R2 SQL Gotchas
Limitations, troubleshooting, and common pitfalls for R2 SQL.
Overview
R2 SQL Gotchas
Limitations, troubleshooting, and common pitfalls for R2 SQL.
Critical Limitations
No Workers Binding
Cannot call R2 SQL from Workers/Pages code - no binding exists.
// ❌ This doesn't exist
async fetch(request, env) {
const result = await env.R2_SQL.query("SELECT * FROM table"); // Not possible
return Response.json(result);
}
};
Solutions:
- HTTP API from external systems (not Workers)
- PyIceberg/Spark via r2-data-catalog REST API
- For Workers, use D1 or external databases
ORDER BY Limitations
Can only order by:
- Partition key columns - Always supported
- Aggregation functions - Supported via shuffle strategy
Cannot order by regular non-partition columns.
-- ✅ Valid: ORDER BY partition key
SELECT * FROM logs.requests ORDER BY timestamp DESC LIMIT 100;
-- ✅ Valid: ORDER BY aggregation
SELECT region, SUM(amount) FROM sales.transactions
GROUP BY region ORDER BY SUM(amount) DESC;
-- ❌ Invalid: ORDER BY non-partition column
SELECT * FROM logs.requests ORDER BY user_id;
-- ❌ Invalid: ORDER BY alias (must repeat function)
SELECT region, SUM(amount) as total FROM sales.transactions
GROUP BY region ORDER BY total; -- Use ORDER BY SUM(amount)
Check partition spec: DESCRIBE namespace.table_name
SQL Feature Limitations
| Feature | Supported | Notes |
|---|---|---|
| SELECT, WHERE, GROUP BY, HAVING | ✅ | Standard support |
| COUNT, SUM, AVG, MIN, MAX | ✅ | Standard aggregations |
| ORDER BY partition/aggregation | ✅ | See above |
| LIMIT | ✅ | Max 10,000 |
| Column aliases | ❌ | No AS alias |
| Expressions in SELECT | ❌ | No col1 + col2 |
| ORDER BY non-partition | ❌ | Fails at runtime |
| JOINs, subqueries, CTEs | ❌ | Denormalize at write time |
| Window functions, UNION | ❌ | Use external engines |
| INSERT/UPDATE/DELETE | ❌ | Use PyIceberg/Pipelines |
| Nested columns, arrays, JSON | ❌ | Flatten at write time |
Workarounds:
- No JOINs: Denormalize data or use Spark/PyIceberg
- No subqueries: Split into multiple queries
- No aliases: Accept generated names, transform in app
Common Errors
"Column not found"
Cause: Typo, column doesn't exist, or case mismatch
Solution: DESCRIBE namespace.table_name to check schema
"Type mismatch"
-- ❌ Wrong types
WHERE status = '200' -- string instead of integer
WHERE timestamp > '2025-01-01' -- missing time/timezone
-- ✅ Correct types
WHERE status = 200
WHERE timestamp > '2025-01-01T00:00:00Z'
"ORDER BY column not in partition key"
Cause: Ordering by non-partition column
Solution: Use partition key, aggregation, or remove ORDER BY. Check: DESCRIBE table
"Token authentication failed"
# Check/set token
echo $WRANGLER_R2_SQL_AUTH_TOKEN
# Or .env file
echo "WRANGLER_R2_SQL_AUTH_TOKEN=<your-token>" > .env
"Table not found"
-- Verify catalog and tables
SHOW DATABASES;
SHOW TABLES IN namespace_name;
Enable catalog: npx wrangler r2 bucket catalog enable <bucket>
"LIMIT exceeds maximum"
Max LIMIT is 10,000. For pagination, use WHERE filters with partition keys.
"No data returned" (unexpected)
Debug steps:
SELECT COUNT(*) FROM table- verify data exists- Remove WHERE filters incrementally
SELECT * FROM table LIMIT 10- inspect actual data/types
Performance Issues
Slow Queries
Causes: Too many partitions, large LIMIT, no filters, small files
-- ❌ Slow: No filters
SELECT * FROM logs.requests LIMIT 10000;
-- ✅ Fast: Filter on partition key
SELECT * FROM logs.requests
WHERE timestamp >= '2025-01-15T00:00:00Z' AND timestamp < '2025-01-16T00:00:00Z'
LIMIT 1000;
-- ✅ Faster: Multiple filters
SELECT * FROM logs.requests
WHERE timestamp >= '2025-01-15T00:00:00Z' AND status = 404 AND method = 'GET'
LIMIT 1000;
File optimization:
- Target Parquet size: 100-500MB compressed
- Pipelines roll interval: 300+ sec (prod), 10 sec (dev)
- Run compaction to merge small files
Query Timeout
Solution: Add restrictive WHERE filters, reduce time range, query smaller intervals
-- ❌ Times out: Year-long aggregation
SELECT status, COUNT(*) FROM logs.requests
WHERE timestamp >= '2024-01-01T00:00:00Z' GROUP BY status;
-- ✅ Faster: Month-long aggregation
SELECT status, COUNT(*) FROM logs.requests
WHERE timestamp >= '2025-01-01T00:00:00Z' AND timestamp < '2025-02-01T00:00:00Z'
GROUP BY status;
Best Practices
Partitioning
- Time-series: Partition by day/hour on timestamp
- Avoid: High-cardinality keys (user_id), >10,000 partitions
from pyiceberg.partitioning import PartitionSpec, PartitionField
from pyiceberg.transforms import DayTransform
PartitionSpec(PartitionField(source_id=1, field_id=1000, transform=DayTransform(), name="day"))
Query Writing
- Always use LIMIT for early termination
- Filter on partition keys first for pruning
- Combine filters with AND for more pruning
-- Good
WHERE timestamp >= '2025-01-15T00:00:00Z' AND status = 404 AND method = 'GET' LIMIT 100
Type Safety
- Quote strings:
'GET'notGET - RFC3339 timestamps:
'2025-01-01T00:00:00Z'not'2025-01-01' - ISO dates:
'2025-01-15'not'01/15/2025'
Data Organization
- Pipelines: Dev
roll_file_time: 10, Prodroll_file_time: 300+ - Compression: Use
zstd - Maintenance: Compaction for small files, expire old snapshots
Debugging Checklist
npx wrangler r2 bucket catalog enable <bucket>- Verify catalogecho $WRANGLER_R2_SQL_AUTH_TOKEN- Check tokenSHOW DATABASES- List namespacesSHOW TABLES IN namespace- List tablesDESCRIBE namespace.table- Check schemaSELECT COUNT(*) FROM namespace.table- Verify dataSELECT * FROM namespace.table LIMIT 10- Test simple query- Add filters incrementally
See Also
- api.md - SQL syntax
- patterns.md - Query optimization
- configuration.md - Setup
- Cloudflare R2 SQL Docs