE
region_name = 'North America';SQL validation checklist
Use this checklist before running SQL in staging or production to reduce preventable syntax and structure errors.
- Confirm every SELECT query has valid FROM sources and correctly declared table aliases.
- Check that SELECT aliases are only used where scope rules allow (not in WHERE).
- Validate aggregation rules: every non-aggregated selected column must be grouped.
- Review INSERT target columns and VALUES count/type compatibility before execution.
After validation, continue with the SQL formatter, SQL optimizer, and SQL explainer to improve readability, performance, and documentation quality.
SQL validator FAQ
Can SQL validation prevent runtime issues?
Validation catches many issues early, but not all runtime problems. You should still test against real schemas, permissions, and data distributions to validate behavior end-to-end.
Should I validate SQL before formatting or optimization?
Yes. Validate first so downstream formatting and optimization steps work on correct SQL. Then format for readability and optimize based on execution plans.