/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include Request to create a new session.See Also:
AWS
* API Reference
The ID of the session request.
*/ inline const Aws::String& GetId() const{ return m_id; } /** *The ID of the session request.
*/ inline bool IdHasBeenSet() const { return m_idHasBeenSet; } /** *The ID of the session request.
*/ inline void SetId(const Aws::String& value) { m_idHasBeenSet = true; m_id = value; } /** *The ID of the session request.
*/ inline void SetId(Aws::String&& value) { m_idHasBeenSet = true; m_id = std::move(value); } /** *The ID of the session request.
*/ inline void SetId(const char* value) { m_idHasBeenSet = true; m_id.assign(value); } /** *The ID of the session request.
*/ inline CreateSessionRequest& WithId(const Aws::String& value) { SetId(value); return *this;} /** *The ID of the session request.
*/ inline CreateSessionRequest& WithId(Aws::String&& value) { SetId(std::move(value)); return *this;} /** *The ID of the session request.
*/ inline CreateSessionRequest& WithId(const char* value) { SetId(value); return *this;} /** *The description of the session.
*/ inline const Aws::String& GetDescription() const{ return m_description; } /** *The description of the session.
*/ inline bool DescriptionHasBeenSet() const { return m_descriptionHasBeenSet; } /** *The description of the session.
*/ inline void SetDescription(const Aws::String& value) { m_descriptionHasBeenSet = true; m_description = value; } /** *The description of the session.
*/ inline void SetDescription(Aws::String&& value) { m_descriptionHasBeenSet = true; m_description = std::move(value); } /** *The description of the session.
*/ inline void SetDescription(const char* value) { m_descriptionHasBeenSet = true; m_description.assign(value); } /** *The description of the session.
*/ inline CreateSessionRequest& WithDescription(const Aws::String& value) { SetDescription(value); return *this;} /** *The description of the session.
*/ inline CreateSessionRequest& WithDescription(Aws::String&& value) { SetDescription(std::move(value)); return *this;} /** *The description of the session.
*/ inline CreateSessionRequest& WithDescription(const char* value) { SetDescription(value); return *this;} /** *The IAM Role ARN
*/ inline const Aws::String& GetRole() const{ return m_role; } /** *The IAM Role ARN
*/ inline bool RoleHasBeenSet() const { return m_roleHasBeenSet; } /** *The IAM Role ARN
*/ inline void SetRole(const Aws::String& value) { m_roleHasBeenSet = true; m_role = value; } /** *The IAM Role ARN
*/ inline void SetRole(Aws::String&& value) { m_roleHasBeenSet = true; m_role = std::move(value); } /** *The IAM Role ARN
*/ inline void SetRole(const char* value) { m_roleHasBeenSet = true; m_role.assign(value); } /** *The IAM Role ARN
*/ inline CreateSessionRequest& WithRole(const Aws::String& value) { SetRole(value); return *this;} /** *The IAM Role ARN
*/ inline CreateSessionRequest& WithRole(Aws::String&& value) { SetRole(std::move(value)); return *this;} /** *The IAM Role ARN
*/ inline CreateSessionRequest& WithRole(const char* value) { SetRole(value); return *this;} /** *The SessionCommand
that runs the job.
The SessionCommand
that runs the job.
The SessionCommand
that runs the job.
The SessionCommand
that runs the job.
The SessionCommand
that runs the job.
The SessionCommand
that runs the job.
The number of minutes before session times out. Default for Spark ETL jobs * is 48 hours (2880 minutes), the maximum session lifetime for this job type. * Consult the documentation for other job types.
*/ inline int GetTimeout() const{ return m_timeout; } /** *The number of minutes before session times out. Default for Spark ETL jobs * is 48 hours (2880 minutes), the maximum session lifetime for this job type. * Consult the documentation for other job types.
*/ inline bool TimeoutHasBeenSet() const { return m_timeoutHasBeenSet; } /** *The number of minutes before session times out. Default for Spark ETL jobs * is 48 hours (2880 minutes), the maximum session lifetime for this job type. * Consult the documentation for other job types.
*/ inline void SetTimeout(int value) { m_timeoutHasBeenSet = true; m_timeout = value; } /** *The number of minutes before session times out. Default for Spark ETL jobs * is 48 hours (2880 minutes), the maximum session lifetime for this job type. * Consult the documentation for other job types.
*/ inline CreateSessionRequest& WithTimeout(int value) { SetTimeout(value); return *this;} /** *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. *
*/ inline int GetIdleTimeout() const{ return m_idleTimeout; } /** *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. *
*/ inline bool IdleTimeoutHasBeenSet() const { return m_idleTimeoutHasBeenSet; } /** *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. *
*/ inline void SetIdleTimeout(int value) { m_idleTimeoutHasBeenSet = true; m_idleTimeout = value; } /** *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. *
*/ inline CreateSessionRequest& WithIdleTimeout(int value) { SetIdleTimeout(value); return *this;} /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline const Aws::MapA map array of key-value pairs. Max is 75 pairs.
