AWS emr documentation change
Summary
Minor grammatical and stylistic improvements throughout documentation, including changing 'you'll' to 'you', removing redundant phrases like 'you must', and replacing 'see' with 'refer to' in links. No technical content changes.
Security assessment
The changes are purely editorial improvements without any mention of security vulnerabilities, mitigations, or new security features. The existing security-related content (VPC isolation, IAM policies) remains unchanged in substance.
Diff
diff --git a/emr/latest/EMR-Serverless-UserGuide/emr-serverless.md b/emr/latest/EMR-Serverless-UserGuide/emr-serverless.md index e6f2604c6..412b8dbef 100644 --- a//emr/latest/EMR-Serverless-UserGuide/emr-serverless.md +++ b//emr/latest/EMR-Serverless-UserGuide/emr-serverless.md @@ -13 +13 @@ EMR Serverless helps you avoid over- or under-provisioning resources for your da -With EMR Serverless, you'll continue to get the benefits of Amazon EMR, such as open source compatibility, concurrency, and optimized runtime performance for popular frameworks. +With EMR Serverless, you continue to get the benefits of Amazon EMR, such as open source compatibility, concurrency, and optimized runtime performance for popular frameworks. @@ -23 +23 @@ In this section, we cover EMR Serverless terms and concepts that appear througho -An Amazon EMR _release_ is a set of open-source applications from the big data ecosystem. Each release includes different big data applications, components, and features that you select for EMR Serverless to deploy and configure so that they can run your applications. When you create an application, you must specify its release version. Choose the Amazon EMR release version and the open source framework version that you want to use in your application. To learn more about pre-release versions, see [Amazon EMR Serverless release versions](./release-versions.html). +An Amazon EMR _release_ is a set of open-source applications from the big data ecosystem. Each release includes different big data applications, components, and features that you select for EMR Serverless to deploy and configure so that they can run your applications. When you create an application, specify its release version. Choose the Amazon EMR release version and the open source framework version that you want to use in your application. To learn more about pre-release versions, refer to [Amazon EMR Serverless release versions](./release-versions.html). @@ -27 +27 @@ An Amazon EMR _release_ is a set of open-source applications from the big data e -With EMR Serverless, you can create one or more EMR Serverless applications that use open source analytics frameworks. To create an application, you must specify the following attributes: +With EMR Serverless, you can create one or more EMR Serverless applications that use open source analytics frameworks. To create an application, specify the following attributes: @@ -29 +29 @@ With EMR Serverless, you can create one or more EMR Serverless applications that - * The Amazon EMR release version for the open source framework version that you want to use. To determine your release version, see [Amazon EMR Serverless release versions](./release-versions.html). + * The Amazon EMR release version for the open source framework version that you want to use. To determine your release version, refer to [Amazon EMR Serverless release versions](./release-versions.html). @@ -36 +36 @@ With EMR Serverless, you can create one or more EMR Serverless applications that -After you create an application, you can submit data-processing jobs or interactive requests to your application. +After you create an application, submit data-processing jobs or interactive requests to your application. @@ -38 +38 @@ After you create an application, you can submit data-processing jobs or interact -Each EMR Serverless application runs on a secure Amazon Virtual Private Cloud (VPC) strictly apart from other applications. Additionally, you can use AWS Identity and Access Management (IAM) policies to define which users and roles can access the application. You can also specify limits to control and track usage costs incurred by the application. +Each EMR Serverless application runs on a secure Amazon Virtual Private Cloud (VPC) strictly apart from other applications. Additionally, use AWS Identity and Access Management (IAM) policies to define which users and roles can access the application. You can also specify limits to control and track usage costs incurred by the application. @@ -40 +40 @@ Each EMR Serverless application runs on a secure Amazon Virtual Private Cloud (V -Consider creating multiple applications when you need to do the following: +Consider creating multiple applications when you must do the following: @@ -57 +57 @@ Consider creating multiple applications when you need to do the following: -EMR Serverless is a Regional service that simplifies how workloads run across multiple Availability Zones in a Region. To learn more about how to use applications with EMR Serverless, see [Interact with and configure an EMR Serverless application](./applications.html). +EMR Serverless is a Regional service that simplifies how workloads run across multiple Availability Zones in a Region. To learn more