From bf7b860b09af2d3b55b8e25637e3fcacd9991ef5 Mon Sep 17 00:00:00 2001 From: Siva Ramani Date: Fri, 9 Sep 2022 12:37:33 -0500 Subject: [PATCH] bar raiser review comments --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 569aab7..d402480 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# Running a Data Processing Job on EMR Serverless with AWS Step Functions and AWS Lambda using Terraform (By HashiCorp) +# Run a data processing job on Amazon EMR Serverless with AWS Step Functions In this blog we showcase how to build and orchestrate a [Scala](https://www.scala-lang.org/) Spark Application using [Amazon EMR Serverless](https://aws.amazon.com/emr/serverless/) , AWS Step Functions and [Terraform By HashiCorp](https://www.terraform.io/). In this end to end solution we execute a Spark job on EMR Serverless which processes sample click-stream data in Amazon S3 bucket and stores the aggregation results in Amazon S3. @@ -138,6 +138,7 @@ EMR Studio * Open AWS Console, Navigate to “EMR” > “Serverless” tab on the left pane. * Select “clicklogger-dev-studio” and click “Manage Applications” +* The Application created by the stack will be as shown below clicklogger-dev-loggregator-emr-