This PostgreSQL error occurs when invalid arguments are passed to the width_bucket() function, which is used for histogram calculations. The function requires numeric arguments with proper bounds and bucket counts that follow mathematical constraints.
The width_bucket() function in PostgreSQL is used to assign values to histogram buckets. It takes four arguments: the value to bucket, the lower bound, the upper bound, and the number of buckets. The error "2201G: invalid_argument_for_width_bucket_function" occurs when these arguments violate mathematical constraints. The function creates equal-width buckets between the lower and upper bounds. For example, width_bucket(15, 0, 100, 10) would return bucket 2 (since 15 falls in the second 10-unit bucket). The error typically happens when: 1. The lower bound equals or exceeds the upper bound 2. The number of buckets is zero or negative 3. The value is NaN (not a number) or infinite 4. The bounds themselves are invalid (NaN or infinite) This is a data exception error (SQLSTATE class 22) that prevents the function from performing meaningful calculations.
Examine the width_bucket() function call in your query. The function signature is:
width_bucket(operand numeric, low numeric, high numeric, count integer)Verify that:
1. low < high (lower bound must be less than upper bound)
2. count > 0 (number of buckets must be positive)
3. All arguments are valid numbers (not NaN or infinite)
Example of a problematic call:
-- This will fail: lower bound >= upper bound
SELECT width_bucket(50, 100, 0, 10);
-- This will fail: zero buckets
SELECT width_bucket(50, 0, 100, 0);Add checks to ensure your arguments are valid:
-- Check bounds before using width_bucket
SELECT
CASE
WHEN low >= high THEN NULL -- Handle invalid bounds
WHEN count <= 0 THEN NULL -- Handle invalid bucket count
ELSE width_bucket(value, low, high, count)
END as bucket
FROM your_table;
-- Or use a WHERE clause to filter invalid data
SELECT width_bucket(value, low, high, count)
FROM your_table
WHERE low < high AND count > 0;For dynamic bounds, add validation:
WITH validated_data AS (
SELECT
value,
LEAST(min_bound, max_bound) as low,
GREATEST(min_bound, max_bound) as high,
CASE WHEN bucket_count <= 0 THEN 1 ELSE bucket_count END as count
FROM source_data
)
SELECT width_bucket(value, low, high, count)
FROM validated_data;The width_bucket() function returns NULL if any argument is NULL. Add NULL handling:
-- Use COALESCE to provide defaults for NULL values
SELECT width_bucket(
COALESCE(value, 0),
COALESCE(low, 0),
COALESCE(high, 100),
COALESCE(count, 10)
)
FROM your_table;
-- Or filter out NULL rows
SELECT width_bucket(value, low, high, count)
FROM your_table
WHERE value IS NOT NULL
AND low IS NOT NULL
AND high IS NOT NULL
AND count IS NOT NULL;For NaN or infinite values, use additional checks:
SELECT width_bucket(value, low, high, count)
FROM your_table
WHERE
value = value -- NaN != NaN, so this filters NaN values
AND low = low
AND high = high
AND low < high
AND count > 0;Test your width_bucket() calls with hardcoded values to identify the issue:
-- Test with simple values first
SELECT width_bucket(50, 0, 100, 10); -- Should return 5
-- Then test with your actual bounds
SELECT
low,
high,
low < high as bounds_valid,
count,
count > 0 as count_valid
FROM your_table
WHERE your_conditions;
-- If bounds might be reversed, try this:
SELECT width_bucket(
value,
LEAST(low, high), -- Ensure low is smaller
GREATEST(low, high), -- Ensure high is larger
ABS(count) -- Ensure positive count
)
FROM your_table;If you're frequently getting this error, consider these alternatives:
1. Use a custom function with validation:
CREATE OR REPLACE FUNCTION safe_width_bucket(
operand numeric,
low numeric,
high numeric,
count integer
) RETURNS integer AS $$
BEGIN
IF low >= high OR count <= 0 THEN
RETURN NULL;
END IF;
RETURN width_bucket(operand, low, high, count);
END;
$$ LANGUAGE plpgsql;2. Use CASE expressions for simple bucketing:
-- Instead of width_bucket(), use CASE for fixed buckets
SELECT
CASE
WHEN value < 0 THEN 0
WHEN value < 10 THEN 1
WHEN value < 20 THEN 2
-- ... more buckets
ELSE 10
END as bucket
FROM your_table;3. Use ntile() for percentile-based buckets:
-- Create 10 equal-sized buckets based on data distribution
SELECT
value,
ntile(10) OVER (ORDER BY value) as percentile_bucket
FROM your_table;### Understanding width_bucket() Mathematics
The width_bucket() function divides the range [low, high] into "count" equal-width buckets. The buckets are numbered from 1 to count:
- Bucket 1: [low, low + width)
- Bucket 2: [low + width, low + 2*width)
- ...
- Bucket count: [low + (count-1)*width, high]
Where width = (high - low) / count
Values outside the range [low, high] get special bucket numbers:
- Values < low: bucket 0
- Values >= high: bucket count + 1
### Performance Considerations
1. Index usage: width_bucket() calculations can't use indexes on the operand column
2. Pre-calculation: For frequently used bounds, consider storing bucket numbers in a materialized view
3. Dynamic bounds: If bounds change frequently, consider using window functions instead:
-- Use percent_rank() for dynamic ranges
SELECT
value,
width_bucket(
percent_rank() OVER (ORDER BY value) * 100,
0, 100, 10
) as dynamic_bucket
FROM your_table;### Common Use Cases
1. Histograms for data visualization:
SELECT
width_bucket(salary, 30000, 150000, 10) as salary_bucket,
COUNT(*) as employee_count
FROM employees
GROUP BY 1
ORDER BY 1;2. Time-based bucketing:
SELECT
width_bucket(
EXTRACT(EPOCH FROM event_time - '2024-01-01'),
0, 31536000, 52 -- 52 weeks in a year
) as week_number,
COUNT(*) as events
FROM events
GROUP BY 1;### PostgreSQL Version Notes
- width_bucket() has been available since PostgreSQL 9.5
- The function works with numeric, double precision, and date/time types
- For timestamp bucketing, convert to epoch seconds first
- Consider using date_bin() in PostgreSQL 14+ for time-based bucketing
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