#[non_exhaustive]pub struct CreateSessionInput {Show 15 fields
pub id: Option<String>,
pub description: Option<String>,
pub role: Option<String>,
pub command: Option<SessionCommand>,
pub timeout: Option<i32>,
pub idle_timeout: Option<i32>,
pub default_arguments: Option<HashMap<String, String>>,
pub connections: Option<ConnectionsList>,
pub max_capacity: Option<f64>,
pub number_of_workers: Option<i32>,
pub worker_type: Option<WorkerType>,
pub security_configuration: Option<String>,
pub glue_version: Option<String>,
pub tags: Option<HashMap<String, String>>,
pub request_origin: Option<String>,
}Expand description
Request to create a new session.
Fields (Non-exhaustive)§
This struct is marked as non-exhaustive
Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.id: Option<String>The ID of the session request.
description: Option<String>The description of the session.
role: Option<String>The IAM Role ARN
command: Option<SessionCommand>The SessionCommand that runs the job.
timeout: Option<i32>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.
idle_timeout: Option<i32>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.
default_arguments: Option<HashMap<String, String>>A map array of key-value pairs. Max is 75 pairs.
connections: Option<ConnectionsList>The number of connections to use for the session.
max_capacity: Option<f64>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: Option<i32>The number of workers of a defined WorkerType to use for the session.
worker_type: Option<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.
security_configuration: Option<String>The name of the SecurityConfiguration structure to be used with the session
glue_version: Option<String>The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0.
The map of key value pairs (tags) belonging to the session.
request_origin: Option<String>The origin of the request.
Implementations§
Source§impl CreateSessionInput
impl CreateSessionInput
Sourcepub fn description(&self) -> Option<&str>
pub fn description(&self) -> Option<&str>
The description of the session.
Sourcepub fn command(&self) -> Option<&SessionCommand>
pub fn command(&self) -> Option<&SessionCommand>
The SessionCommand that runs the job.
Sourcepub fn timeout(&self) -> Option<i32>
pub fn timeout(&self) -> Option<i32>
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.
Sourcepub fn idle_timeout(&self) -> Option<i32>
pub fn idle_timeout(&self) -> Option<i32>
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.
Sourcepub fn default_arguments(&self) -> Option<&HashMap<String, String>>
pub fn default_arguments(&self) -> Option<&HashMap<String, String>>
A map array of key-value pairs. Max is 75 pairs.
Sourcepub fn connections(&self) -> Option<&ConnectionsList>
pub fn connections(&self) -> Option<&ConnectionsList>
The number of connections to use for the session.
Sourcepub fn max_capacity(&self) -> Option<f64>
pub fn max_capacity(&self) -> Option<f64>
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.
Sourcepub fn number_of_workers(&self) -> Option<i32>
pub fn number_of_workers(&self) -> Option<i32>
The number of workers of a defined WorkerType to use for the session.
Sourcepub fn worker_type(&self) -> Option<&WorkerType>
pub fn worker_type(&self) -> Option<&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.
Sourcepub fn security_configuration(&self) -> Option<&str>
pub fn security_configuration(&self) -> Option<&str>
The name of the SecurityConfiguration structure to be used with the session
Sourcepub fn glue_version(&self) -> Option<&str>
pub fn glue_version(&self) -> Option<&str>
The Glue version determines the versions of Apache Spark and Python that Glue supports. The GlueVersion must be greater than 2.0.
The map of key value pairs (tags) belonging to the session.
Sourcepub fn request_origin(&self) -> Option<&str>
pub fn request_origin(&self) -> Option<&str>
The origin of the request.
Source§impl CreateSessionInput
impl CreateSessionInput
Sourcepub fn builder() -> CreateSessionInputBuilder
pub fn builder() -> CreateSessionInputBuilder
Creates a new builder-style object to manufacture CreateSessionInput.
Trait Implementations§
Source§impl Clone for CreateSessionInput
impl Clone for CreateSessionInput
Source§fn clone(&self) -> CreateSessionInput
fn clone(&self) -> CreateSessionInput
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl Debug for CreateSessionInput
impl Debug for CreateSessionInput
Source§impl PartialEq for CreateSessionInput
impl PartialEq for CreateSessionInput
impl StructuralPartialEq for CreateSessionInput
Auto Trait Implementations§
impl Freeze for CreateSessionInput
impl RefUnwindSafe for CreateSessionInput
impl Send for CreateSessionInput
impl Sync for CreateSessionInput
impl Unpin for CreateSessionInput
impl UnwindSafe for CreateSessionInput
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