AWS emr documentation change
Summary
Fixed a typo in the word 'pre-initialized'
Security assessment
This is a minor typographical correction with no security implications. The change doesn't address any security vulnerability or weakness.
Diff
diff --git a/emr/latest/EMR-Serverless-UserGuide/interactive-workloads.md b/emr/latest/EMR-Serverless-UserGuide/interactive-workloads.md index 090add843..91a61a6ed 100644 --- a//emr/latest/EMR-Serverless-UserGuide/interactive-workloads.md +++ b//emr/latest/EMR-Serverless-UserGuide/interactive-workloads.md @@ -138 +138 @@ When you attach an application to a Studio Workspace, the application start trig - * When using an interactive application, we suggest that you configure a pre-intialized capacity of kernels, drivers, and executors to run your notebooks. Each Spark interactive session requires one kernel and one driver, so EMR Serverless maintains a pre-initialized kernel worker for every pre-initialized driver. By default, EMR Serverless maintains a pre-initialized capacity of one kernel worker throughout the entire application even if you don't specify any pre-initialized capacity for drivers. Each kernel worker uses 4 vCPU and 16 GB of memory. For current pricing information, refer to the [Amazon EMR Pricing](https://aws.amazon.com/emr/pricing/) page. + * When using an interactive application, we suggest that you configure a pre-initialized capacity of kernels, drivers, and executors to run your notebooks. Each Spark interactive session requires one kernel and one driver, so EMR Serverless maintains a pre-initialized kernel worker for every pre-initialized driver. By default, EMR Serverless maintains a pre-initialized capacity of one kernel worker throughout the entire application even if you don't specify any pre-initialized capacity for drivers. Each kernel worker uses 4 vCPU and 16 GB of memory. For current pricing information, refer to the [Amazon EMR Pricing](https://aws.amazon.com/emr/pricing/) page.