SageMaker contoh penggunaan SDK untuk Kotlin - AWS SDKContoh Kode
TindakanSkenario

Ada lebih banyak AWS SDK contoh yang tersedia di GitHub repo SDKContoh AWS Dokumen.

Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.

SageMaker contoh penggunaan SDK untuk Kotlin

Contoh kode berikut menunjukkan cara melakukan tindakan dan mengimplementasikan skenario umum dengan menggunakan AWS SDK for Kotlin with SageMaker.

Tindakan adalah kutipan kode dari program yang lebih besar dan harus dijalankan dalam konteks. Sementara tindakan menunjukkan cara memanggil fungsi layanan individual, Anda dapat melihat tindakan dalam konteks dalam skenario terkait.

Skenario adalah contoh kode yang menunjukkan kepada Anda bagaimana menyelesaikan tugas tertentu dengan memanggil beberapa fungsi dalam layanan atau dikombinasikan dengan yang lain AWS layanan.

Setiap contoh menyertakan tautan ke kode sumber lengkap, di mana Anda dapat menemukan instruksi tentang cara mengatur dan menjalankan kode dalam konteks.

Memulai

Contoh kode berikut menunjukkan cara untuk mulai menggunakan SageMaker.

SDKuntuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode AWS. 

suspend fun listBooks() {
    SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
        val response = sageMakerClient.listNotebookInstances(ListNotebookInstancesRequest {})
        response.notebookInstances?.forEach { item ->
            println("The notebook name is: ${item.notebookInstanceName}")
        }
    }
}

Tindakan

Contoh kode berikut menunjukkan cara menggunakanCreatePipeline.

SDKuntuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode AWS. 

// Create a pipeline from the example pipeline JSON.
suspend fun setupPipeline(filePath: String?, roleArnVal: String?, functionArnVal: String?, pipelineNameVal: String?) {
    println("Setting up the pipeline.")
    val parser = JSONParser()

    // Read JSON and get pipeline definition.
    FileReader(filePath).use { reader ->
        val obj: Any = parser.parse(reader)
        val jsonObject: JSONObject = obj as JSONObject
        val stepsArray: JSONArray = jsonObject.get("Steps") as JSONArray
        for (stepObj in stepsArray) {
            val step: JSONObject = stepObj as JSONObject
            if (step.containsKey("FunctionArn")) {
                step.put("FunctionArn", functionArnVal)
            }
        }
        println(jsonObject)

        // Create the pipeline.
        val pipelineRequest = CreatePipelineRequest {
            pipelineDescription = "Kotlin SDK example pipeline"
            roleArn = roleArnVal
            pipelineName = pipelineNameVal
            pipelineDefinition = jsonObject.toString()
        }

        SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
            sageMakerClient.createPipeline(pipelineRequest)
        }
    }
}

Contoh kode berikut menunjukkan cara menggunakanDeletePipeline.

SDKuntuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode AWS. 

// Delete a SageMaker pipeline by name.
suspend fun deletePipeline(pipelineNameVal: String) {
    val pipelineRequest = DeletePipelineRequest {
        pipelineName = pipelineNameVal
    }

    SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
        sageMakerClient.deletePipeline(pipelineRequest)
        println("*** Successfully deleted $pipelineNameVal")
    }
}

Contoh kode berikut menunjukkan cara menggunakanDescribePipelineExecution.

SDKuntuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode AWS. 

suspend fun waitForPipelineExecution(executionArn: String?) {
    var status: String
    var index = 0
    do {
        val pipelineExecutionRequest = DescribePipelineExecutionRequest {
            pipelineExecutionArn = executionArn
        }

        SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
            val response = sageMakerClient.describePipelineExecution(pipelineExecutionRequest)
            status = response.pipelineExecutionStatus.toString()
            println("$index. The status of the pipeline is $status")
            TimeUnit.SECONDS.sleep(4)
            index++
        }
    } while ("Executing" == status)
    println("Pipeline finished with status $status")
}

Contoh kode berikut menunjukkan cara menggunakanStartPipelineExecution.

SDKuntuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode AWS. 

// Start a pipeline run with job configurations.
suspend fun executePipeline(bucketName: String, queueUrl: String?, roleArn: String?, pipelineNameVal: String): String? {
    println("Starting pipeline execution.")
    val inputBucketLocation = "s3://$bucketName/samplefiles/latlongtest.csv"
    val output = "s3://$bucketName/outputfiles/"

    val gson = GsonBuilder()
        .setFieldNamingPolicy(FieldNamingPolicy.UPPER_CAMEL_CASE)
        .setPrettyPrinting()
        .create()

    // Set up all parameters required to start the pipeline.
    val parameters: MutableList<Parameter> = java.util.ArrayList<Parameter>()

    val para1 = Parameter {
        name = "parameter_execution_role"
        value = roleArn
    }
    val para2 = Parameter {
        name = "parameter_queue_url"
        value = queueUrl
    }

    val inputJSON = """{
        "DataSourceConfig": {
        "S3Data": {
            "S3Uri": "s3://$bucketName/samplefiles/latlongtest.csv"
        },
        "Type": "S3_DATA"
        },
        "DocumentType": "CSV"
    }"""
    println(inputJSON)
    val para3 = Parameter {
        name = "parameter_vej_input_config"
        value = inputJSON
    }

    // Create an ExportVectorEnrichmentJobOutputConfig object.
    val jobS3Data = VectorEnrichmentJobS3Data {
        s3Uri = output
    }

    val outputConfig = ExportVectorEnrichmentJobOutputConfig {
        s3Data = jobS3Data
    }

    val gson4: String = gson.toJson(outputConfig)
    val para4: Parameter = Parameter {
        name = "parameter_vej_export_config"
        value = gson4
    }
    println("parameter_vej_export_config:" + gson.toJson(outputConfig))

    val para5JSON =
        "{\"MapMatchingConfig\":null,\"ReverseGeocodingConfig\":{\"XAttributeName\":\"Longitude\",\"YAttributeName\":\"Latitude\"}}"

    val para5: Parameter = Parameter {
        name = "parameter_step_1_vej_config"
        value = para5JSON
    }

    parameters.add(para1)
    parameters.add(para2)
    parameters.add(para3)
    parameters.add(para4)
    parameters.add(para5)

    val pipelineExecutionRequest = StartPipelineExecutionRequest {
        pipelineExecutionDescription = "Created using Kotlin SDK"
        pipelineExecutionDisplayName = "$pipelineName-example-execution"
        pipelineParameters = parameters
        pipelineName = pipelineNameVal
    }

    SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
        val response = sageMakerClient.startPipelineExecution(pipelineExecutionRequest)
        return response.pipelineExecutionArn
    }
}

Skenario

Contoh kode berikut ini menunjukkan cara:

  • Siapkan sumber daya untuk pipa.

  • Siapkan pipa yang menjalankan pekerjaan geospasial.

  • Mulai eksekusi pipeline.

  • Pantau status eksekusi.

  • Lihat output dari pipa.

  • Pembersihan sumber daya

Untuk informasi selengkapnya, lihat Membuat dan menjalankan SageMaker pipeline menggunakan AWS SDKs Community.aws.

SDKuntuk Kotlin
catatan

Ada lebih banyak tentang GitHub. Temukan contoh lengkapnya dan pelajari cara pengaturan dan menjalankannya di Repositori Contoh Kode AWS. 

val DASHES = String(CharArray(80)).replace("\u0000", "-")
private var eventSourceMapping = ""

suspend fun main(args: Array<String>) {
    val usage = """
    Usage:
          <sageMakerRoleName> <lambdaRoleName> <functionName> <functionKey> <queueName> <bucketName> <bucketFunction> <lnglatData> <spatialPipelinePath> <pipelineName>

