CreateSessionRequest
¶
Source code in docs_src/capo_glue/types/create_session_request.py
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.
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.
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.1Xworker 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.2Xworker 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.4Xworker 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.8Xworker 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 theG.4Xworker type. -
For the
Z.2Xworker 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.