add an emr serverless sample (#220)

emr-serverless-sample/hello-world/.gitignore

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+target/

emr-serverless-spark/README.md

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+# Running EMR Serverless Jobs with Java
+
+We will run a Java Spark job on EMR Serverless using a simple Java "Hello World" example in this example.
+
+## Prerequisites
+
+* LocalStack
+* `aws` CLI & `awslocal` script
+* Docker
+* Java and Maven
+
+## Installation
+
+Before creating the EMR Serverless job, we need to create a JAR file containing the Java code. We have the `java-demo-1.0.jar` file in the current directory. Alternatively, you can create the JAR file yourself by following the steps below.
+
+```bash
+cd hello-world
+mvn package
+```
+
+Next, we need to create an S3 bucket to store the JAR file. To do this, run the following command:
+
+```bash
+export S3_BUCKET=test
+awslocal s3 mb s3://$S3_BUCKET
+```
+
+You can now copy the JAR file from your current directory to the S3 bucket:
+
+```bash
+awslocal s3 cp java-demo-1.0.jar s3://${S3_BUCKET}/code/java-spark/ 
+```
+
+## Creating the EMR Serverless Job
+
+Specify the ARN for the EMR Serverless job with the following command:
+
+```bash
+export JOB_ROLE_ARN=arn:aws:iam::000000000000:role/emr-serverless-job-role
+```
+
+We can now create an EMR Serverless application, which will run Spark 3.3.0. Run the following command:
+
+```bash
+awslocal emr-serverless create-application \
+    --type SPARK \
+    --name serverless-java-demo \
+    --release-label "emr-6.9.0" \
+    --initial-capacity '{
+        "DRIVER": {
+            "workerCount": 1,
+            "workerConfiguration": {
+                "cpu": "4vCPU",
+                "memory": "16GB"
+            }
+        },
+        "EXECUTOR": {
+            "workerCount": 3,
+            "workerConfiguration": {
+                "cpu": "4vCPU",
+                "memory": "16GB"
+            }
+        }
+    }'
+```
+
+You can retrieve the Application ID from the output of the command, and export it as an environment variable:
+
+```bash
+export APPLICATION_ID='<application-id>'
+```
+
+Start the EMR Serverless application:
+
+```shell
+awslocal emr-serverless start-application \
+    --application-id $APPLICATION_ID
+```
+
+## Running the EMR Serverless Job
+
+You can now run the EMR Serverless job:
+
+```bash
+awslocal emr-serverless start-job-run \
+    --application-id $APPLICATION_ID \
+    --execution-role-arn $JOB_ROLE_ARN \
+    --job-driver '{
+        "sparkSubmit": {
+            "entryPoint": "s3://'${S3_BUCKET}'/code/java-spark/java-demo-1.0.jar",
+            "sparkSubmitParameters": "--class HelloWorld"
+        }
+    }' \
+    --configuration-overrides '{
+        "monitoringConfiguration": {
+            "s3MonitoringConfiguration": {
+                "logUri": "s3://'${S3_BUCKET}'/logs/"
+            }
+        }
+    }'
+```
+
+The Spark logs will be written to the S3 bucket specified in the `logUri` parameter. You can stop the EMR Serverless application with the following command:
+
+```bash
+awslocal emr-serverless stop-application \
+    --application-id $APPLICATION_ID
+```

emr-serverless-spark/hello-world/pom.xml

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+<project>
+    <groupId>aws.emr-serverless-samples</groupId>
+    <artifactId>java-demo</artifactId>
+    <modelVersion>4.0.0</modelVersion>
+    <name>EMR Serverless Samples</name>
+    <packaging>jar</packaging>
+    <version>1.0</version>
+    <dependencies>
+      <dependency> <!-- Spark dependency -->
+        <groupId>org.apache.spark</groupId>
+        <artifactId>spark-sql_2.12</artifactId>
+        <version>3.3.0</version>
+        <scope>provided</scope>
+      </dependency>
+    </dependencies>
+    <properties>
+        <maven.compiler.source>1.8</maven.compiler.source>
+        <maven.compiler.target>1.8</maven.compiler.target>
+   </properties>
+  </project>

emr-serverless-spark/hello-world/src/main/java/HelloWorld.java

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+import org.apache.spark.sql.SparkSession;
+
+public class HelloWorld {
+  public static void main(String[] args) {
+    SparkSession spark = SparkSession.builder().appName("Simple Application").getOrCreate();
+
+    System.out.println("Hello, from LocalStack's EMR Serverless implementation!");
+
+    spark.stop();
+  }
+}