CREATE COMPUTE POOL¶

Syntax¶

CREATE COMPUTE POOL [ IF NOT EXISTS ] <name>
  [ FOR APPLICATION <app-name> ]
  MIN_NODES = <num>
  MAX_NODES = <num>
  INSTANCE_FAMILY = <instance_family_name>
  [ AUTO_RESUME = { TRUE | FALSE } ]
  [ INITIALLY_SUSPENDED = { TRUE | FALSE } ]
  [ AUTO_SUSPEND_SECS = <num>  ]
  [ COMMENT = '<string_literal>' ]

Required parameters¶

name

String that specifies the identifier (that is, the name) for the compute pool; it must be unique for your account. Quoted names for special characters or case-sensitive names are not supported.

MIN_NODES = num

Specifies the minimum number of nodes for the compute pool. This value must be greater than 0. For more information, see Creating a compute pool.

MAX_NODES = num

Specifies the maximum number of nodes for the compute pool.

INSTANCE_FAMILY = instance_family_name

Identifies the type of machine you want to provision for the nodes in the compute pool. The machine type determines the amount of compute resources in the compute pool and, therefore, the number of credits consumed while the compute pool is running.

The INSTANCE_FAMILY values in the following table can be grouped into 3 categories:

• Generic instance types: Provide a balance of CPU, memory and disk. This does not include GPU. These instance family names start with “CPU”.

• High memory instance types: Similar to generic instance types, but these provide more memory. These instance family names start with “HighMemory”.

• Instance types with GPU attached: These instance family names start with “GPU”.

INSTANCE_FAMILY, Snowflake Service Consumption Table Mapping	vCPU	Memory (GiB)	Storage (GiB)	Bandwidth limit (Gbps)	GPU	GPU Memory per GPU (GiB)	Node limit	Description
CPU_X64_XS, . CPU | XS	1	6	100	Up to 12.5	n/a	n/a	50	Smallest instance available for Snowpark Containers. Ideal for cost-savings and getting started.
CPU_X64_S, . CPU | S	3	13	100	Up to 12.5	n/a	n/a	50	Ideal for hosting multiple services/jobs while saving cost.
CPU_X64_M, . CPU | M	6	28	100	Up to 12.5	n/a	n/a	50	Ideal for having a full stack application or multiple services
CPU_X64_L, . CPU | L	28	116	100	12.5	n/a	n/a	50	For applications which need an unusually large number of CPUs, memory and Storage.
HIGHMEM_X64_S, . High-Memory CPU | S	6	58	100	AWS: Up to 12.5, Azure: 8	n/a	n/a	50	For memory intensive applications.
HIGHMEM_X64_M, . High-Memory CPU | M . (AWS only)	28	240	100	12.5	n/a	n/a	50	For hosting multiple memory intensive applications on a single machine.
HIGHMEM_X64_M, . High-Memory CPU | M . (Azure only)	28	244	100	16	n/a	n/a	50	For hosting multiple memory intensive applications on a single machine.
HIGHMEM_X64_L, . High-Memory CPU | L . (AWS only)	124	984	100	50	n/a	n/a	20	Largest AWS high-memory machine available for processing large in-memory data.
HIGHMEM_X64_SL, . High-Memory CPU | L . (Azure only)	92	654	100	32	n/a	n/a	20	Largest Azure high-memory machine available for processing large in-memory data.
GPU_NV_S, . GPU | S . (AWS only, except Paris and Osaka regions)	6	27	100	Up to 10	1 NVIDIA A10G	24	10	Our smallest NVIDIA GPU size available for Snowpark Containers to get started.
GPU_NV_M, . GPU | M . (AWS only, except not Paris and Osaka regions)	44	178	100	40	4 NVIDIA A10G	24	10	Optimized for intensive GPU usage scenarios like Computer Vision or LLMs/VLMs.
GPU_NV_L, . GPU | L . (AWS only, available only in AWS US West and US East regions by request; limited availability might be possible in other regions upon request)	92	1112	100	400	8 NVIDIA A100	40	On request	Largest GPU instance for specialized and advanced GPU cases like LLMs and Clustering, etc.
GPU_NV_XS, . GPU | XS . (Azure only, except not Switzerland North and UAE North regions)	3	26	100	8	1 NVIDIA T4	16	10	Our smallest Azure NVIDIA GPU size available for Snowpark Containers to get started.
GPU_NV_SM, . GPU | SM . (Azure only, except not Central US region)	32	424	100	40	1 NVIDIA A10	24	10	A smaller Azure NVIDIA GPU size available for Snowpark Containers to get started.
GPU_NV_2M, . GPU | 2M . (Azure only, except not Central US region)	68	858	100	80	2 NVIDIA A10	24	5	Optimized for intensive GPU usage scenarios like Computer Vision or LLMs/VLMs.
GPU_NV_3M, . GPU | 3M . (Azure only, except not North Europe and UAE North regions)	44	424	100	40	2 NVIDIA A100	80	On request	Optimized for memory-intensive GPU usage scenarios like Computer Vision or LLMs/VLMs.
GPU_NV_SL, . GPU | SL . (Azure only, except not North Europe and UAE North regions)	92	858	100	80	4 NVIDIA A100	80	On request	Largest GPU instance for specialized and advanced GPU cases like LLMs and Clustering, etc.

