MySQL error 3015 ER_ENGINE_OUT_OF_MEMORY indicates the storage engine could not allocate the memory it needs to execute the current operation.
ER_ENGINE_OUT_OF_MEMORY occurs when a MySQL storage engine, usually InnoDB, runs out of available memory. Check buffer sizes, lower per-connection settings, kill heavy sessions, or add more RAM to resolve the error.
ER_ENGINE_OUT_OF_MEMORY
MySQL raises error 3015 ER_ENGINE_OUT_OF_MEMORY when the storage engine cannot obtain enough memory from the operating system to complete an operation. The message usually appears as "Out of memory in storage engine 'InnoDB'" or names another engine.
The error stops the current query, transaction, or DDL statement. Rapid resolution is vital because the problem can block writes, cause replication lag, and expose deeper configuration issues.
Insufficient RAM or swap leaves the storage engine without free pages to allocate. Large sorts, hash joins, or temporary tables exhaust memory quickly.
Misconfigured variables such as innodb_buffer_pool_size or tmp_table_size can consume most memory at startup or during peak load.
Memory leaks in user defined functions, plugins, or old engine versions steadily reduce free memory until allocations fail.
Heavy concurrency inflates per-connection buffers, pushing total usage beyond operating-system limits.
Verify the error in the MySQL error log and SHOW ENGINE INNODB STATUS. Identify which allocation failed and current free memory.
Lower per-connection variables like read_buffer_size, sort_buffer_size, and join_buffer_size. Apply changes dynamically or in my.cnf and restart.
Right-size global caches. Set innodb_buffer_pool_size to roughly 60-70 percent of RAM, not 90 percent.
Add physical RAM or enable swap to give the OS more headroom. Restart MySQL after hardware changes.
Terminate runaway sessions that hold large temporary tables. Enforce idle timeouts with wait_timeout.
Large ALTER TABLE commands can fail when the buffer pool is nearly full. Use ALGORITHM=INPLACE or online schema change tools to reduce memory impact.
Traffic bursts during maintenance reduce free memory. Limit max_connections and use connection pooling.
Reporting queries in BI tools create huge temporary tables. Rewrite the queries in Galaxy or add supporting indexes to avoid heavy sorts.
Baseline memory usage after every MySQL upgrade and adjust tuning scripts accordingly.
Monitor free memory, swap, and MySQL memory status with Prometheus or CloudWatch. Alert when free memory falls under 10 percent.
Use Galaxy's query profiler to spot expensive sorts and hash joins during development so they never reach production.
Error 1041 "Out of memory" occurs at the server layer, not the engine. Similar tuning steps apply but check OS ulimits too.
Error 1135 "Can't create a new thread" surfaces when mysqld hits thread limits rather than memory. Lower max_connections or raise thread_stack.
Error 1206 "Lock wait timeout exceeded" may appear after out-of-memory events because locked transactions cannot progress.
The server simply lacks enough memory to satisfy the storage engine's allocation request.
innodb_buffer_pool_size consumes most RAM, leaving little for other processes and per-connection buffers.
High values for read_buffer_size, sort_buffer_size, or join_buffer_size multiply under heavy concurrency and exhaust memory.
Faulty plugins, UDFs, or outdated engine versions leak memory over time until none remains.
Complex queries create in-memory temp tables larger than tmp_table_size or memory limits, triggering allocations that fail.
Server layer memory exhaustion, not storage engine.
Thread creation fails due to OS or MySQL limits rather than pure memory shortage.
Lock waits grow after memory errors stall transactions.
Sort buffer runs out of space during large ORDER BY operations.
No. Often the problem is misconfigured buffers or memory leaks. Check tuning before buying hardware.
Yes. Lower per-connection buffers, kill heavy sessions, or enable swap. A restart is only required after changing my.cnf or adding RAM.
InnoDB is most common, but any pluggable engine can report the error when its internal allocator fails.
Galaxy highlights queries that build large temp tables and encourages indexing or rewriting before they hit production.
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