about how to use applications with EMR Serverless, refer to [Interact with and configure an EMR Serverless application](./applications.html). @@ -61 +61 @@ EMR Serverless is a Regional service that simplifies how workloads run across mu -A _job run_ is a request submitted to an EMR Serverless application that the application asychronously executes and tracks through completion. Examples of jobs include a HiveQL query that you submit to an Apache Hive application, or a PySpark data processing script that you submit to an Apache Spark application. When you submit a job, you must specify a runtime role, authored in IAM, that the job uses to access AWS resources, such as Amazon S3 objects. You can submit multiple job run requests to an application, and each job run can use a different runtime role to access AWS resources. An EMR Serverless application starts executing jobs as soon as it receives them and runs multiple job requests concurrently. To learn more about how EMR Serverless runs jobs, see [Running jobs](./jobs.html). +A _job run_ is a request submitted to an EMR Serverless application that the application asychronously executes and tracks through completion. Examples of jobs include a HiveQL query that you submit to an Apache Hive application, or a PySpark data processing script that you submit to an Apache Spark application. When you submit a job, you must specify a runtime role, authored in IAM, that the job uses to access AWS resources, such as Amazon S3 objects. You can submit multiple job run requests to an application, and each job run can use a different runtime role to access AWS resources. An EMR Serverless application starts executing jobs as soon as it receives them and runs multiple job requests concurrently. To learn more about how EMR Serverless runs jobs, refer to [Running jobs](./jobs.html). @@ -65 +65 @@ A _job run_ is a request submitted to an EMR Serverless application that the app -An EMR Serverless application internally uses _workers_ to execute your workloads. The default sizes of these workers are based on your application type and Amazon EMR release version. When you schedule a job run, you can override these sizes. +An EMR Serverless application internally uses _workers_ to execute your workloads. The default sizes of these workers are based on your application type and Amazon EMR release version. When you schedule a job run, override these sizes. @@ -71 +71 @@ When you submit a job, EMR Serverless computes the resources that the applicatio -EMR Serverless provides a _pre-initialized capacity_ feature that keeps workers initialized and ready to respond in seconds. This capacity effectively creates a warm pool of workers for an application. To configure this feature for each application, set the `initial-capacity` parameter of an application. When you configure pre-initialized capacity, jobs can start immediately so that you can implement iterative applications and time-sensitive jobs. To learn more about pre-initialized workers, see [Configuring an application when working with EMR Serverless](./application-capacity.html). +EMR Serverless provides a _pre-initialized capacity_ feature that keeps workers initialized and ready to respond in seconds. This capacity effectively creates a warm pool of workers for an application. To configure this feature for each application, set the `initial-capacity` parameter of an application. When you configure pre-initialized capacity, jobs can start immediately so that you can implement iterative applications and time-sensitive jobs. To learn more about pre-initialized workers, refer to [Configuring an application when working with EMR Serverless](./application-capacity.html). @@ -75 +75 @@ EMR Serverless provides a _pre-initialized capacity_ feature that keeps workers -EMR Studio is the user console that you can use to manage your EMR Serverless applications. If an EMR Studio doesn't exist in your account when you create your first EMR Serverless application, we automatically create one for you. You can access EMR Studio either from the Amazon EMR console, or you can turn on federated access from your identity provider (IdP) through IAM or IAM Identity Center. When you do this, users can access Studio and manage EMR Serverless applications without direct access to the Amazon EMR console. To learn more about how EMR Serverless applications works with EMR Studio, see [Creating an EMR Serverless application from the EMR Studio console](./studio.html) and [Running jobs from the EMR Studio console](./jobs-studio.html). +EMR Studio is the user console for managing your EMR Serverless applications. If an EMR Studio doesn't exist in your account when you create your first EMR Serverless application, we automatically create one for you. Access EMR Studio either from the Amazon EMR console, or turn on federated access from your identity provider (IdP) through IAM or IAM Identity Center. When you do this, users can access Studio and manage EMR Serverless applications without direct access to the Amazon EMR console. To learn more about how EMR Serverless applications works with EMR Studio, refer to [Creating an EMR Serverless application from the EMR Studio console](./studio.html) and [Running jobs from the EMR Studio console](./jobs-studio.html).