    Where:
        sageMakerRoleName - The name of the Amazon SageMaker role.
        lambdaRoleName - The name of the AWS Lambda role.
        functionName - The name of the AWS Lambda function (for example,SageMakerExampleFunction).
        functionKey - The name of the Amazon S3 key name that represents the Lambda function (for example, SageMakerLambda.zip).
        queueName - The name of the Amazon Simple Queue Service (Amazon SQS) queue.
        bucketName - The name of the Amazon Simple Storage Service (Amazon S3) bucket.
        bucketFunction - The name of the Amazon S3 bucket that contains the Lambda ZIP file. 
        lnglatData - The file location of the latlongtest.csv file required for this use case.
        spatialPipelinePath - The file location of the GeoSpatialPipeline.json file required for this use case.
        pipelineName - The name of the pipeline to create (for example, sagemaker-sdk-example-pipeline).
    """

    if (args.size != 10) {
        println(usage)
        exitProcess(1)
    }

    val sageMakerRoleName = args[0]
    val lambdaRoleName = args[1]
    val functionKey = args[2]
    val functionName = args[3]
    val queueName = args[4]
    val bucketName = args[5]
    val bucketFunction = args[6]
    val lnglatData = args[7]
    val spatialPipelinePath = args[8]
    val pipelineName = args[9]
    val handlerName = "org.example.SageMakerLambdaFunction::handleRequest"

    println(DASHES)
    println("Welcome to the Amazon SageMaker pipeline example scenario.")
    println(
        """
         This example workflow will guide you through setting up and running an
         Amazon SageMaker pipeline. The pipeline uses an AWS Lambda function and an
         Amazon SQS Queue. It runs a vector enrichment reverse geocode job to
         reverse geocode addresses in an input file and store the results in an export file.
        """.trimIndent(),
    )
    println(DASHES)

    println(DASHES)
    println("First, we will set up the roles, functions, and queue needed by the SageMaker pipeline.")
    val lambdaRoleArn: String = checkLambdaRole(lambdaRoleName)
    val sageMakerRoleArn: String = checkSageMakerRole(sageMakerRoleName)
    val functionArn = checkFunction(functionName, bucketFunction, functionKey, handlerName, lambdaRoleArn)
    val queueUrl = checkQueue(queueName, functionName)
    println(DASHES)

    println(DASHES)
    println("Setting up bucket $bucketName")
    if (!checkBucket(bucketName)) {
        setupBucket(bucketName)
        println("Put $lnglatData into $bucketName")
        val objectKey = "samplefiles/latlongtest.csv"
        putS3Object(bucketName, objectKey, lnglatData)
    }
    println(DASHES)

    println(DASHES)
    println("Now we can create and run our pipeline.")
    setupPipeline(spatialPipelinePath, sageMakerRoleArn, functionArn, pipelineName)
    val pipelineExecutionARN = executePipeline(bucketName, queueUrl, sageMakerRoleArn, pipelineName)
    println("The pipeline execution ARN value is $pipelineExecutionARN")
    waitForPipelineExecution(pipelineExecutionARN)
    println("Wait 30 secs to get output results $bucketName")
    TimeUnit.SECONDS.sleep(30)
    getOutputResults(bucketName)
    println(DASHES)

    println(DASHES)
    println(
        """
             The pipeline has completed. To view the pipeline and runs in SageMaker Studio, follow these instructions:
             https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-studio.html
        """.trimIndent(),
    )
    println(DASHES)

    println(DASHES)
    println("Do you want to delete the AWS resources used in this Workflow? (y/n)")
    val `in` = Scanner(System.`in`)
    val delResources = `in`.nextLine()
    if (delResources.compareTo("y") == 0) {
        println("Lets clean up the AWS resources. Wait 30 seconds")
        TimeUnit.SECONDS.sleep(30)
        deleteEventSourceMapping(functionName)
        deleteSQSQueue(queueName)
        listBucketObjects(bucketName)
        deleteBucket(bucketName)
        delLambdaFunction(functionName)
        deleteLambdaRole(lambdaRoleName)
        deleteSagemakerRole(sageMakerRoleName)
        deletePipeline(pipelineName)
    } else {
        println("The AWS Resources were not deleted!")
    }
    println(DASHES)

    println(DASHES)
    println("SageMaker pipeline scenario is complete.")
    println(DASHES)
}

