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CreateSessionRequest

Source code in docs_src/capo_glue/types/create_session_request.py
class CreateSessionRequest(TypedDict, closed=True):
    id: "capo_glue.types.name_string.NameString"
    """<p>The ID of the session request. </p>"""
    description: NotRequired["capo_glue.types.description_string.DescriptionString"]
    """<p>The description of the session. </p>"""
    role: "capo_glue.types.orchestration_role_arn.OrchestrationRoleArn"
    """<p>The IAM Role ARN </p>"""
    command: "capo_glue.types.session_command.SessionCommand"
    """<p>The <code>SessionCommand</code> that runs the job. </p>"""
    timeout: NotRequired["capo_glue.types.timeout.Timeout"]
    """<p> The number of minutes before session times out. Default for Spark ETL jobs is 48 hours (2880 minutes). Consult the documentation for other job types. </p>"""
    idle_timeout: NotRequired["capo_glue.types.timeout.Timeout"]
    """<p> The number of minutes when idle before session times out. Default for Spark ETL jobs is value of Timeout. Consult the documentation for other job types. </p>"""
    default_arguments: NotRequired[
        "capo_glue.types.orchestration_arguments_map.OrchestrationArgumentsMap"
    ]
    """<p>A map array of key-value pairs. Max is 75 pairs. </p>"""
    connections: NotRequired["capo_glue.types.connections_list.ConnectionsList"]
    """<p>The number of connections to use for the session. </p>"""
    max_capacity: NotRequired["capo_glue.types.nullable_double.NullableDouble"]
    """<p>The number of Glue data processing units (DPUs) that can be allocated when the job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB memory. </p>"""
    number_of_workers: NotRequired["capo_glue.types.nullable_integer.NullableInteger"]
    """<p>The number of workers of a defined <code>WorkerType</code> to use for the session. </p>"""
    worker_type: NotRequired["capo_glue.types.worker_type.WorkerType"]
    """<p>The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, or G.8X for Spark jobs. Accepts the value Z.2X for Ray notebooks.</p> <ul> <li> <p>For the <code>G.1X</code> worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 94GB disk, and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.</p> </li> <li> <p>For the <code>G.2X</code> worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 138GB disk, and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.</p> </li> <li> <p>For the <code>G.4X</code> worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk, and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).</p> </li> <li> <p>For the <code>G.8X</code> worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk, and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the <code>G.4X</code> worker type.</p> </li> <li> <p>For the <code>Z.2X</code> worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk, and provides up to 8 Ray workers based on the autoscaler.</p> </li> </ul>"""
    security_configuration: NotRequired["capo_glue.types.name_string.NameString"]
    """<p>The name of the SecurityConfiguration structure to be used with the session </p>"""
    glue_version: NotRequired["capo_glue.types.glue_version_string.GlueVersionString"]
    """<p>The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0. </p>"""
    tags: NotRequired["capo_glue.types.tags_map.TagsMap"]
    """<p>The map of key value pairs (tags) belonging to the session.</p>"""
    request_origin: NotRequired[
        "capo_glue.types.orchestration_name_string.OrchestrationNameString"
    ]
    """<p>The origin of the request. </p>"""
    session_type: NotRequired["capo_glue.types.session_type.SessionType"]
    """<p>The type of session to create.</p>"""

command instance-attribute

command: SessionCommand

The SessionCommand that runs the job.

connections instance-attribute

connections: NotRequired[ConnectionsList]

The number of connections to use for the session.

default_arguments instance-attribute

default_arguments: NotRequired[OrchestrationArgumentsMap]

A map array of key-value pairs. Max is 75 pairs.

description instance-attribute

description: NotRequired[DescriptionString]

The description of the session.

glue_version instance-attribute

glue_version: NotRequired[GlueVersionString]

The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0.

id instance-attribute

The ID of the session request.

idle_timeout instance-attribute

idle_timeout: NotRequired[Timeout]

The number of minutes when idle before session times out. Default for Spark ETL jobs is value of Timeout. Consult the documentation for other job types.

max_capacity instance-attribute

max_capacity: NotRequired[NullableDouble]

The number of Glue data processing units (DPUs) that can be allocated when the job runs. A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB memory.

number_of_workers instance-attribute

number_of_workers: NotRequired[NullableInteger]

The number of workers of a defined WorkerType to use for the session.

request_origin instance-attribute

request_origin: NotRequired[OrchestrationNameString]

The origin of the request.

role instance-attribute

The IAM Role ARN

security_configuration instance-attribute

security_configuration: NotRequired[NameString]

The name of the SecurityConfiguration structure to be used with the session

session_type instance-attribute

session_type: NotRequired[SessionType]

The type of session to create.

tags instance-attribute

tags: NotRequired[TagsMap]

The map of key value pairs (tags) belonging to the session.

timeout instance-attribute

timeout: NotRequired[Timeout]

The number of minutes before session times out. Default for Spark ETL jobs is 48 hours (2880 minutes). Consult the documentation for other job types.

worker_type instance-attribute

worker_type: NotRequired[WorkerType]

The type of predefined worker that is allocated when a job runs. Accepts a value of G.1X, G.2X, G.4X, or G.8X for Spark jobs. Accepts the value Z.2X for Ray notebooks.

  • For the G.1X worker type, each worker maps to 1 DPU (4 vCPUs, 16 GB of memory) with 94GB disk, and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.

  • For the G.2X worker type, each worker maps to 2 DPU (8 vCPUs, 32 GB of memory) with 138GB disk, and provides 1 executor per worker. We recommend this worker type for workloads such as data transforms, joins, and queries, to offers a scalable and cost effective way to run most jobs.

  • For the G.4X worker type, each worker maps to 4 DPU (16 vCPUs, 64 GB of memory) with 256GB disk, and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs in the following Amazon Web Services Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), and Europe (Stockholm).

  • For the G.8X worker type, each worker maps to 8 DPU (32 vCPUs, 128 GB of memory) with 512GB disk, and provides 1 executor per worker. We recommend this worker type for jobs whose workloads contain your most demanding transforms, aggregations, joins, and queries. This worker type is available only for Glue version 3.0 or later Spark ETL jobs, in the same Amazon Web Services Regions as supported for the G.4X worker type.

  • For the Z.2X worker type, each worker maps to 2 M-DPU (8vCPUs, 64 GB of memory) with 128 GB disk, and provides up to 8 Ray workers based on the autoscaler.