*/ inline bool DefaultArgumentsHasBeenSet() const { return m_defaultArgumentsHasBeenSet; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline void SetDefaultArguments(const Aws::MapA map array of key-value pairs. Max is 75 pairs.
*/ inline void SetDefaultArguments(Aws::MapA map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& WithDefaultArguments(const Aws::MapA map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& WithDefaultArguments(Aws::MapA map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(const Aws::String& key, const Aws::String& value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(key, value); return *this; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(Aws::String&& key, const Aws::String& value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(std::move(key), value); return *this; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(const Aws::String& key, Aws::String&& value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(key, std::move(value)); return *this; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(Aws::String&& key, Aws::String&& value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(std::move(key), std::move(value)); return *this; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(const char* key, Aws::String&& value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(key, std::move(value)); return *this; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(Aws::String&& key, const char* value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(std::move(key), value); return *this; } /** *A map array of key-value pairs. Max is 75 pairs.
*/ inline CreateSessionRequest& AddDefaultArguments(const char* key, const char* value) { m_defaultArgumentsHasBeenSet = true; m_defaultArguments.emplace(key, value); return *this; } /** *The number of connections to use for the session.
*/ inline const ConnectionsList& GetConnections() const{ return m_connections; } /** *The number of connections to use for the session.
*/ inline bool ConnectionsHasBeenSet() const { return m_connectionsHasBeenSet; } /** *The number of connections to use for the session.
*/ inline void SetConnections(const ConnectionsList& value) { m_connectionsHasBeenSet = true; m_connections = value; } /** *The number of connections to use for the session.
*/ inline void SetConnections(ConnectionsList&& value) { m_connectionsHasBeenSet = true; m_connections = std::move(value); } /** *The number of connections to use for the session.
*/ inline CreateSessionRequest& WithConnections(const ConnectionsList& value) { SetConnections(value); return *this;} /** *The number of connections to use for the session.
*/ inline CreateSessionRequest& WithConnections(ConnectionsList&& value) { SetConnections(std::move(value)); return *this;} /** *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.
*/ inline double GetMaxCapacity() const{ return m_maxCapacity; } /** *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.
*/ inline bool MaxCapacityHasBeenSet() const { return m_maxCapacityHasBeenSet; } /** *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.
*/ inline void SetMaxCapacity(double value) { m_maxCapacityHasBeenSet = true; m_maxCapacity = value; } /** *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.
*/ inline CreateSessionRequest& WithMaxCapacity(double value) { SetMaxCapacity(value); return *this;} /** *The number of workers of a defined WorkerType
to use for the
* session.
The number of workers of a defined WorkerType
to use for the
* session.
The number of workers of a defined WorkerType
to use for the
* session.
The number of workers of a defined WorkerType
to use for the
* session.
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 84GB disk (approximately
* 34GB free), 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 128GB disk (approximately 77GB free), 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 (approximately 235GB free),
* 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 (approximately 487GB free), 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 (approximately 120GB free), and provides up to
* 8 Ray workers based on the autoscaler.
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 84GB disk (approximately
* 34GB free), 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 128GB disk (approximately 77GB free), 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 (approximately 235GB free),
* 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 (approximately 487GB free), 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 (approximately 120GB free), and provides up to
* 8 Ray workers based on the autoscaler.
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 84GB disk (approximately
* 34GB free), 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 128GB disk (approximately 77GB free), 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 (approximately 235GB free),
* 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 (approximately 487GB free), 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 (approximately 120GB free), and provides up to
* 8 Ray workers based on the autoscaler.
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 84GB disk (approximately
* 34GB free), 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 128GB disk (approximately 77GB free), 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 (approximately 235GB free),
* 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 (approximately 487GB free), 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 (approximately 120GB free), and provides up to
* 8 Ray workers based on the autoscaler.
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 84GB disk (approximately
* 34GB free), 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 128GB disk (approximately 77GB free), 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 (approximately 235GB free),
* 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 (approximately 487GB free), 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 (approximately 120GB free), and provides up to
* 8 Ray workers based on the autoscaler.
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 84GB disk (approximately
* 34GB free), 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 128GB disk (approximately 77GB free), 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 (approximately 235GB free),
* 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 (approximately 487GB free), 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 (approximately 120GB free), and provides up to
* 8 Ray workers based on the autoscaler.