// Delete a SageMaker pipeline by name.
suspend fun deletePipeline(pipelineNameVal: String) {
    val pipelineRequest = DeletePipelineRequest {
        pipelineName = pipelineNameVal
    }

    SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
        sageMakerClient.deletePipeline(pipelineRequest)
        println("*** Successfully deleted $pipelineNameVal")
    }
}

suspend fun deleteSagemakerRole(roleNameVal: String) {
    val sageMakerRolePolicies = getSageMakerRolePolicies()
    IamClient { region = "us-west-2" }.use { iam ->
        for (policy in sageMakerRolePolicies) {
            // First the policy needs to be detached.
            val rolePolicyRequest = DetachRolePolicyRequest {
                policyArn = policy
                roleName = roleNameVal
            }
            iam.detachRolePolicy(rolePolicyRequest)
        }

        // Delete the role.
        val roleRequest = DeleteRoleRequest {
            roleName = roleNameVal
        }
        iam.deleteRole(roleRequest)
        println("*** Successfully deleted $roleNameVal")
    }
}

suspend fun deleteLambdaRole(roleNameVal: String) {
    val lambdaRolePolicies = getLambdaRolePolicies()
    IamClient { region = "us-west-2" }.use { iam ->
        for (policy in lambdaRolePolicies) {
            // First the policy needs to be detached.
            val rolePolicyRequest = DetachRolePolicyRequest {
                policyArn = policy
                roleName = roleNameVal
            }
            iam.detachRolePolicy(rolePolicyRequest)
        }

        // Delete the role.
        val roleRequest = DeleteRoleRequest {
            roleName = roleNameVal
        }
        iam.deleteRole(roleRequest)
        println("*** Successfully deleted $roleNameVal")
    }
}

suspend fun delLambdaFunction(myFunctionName: String) {
    val request = DeleteFunctionRequest {
        functionName = myFunctionName
    }

    LambdaClient { region = "us-west-2" }.use { awsLambda ->
        awsLambda.deleteFunction(request)
        println("$myFunctionName was deleted")
    }
}

suspend fun deleteBucket(bucketName: String?) {
    val request = DeleteBucketRequest {
        bucket = bucketName
    }
    S3Client { region = "us-east-1" }.use { s3 ->
        s3.deleteBucket(request)
        println("The $bucketName was successfully deleted!")
    }
}

suspend fun deleteBucketObjects(bucketName: String, objectName: String?) {
    val toDelete = ArrayList<ObjectIdentifier>()
    val obId = ObjectIdentifier {
        key = objectName
    }
    toDelete.add(obId)
    val delOb = Delete {
        objects = toDelete
    }
    val dor = DeleteObjectsRequest {
        bucket = bucketName
        delete = delOb
    }

    S3Client { region = "us-east-1" }.use { s3Client ->
        s3Client.deleteObjects(dor)
        println("*** $bucketName objects were deleted.")
    }
}

suspend fun listBucketObjects(bucketNameVal: String) {
    val listObjects = ListObjectsRequest {
        bucket = bucketNameVal
    }

    S3Client { region = "us-east-1" }.use { s3Client ->
        val res = s3Client.listObjects(listObjects)
        val objects = res.contents
        if (objects != null) {
            for (myValue in objects) {
                println("The name of the key is ${myValue.key}")
                deleteBucketObjects(bucketNameVal, myValue.key)
            }
        }
    }
}

// Delete the specific Amazon SQS queue.
suspend fun deleteSQSQueue(queueNameVal: String?) {
    val getQueueRequest = GetQueueUrlRequest {
        queueName = queueNameVal
    }

