Memory Errors
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ERROR 1712: Not enough memory available to complete the current request. The request was not processed.
For potential causes and solutions, see Identifying and Reducing Memory Usage.
ERROR: 1720 - Memory usage by SingleStore for tables (XXXXX MB) has reached the value of maximum_ table_ memory
global variable (YYYYY MB). This query cannot be executed.
maximum_global variable (YYYYY MB).table_ memory
For potential causes and solutions, see Identifying and Reducing Memory Usage.
ERROR 2373: Code generation for new statements is disabled because the total number of license units of capacity used on all leaf nodes is XX, which is above the limit of 4 for the SingleStore free license.
Issue
This error is displayed when the limit imposed by the free license has been exceeded.
-
For a v1 license (now deprecated), this limit is 4 license units (8 vCPU / 32GB)
-
For a v2 license, this limit is 4 license units (8 vCPUs / 64GB / 1TB)
Refer to General for more information.
To understand how to handle capacity limit errors with these new licenses, see the Capacity Limit Errors topic.
Solutions
There are three potential solutions depending on what your needs are:
-
If you need a cluster with more than four license units, you will need additional/paid licenses (Standard or Enterprise).
Sign up for a free 30-day trial and create an Enterprise License trial key before deploying a larger cluster. -
Redeploy the cluster on a smaller set of machines that will keep you under the four-unit limit.
-
Deploy your cluster manually using the Comprehensive Install Guide, and reduce the memory limits on all nodes with the instructions below.
NUMA CPUs and Multiple Nodes per Host
If you have NUMA-capable CPUs on your host machine, and wish to run more than one node per host machine, then your maximum_ value would have to be reduced according to the count of nodes per host.
Memory allocation is calculated as follows:
-
One node, default settings: maximum_
memory = 90% of physical memory -
Two nodes, set maximum_
memory = (90% of physical memory) / 2 per node -
Four nodes, set maximum_
memory = (90% of physical memory) / 4 per node
ERROR 2374: Leaf or aggregator node could not be added because you are using the SingleStore free license which has a limit of 4 license units and after adding the node you would be using XX license units.
Issue
This error is displayed when the limit imposed by the free license has been exceeded.
-
For a v1 license (now deprecated), this limit is 4 license units (8 vCPU / 32GB)
-
For a v2 license, this limit is 4 license units (8 vCPUs / 64GB / 1TB)
Refer to General for more information.
To understand how to handle capacity limit errors with these new licenses, see the Capacity Limit Errors topic.
Solutions
There are three potential solutions depending on what your needs are:
-
If you need a cluster with more than four license units, you will need additional/paid licenses (Standard or Enterprise).
Sign up for a free 30-day trial and create an Enterprise License trial key before deploying a larger cluster. -
Redeploy the cluster on a smaller set of machines that will keep you under the four-unit limit.
-
Deploy your cluster manually using the Comprehensive Install Guide, and reduce the memory limits on all nodes with the instructions below.
NUMA CPUs and Multiple Nodes per Host
If you have NUMA-capable CPUs on your host machine, and wish to run more than one node per host machine, then your maximum_ value would have to be reduced according to the count of nodes per host.
Memory allocation is calculated as follows:
-
One node, default settings: maximum_
memory = 90% of physical memory -
Two nodes, set maximum_
memory = (90% of physical memory) / 2 per node -
Four nodes, set maximum_
memory = (90% of physical memory) / 4 per node
ERROR: "Nonfatal buffer manager memory allocation failure. The maximum_ memory parameter (XXXXX MB) has been reached.
For potential causes and solutions, see Identifying and Reducing Memory Usage.
Failed to allocate XXXXX bytes of memory from the operating system (Error 12: Cannot allocate memory). This is usually due to a misconfigured operating system or virtualization technology.
This error message indicates a host level misconfiguration in how the kernel is allowed to allocate memory.
-
low
vm.max_ map_ count -
high
vm.min_ free_ kbytes -
low
vm.swappiness -
vm.overcommit_ memory -
low
vm.overcommit_ ratio -
inadequate Swap space
For more information about the recommended configuration of these settings, see System Requirements and Recommendations
Last modified: February 12, 2025