Note the following:

• The consumption table link in the first column heading provides information about the credit consumption rate for the specific INSTANCE_FAMILY.

• The Node limit column indicates the maximum number of nodes a Snowflake account can provision for the specific INSTANCE_FAMILY type. Contact your account representative to increase the limit.

Optional parameters¶

FOR APPLICATION app_name

Specifies the Snowflake Native App name. If specified, the compute pool can only be used by the native app. The SHOW COMPUTE POOLS command output includes the is_exclusive and application columns to indicate whether the compute pool is created exclusively for an app and provides the app name.

AUTO_RESUME = { TRUE | FALSE }

Specifies whether to automatically resume a compute pool when a service or job is submitted to it.

• If AUTO_RESUME is FALSE, you need to explicitly resume the compute pool (using ALTER COMPUTE POOL RESUME) before you can start a service or job on the compute pool.

• If AUTO_RESUME is TRUE, if you start a new service on a suspended compute pool, Snowflake starts the compute pool. Similarly, when you use a service either by invoking a service function or accessing ingress (see Using a service), Snowflake starts the previously suspended compute pool and resumes the service.

Default: TRUE

INITIALLY_SUSPENDED = { TRUE | FALSE }

Specifies whether the compute pool is created initially in the suspended state. If you create a compute pool with INITIALLY_SUSPENDED set to TRUE, Snowflake will not provision any nodes requested for the compute pool at the compute pool creation time. You can start the suspended compute pool using ALTER COMPUTE POOL … RESUME.

Default: FALSE

AUTO_SUSPEND_SECS = num

Number of seconds of inactivity after which you want Snowflake to automatically suspend the compute pool. An inactive compute pool is one in which no services or jobs are currently active on any node in the pool. If auto_suspend_secs is set to 0, Snowflake does not suspend the compute pool automatically.

Default: 3600 seconds

COMMENT = 'string_literal'

Specifies a comment for the compute pool.

Default: No value

Access control requirements¶

A role used to execute this SQL command must have the following privileges at a minimum:

For instructions on creating a custom role with a specified set of privileges, see Creating custom roles.

For general information about roles and privilege grants for performing SQL actions on securable objects, see Overview of Access Control.

Usage notes¶

• Regarding metadata:

  Attention

  Customers should ensure that no personal data (other than for a User object), sensitive data, export-controlled data, or other regulated data is entered as metadata when using the Snowflake service. For more information, see Metadata fields in Snowflake.

Examples¶

Create a 1-node compute pool. This example command specifies the minimum required parameters:

CREATE COMPUTE POOL tutorial_compute_pool
  MIN_NODES = 1
  MAX_NODES = 1
  INSTANCE_FAMILY = CPU_X64_XS;

The following command specifies the optional AUTO_RESUME parameter:

CREATE COMPUTE POOL tutorial_compute_pool
  MIN_NODES = 1
  MAX_NODES = 1
  INSTANCE_FAMILY = CPU_X64_XS
  AUTO_RESUME = FALSE;