    SqsClient { region = "us-west-2" }.use { sqsClient ->
        val urlVal = sqsClient.getQueueUrl(getQueueRequest).queueUrl
        val deleteQueueRequest = DeleteQueueRequest {
            queueUrl = urlVal
        }
        sqsClient.deleteQueue(deleteQueueRequest)
    }
}

// Delete the queue event mapping.
suspend fun deleteEventSourceMapping(functionNameVal: String) {
    if (eventSourceMapping.compareTo("") == 0) {
        LambdaClient { region = "us-west-2" }.use { lambdaClient ->
            val request = ListEventSourceMappingsRequest {
                functionName = functionNameVal
            }
            val response = lambdaClient.listEventSourceMappings(request)
            val eventList = response.eventSourceMappings
            if (eventList != null) {
                for (event in eventList) {
                    eventSourceMapping = event.uuid.toString()
                }
            }
        }
    }

    val eventSourceMappingRequest = DeleteEventSourceMappingRequest {
        uuid = eventSourceMapping
    }
    LambdaClient { region = "us-west-2" }.use { lambdaClient ->
        lambdaClient.deleteEventSourceMapping(eventSourceMappingRequest)
        println("The event mapping is deleted!")
    }
}

// Reads the objects in the S3 bucket and displays the values.
private suspend fun readObject(bucketName: String, keyVal: String?) {
    println("Output file contents: \n")
    val objectRequest = GetObjectRequest {
        bucket = bucketName
        key = keyVal
    }
    S3Client { region = "us-east-1" }.use { s3Client ->
        s3Client.getObject(objectRequest) { resp ->
            val byteArray = resp.body?.toByteArray()
            val text = byteArray?.let { String(it, StandardCharsets.UTF_8) }
            println("Text output: $text")
        }
    }
}

// Display the results from the output directory.
suspend fun getOutputResults(bucketName: String?) {
    println("Getting output results $bucketName.")
    val listObjectsRequest = ListObjectsRequest {
        bucket = bucketName
        prefix = "outputfiles/"
    }
    S3Client { region = "us-east-1" }.use { s3Client ->
        val response = s3Client.listObjects(listObjectsRequest)
        val s3Objects: List<Object>? = response.contents
        if (s3Objects != null) {
            for (`object` in s3Objects) {
                if (bucketName != null) {
                    readObject(bucketName, (`object`.key))
                }
            }
        }
    }
}

suspend fun waitForPipelineExecution(executionArn: String?) {
    var status: String
    var index = 0
    do {
        val pipelineExecutionRequest = DescribePipelineExecutionRequest {
            pipelineExecutionArn = executionArn
        }

        SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
            val response = sageMakerClient.describePipelineExecution(pipelineExecutionRequest)
            status = response.pipelineExecutionStatus.toString()
            println("$index. The status of the pipeline is $status")
            TimeUnit.SECONDS.sleep(4)
            index++
        }
    } while ("Executing" == status)
    println("Pipeline finished with status $status")
}

// Start a pipeline run with job configurations.
suspend fun executePipeline(bucketName: String, queueUrl: String?, roleArn: String?, pipelineNameVal: String): String? {
    println("Starting pipeline execution.")
    val inputBucketLocation = "s3://$bucketName/samplefiles/latlongtest.csv"
    val output = "s3://$bucketName/outputfiles/"

    val gson = GsonBuilder()
        .setFieldNamingPolicy(FieldNamingPolicy.UPPER_CAMEL_CASE)
        .setPrettyPrinting()
        .create()

    // Set up all parameters required to start the pipeline.
    val parameters: MutableList<Parameter> = java.util.ArrayList<Parameter>()

    val para1 = Parameter {
        name = "parameter_execution_role"
        value = roleArn
    }
    val para2 = Parameter {
        name = "parameter_queue_url"
        value = queueUrl
    }

    val inputJSON = """{
        "DataSourceConfig": {
        "S3Data": {
            "S3Uri": "s3://$bucketName/samplefiles/latlongtest.csv"
        },
        "Type": "S3_DATA"
        },
        "DocumentType": "CSV"
    }"""
    println(inputJSON)
    val para3 = Parameter {
        name = "parameter_vej_input_config"
        value = inputJSON
    }