The name of the SecurityConfiguration structure to be used with the session *
*/ inline const Aws::String& GetSecurityConfiguration() const{ return m_securityConfiguration; } /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline bool SecurityConfigurationHasBeenSet() const { return m_securityConfigurationHasBeenSet; } /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline void SetSecurityConfiguration(const Aws::String& value) { m_securityConfigurationHasBeenSet = true; m_securityConfiguration = value; } /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline void SetSecurityConfiguration(Aws::String&& value) { m_securityConfigurationHasBeenSet = true; m_securityConfiguration = std::move(value); } /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline void SetSecurityConfiguration(const char* value) { m_securityConfigurationHasBeenSet = true; m_securityConfiguration.assign(value); } /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline CreateSessionRequest& WithSecurityConfiguration(const Aws::String& value) { SetSecurityConfiguration(value); return *this;} /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline CreateSessionRequest& WithSecurityConfiguration(Aws::String&& value) { SetSecurityConfiguration(std::move(value)); return *this;} /** *The name of the SecurityConfiguration structure to be used with the session *
*/ inline CreateSessionRequest& WithSecurityConfiguration(const char* value) { SetSecurityConfiguration(value); return *this;} /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline const Aws::String& GetGlueVersion() const{ return m_glueVersion; } /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline bool GlueVersionHasBeenSet() const { return m_glueVersionHasBeenSet; } /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline void SetGlueVersion(const Aws::String& value) { m_glueVersionHasBeenSet = true; m_glueVersion = value; } /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline void SetGlueVersion(Aws::String&& value) { m_glueVersionHasBeenSet = true; m_glueVersion = std::move(value); } /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline void SetGlueVersion(const char* value) { m_glueVersionHasBeenSet = true; m_glueVersion.assign(value); } /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline CreateSessionRequest& WithGlueVersion(const Aws::String& value) { SetGlueVersion(value); return *this;} /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline CreateSessionRequest& WithGlueVersion(Aws::String&& value) { SetGlueVersion(std::move(value)); return *this;} /** *The Glue version determines the versions of Apache Spark and Python that Glue * supports. The GlueVersion must be greater than 2.0.
*/ inline CreateSessionRequest& WithGlueVersion(const char* value) { SetGlueVersion(value); return *this;} /** *The map of key value pairs (tags) belonging to the session.
*/ inline const Aws::MapThe map of key value pairs (tags) belonging to the session.
*/ inline bool TagsHasBeenSet() const { return m_tagsHasBeenSet; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline void SetTags(const Aws::MapThe map of key value pairs (tags) belonging to the session.
*/ inline void SetTags(Aws::MapThe map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& WithTags(const Aws::MapThe map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& WithTags(Aws::MapThe map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(const Aws::String& key, const Aws::String& value) { m_tagsHasBeenSet = true; m_tags.emplace(key, value); return *this; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(Aws::String&& key, const Aws::String& value) { m_tagsHasBeenSet = true; m_tags.emplace(std::move(key), value); return *this; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(const Aws::String& key, Aws::String&& value) { m_tagsHasBeenSet = true; m_tags.emplace(key, std::move(value)); return *this; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(Aws::String&& key, Aws::String&& value) { m_tagsHasBeenSet = true; m_tags.emplace(std::move(key), std::move(value)); return *this; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(const char* key, Aws::String&& value) { m_tagsHasBeenSet = true; m_tags.emplace(key, std::move(value)); return *this; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(Aws::String&& key, const char* value) { m_tagsHasBeenSet = true; m_tags.emplace(std::move(key), value); return *this; } /** *The map of key value pairs (tags) belonging to the session.
*/ inline CreateSessionRequest& AddTags(const char* key, const char* value) { m_tagsHasBeenSet = true; m_tags.emplace(key, value); return *this; } /** *The origin of the request.
*/ inline const Aws::String& GetRequestOrigin() const{ return m_requestOrigin; } /** *The origin of the request.
*/ inline bool RequestOriginHasBeenSet() const { return m_requestOriginHasBeenSet; } /** *The origin of the request.
*/ inline void SetRequestOrigin(const Aws::String& value) { m_requestOriginHasBeenSet = true; m_requestOrigin = value; } /** *The origin of the request.
*/ inline void SetRequestOrigin(Aws::String&& value) { m_requestOriginHasBeenSet = true; m_requestOrigin = std::move(value); } /** *The origin of the request.
*/ inline void SetRequestOrigin(const char* value) { m_requestOriginHasBeenSet = true; m_requestOrigin.assign(value); } /** *The origin of the request.
*/ inline CreateSessionRequest& WithRequestOrigin(const Aws::String& value) { SetRequestOrigin(value); return *this;} /** *The origin of the request.
*/ inline CreateSessionRequest& WithRequestOrigin(Aws::String&& value) { SetRequestOrigin(std::move(value)); return *this;} /** *The origin of the request.
*/ inline CreateSessionRequest& WithRequestOrigin(const char* value) { SetRequestOrigin(value); return *this;} private: Aws::String m_id; bool m_idHasBeenSet = false; Aws::String m_description; bool m_descriptionHasBeenSet = false; Aws::String m_role; bool m_roleHasBeenSet = false; SessionCommand m_command; bool m_commandHasBeenSet = false; int m_timeout; bool m_timeoutHasBeenSet = false; int m_idleTimeout; bool m_idleTimeoutHasBeenSet = false; Aws::Map