How to Fix "max memory exceeded" in Redshift

Galaxy Glossary

How can I stop Redshift from throwing "max memory exceeded"?

The error appears when a query uses more memory than the slot(s) assigned by your Redshift WLM queue.

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Description

Example H2

Example H3

Why does Redshift show “max memory exceeded”?

Redshift allocates a fixed memory slice to every query slot. When the query’s hash or sort operations need more RAM than that slice, the leader aborts the statement and returns the error.

How do I know which part of my query is leaking memory?

Run EXPLAIN or SVL_QUERY_SUMMARY to see steps with high workmem. Hash joins or sorts on large, unsorted data usually cause the spike.

Can I increase the memory available to a single query?

Yes.Either assign the query to a WLM queue with a larger memory_percent_to_use or temporarily raise wlm_query_slot_count in your session.

Example 1 – use more slots

set wlm_query_slot_count = 3; triples the memory slice, letting the query use RAM from three slots in that queue.

What query rewrites avoid the error?

Replace large hash joins with JOINs on dist-key columns, filter early with WHERE, and order by indexed columns to skip explicit sorts.

How do I tune WLM queues safely?

Create a separate queue for ETL or ad-hoc analytics, set concurrency to 1–3, and give it 70–90 % of memory.Keep short BI queries in a high-concurrency, low-memory queue.

Best practices to prevent “max memory exceeded”

1. Analyze tables after large loads.
2. Vacuum regularly to sort and encode data.
3. Keep DIST style keys aligned.
4. Monitor STL_WLM_QUERY for recurring memory spills.

Full troubleshooting workflow

1. Identify failing query.
2. Check STL_ALERT_EVENT_LOG for memory alerts.
3. Review plan.
4. Rewrite or raise slots.
5.Long-term: redesign table distribution or WLM.

When should I resize the cluster instead?

If optimized queries still exceed memory and lowering concurrency slows workloads, scaling node count or class is the sustainable fix.

Why How to Fix "max memory exceeded" in Redshift is important

How to Fix "max memory exceeded" in Redshift Example Usage


-- Allocate more memory then re-run the query
SET wlm_query_slot_count = 3;

SELECT c.id, SUM(oi.quantity * p.price) AS lifetime_value
FROM Customers c
JOIN Orders o          ON o.customer_id = c.id
JOIN OrderItems oi     ON oi.order_id   = o.id
JOIN Products p        ON p.id          = oi.product_id
GROUP BY c.id
ORDER BY lifetime_value DESC;

How to Fix "max memory exceeded" in Redshift Syntax


-- Increase slots for current session
SET wlm_query_slot_count = <integer>;  -- 1-5 recommended

-- Example: allocate 3 slots before running a heavy join
SET wlm_query_slot_count = 3;

-- Adjust WLM queue (requires cluster reboot)
-- In AWS console or via JSON, set for the target queue:
{
  "concurrency": 3,
  "memory_percent_to_use": 80,
  "name": "etl_queue"
}

-- Basic ecommerce example causing the error
SELECT c.id, SUM(oi.quantity * p.price) AS lifetime_value
FROM Customers c
JOIN Orders o          ON o.customer_id = c.id
JOIN OrderItems oi     ON oi.order_id   = o.id
JOIN Products p        ON p.id          = oi.product_id
GROUP BY c.id
ORDER BY lifetime_value DESC;

Common Mistakes

Blindly raising wlm_query_slot_count to high values. This starves other queries, causing queue backups. Instead, test with 2–3 slots and monitor.
Adding SORT or DISTINCT to force the engine to use more RAM. Rewrite joins or use proper DIST/KEYs instead of memory-intensive operations.

Frequently Asked Questions (FAQs)

Does increasing slots slow other queries?

Yes, because fewer slots remain for parallel statements. Schedule heavy queries during off-peak hours or isolate them in a low-concurrency queue.

Can I see memory usage in real time?

Use Amazon Redshift Console metrics or query STL_WLM_QUERY and SVL_QUERY_REPORT to view max_workmem after the query completes.

Is the error related to disk space?

No. The message refers to RAM allocated to the query slot, not disk. However, insufficient disk can surface as "disk full" errors, not "max memory exceeded".