    // Create an ExportVectorEnrichmentJobOutputConfig object.
    val jobS3Data = VectorEnrichmentJobS3Data {
        s3Uri = output
    }

    val outputConfig = ExportVectorEnrichmentJobOutputConfig {
        s3Data = jobS3Data
    }

    val gson4: String = gson.toJson(outputConfig)
    val para4: Parameter = Parameter {
        name = "parameter_vej_export_config"
        value = gson4
    }
    println("parameter_vej_export_config:" + gson.toJson(outputConfig))

    val para5JSON =
        "{\"MapMatchingConfig\":null,\"ReverseGeocodingConfig\":{\"XAttributeName\":\"Longitude\",\"YAttributeName\":\"Latitude\"}}"

    val para5: Parameter = Parameter {
        name = "parameter_step_1_vej_config"
        value = para5JSON
    }

    parameters.add(para1)
    parameters.add(para2)
    parameters.add(para3)
    parameters.add(para4)
    parameters.add(para5)

    val pipelineExecutionRequest = StartPipelineExecutionRequest {
        pipelineExecutionDescription = "Created using Kotlin SDK"
        pipelineExecutionDisplayName = "$pipelineName-example-execution"
        pipelineParameters = parameters
        pipelineName = pipelineNameVal
    }

    SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
        val response = sageMakerClient.startPipelineExecution(pipelineExecutionRequest)
        return response.pipelineExecutionArn
    }
}

// Create a pipeline from the example pipeline JSON.
suspend fun setupPipeline(filePath: String?, roleArnVal: String?, functionArnVal: String?, pipelineNameVal: String?) {
    println("Setting up the pipeline.")
    val parser = JSONParser()

    // Read JSON and get pipeline definition.
    FileReader(filePath).use { reader ->
        val obj: Any = parser.parse(reader)
        val jsonObject: JSONObject = obj as JSONObject
        val stepsArray: JSONArray = jsonObject.get("Steps") as JSONArray
        for (stepObj in stepsArray) {
            val step: JSONObject = stepObj as JSONObject
            if (step.containsKey("FunctionArn")) {
                step.put("FunctionArn", functionArnVal)
            }
        }
        println(jsonObject)

        // Create the pipeline.
        val pipelineRequest = CreatePipelineRequest {
            pipelineDescription = "Kotlin SDK example pipeline"
            roleArn = roleArnVal
            pipelineName = pipelineNameVal
            pipelineDefinition = jsonObject.toString()
        }

        SageMakerClient { region = "us-west-2" }.use { sageMakerClient ->
            sageMakerClient.createPipeline(pipelineRequest)
        }
    }
}

suspend fun putS3Object(bucketName: String, objectKey: String, objectPath: String) {
    val request = PutObjectRequest {
        bucket = bucketName
        key = objectKey
        body = File(objectPath).asByteStream()
    }

    S3Client { region = "us-east-1" }.use { s3 ->
        s3.putObject(request)
        println("Successfully placed $objectKey into bucket $bucketName")
    }
}

suspend fun setupBucket(bucketName: String) {
    val request = CreateBucketRequest {
        bucket = bucketName
    }

    S3Client { region = "us-east-1" }.use { s3 ->
        s3.createBucket(request)
        println("$bucketName is ready")
    }
}

suspend fun checkBucket(bucketName: String): Boolean {
    try {
        val headBucketRequest = HeadBucketRequest {
            bucket = bucketName
        }
        S3Client { region = "us-east-1" }.use { s3Client ->
            s3Client.headBucket(headBucketRequest)
            println("$bucketName exists")
            return true
        }
    } catch (e: S3Exception) {
        println("Bucket does not exist")
    }
    return false
}

// Connect the queue to the Lambda function as an event source.
suspend fun connectLambda(queueUrlVal: String?, lambdaNameVal: String?) {
    println("Connecting the Lambda function and queue for the pipeline.")
    var queueArn = ""

    // Specify the attributes to retrieve.
    val atts: MutableList<QueueAttributeName> = ArrayList()
    atts.add(QueueAttributeName.QueueArn)
    val attributesRequest = GetQueueAttributesRequest {
        queueUrl = queueUrlVal
        attributeNames = atts
    }

    SqsClient { region = "us-west-2" }.use { sqsClient ->
        val response = sqsClient.getQueueAttributes(attributesRequest)
        val queueAtts = response.attributes
        if (queueAtts != null) {
            for ((key, value) in queueAtts) {
                println("Key = $key, Value = $value")
                queueArn = value
            }
        }
    }
    val eventSourceMappingRequest = CreateEventSourceMappingRequest {
        eventSourceArn = queueArn
        functionName = lambdaNameVal
    }
    LambdaClient { region = "us-west-2" }.use { lambdaClient ->
        val response1 = lambdaClient.createEventSourceMapping(eventSourceMappingRequest)
        eventSourceMapping = response1.uuid.toString()
        println("The mapping between the event source and Lambda function was successful")
    }
}

// Set up the SQS queue to use with the pipeline.
suspend fun setupQueue(queueNameVal: String, lambdaNameVal: String): String {
    println("Setting up queue named $queueNameVal")
    val queueAtt: MutableMap<String, String> = HashMap()
    queueAtt.put("DelaySeconds", "5")
    queueAtt.put("ReceiveMessageWaitTimeSeconds", "5")
    queueAtt.put("VisibilityTimeout", "300")

    val createQueueRequest = CreateQueueRequest {
        queueName = queueNameVal
        attributes = queueAtt
    }

    SqsClient { region = "us-west-2" }.use { sqsClient ->
        sqsClient.createQueue(createQueueRequest)
        println("\nGet queue url")
        val getQueueUrlResponse = sqsClient.getQueueUrl(GetQueueUrlRequest { queueName = queueNameVal })
        TimeUnit.SECONDS.sleep(15)
        connectLambda(getQueueUrlResponse.queueUrl, lambdaNameVal)
        println("Queue ready with Url " + getQueueUrlResponse.queueUrl)
        return getQueueUrlResponse.queueUrl.toString()
    }
}

// Checks to see if the Amazon SQS queue exists. If not, this method creates a new queue
// and returns the ARN value.
suspend fun checkQueue(queueNameVal: String, lambdaNameVal: String): String? {
    println("Checking to see if the queue exists. If not, a new queue will be created for use in this workflow.")
    var queueUrl: String
    try {
        val request = GetQueueUrlRequest {
            queueName = queueNameVal
        }

        SqsClient { region = "us-west-2" }.use { sqsClient ->
            val response = sqsClient.getQueueUrl(request)
            queueUrl = response.queueUrl.toString()
            println(queueUrl)
        }
    } catch (e: SqsException) {
        println(e.message + " A new queue will be created")
        queueUrl = setupQueue(queueNameVal, lambdaNameVal)
    }
    return queueUrl
}

suspend fun createNewFunction(myFunctionName: String, s3BucketName: String, myS3Key: String, myHandler: String, myRole: String): String {
    val functionCode = FunctionCode {
        s3Bucket = s3BucketName
        s3Key = myS3Key
    }

    val request = CreateFunctionRequest {
        functionName = myFunctionName
        code = functionCode
        description = "Created by the Lambda Kotlin API"
        handler = myHandler
        role = myRole
        runtime = Runtime.Java11
        memorySize = 1024
        timeout = 200
    }

    LambdaClient { region = "us-west-2" }.use { awsLambda ->
        val functionResponse = awsLambda.createFunction(request)
        awsLambda.waitUntilFunctionActive {
            functionName = myFunctionName
        }
        println("${functionResponse.functionArn} was created")
        return functionResponse.functionArn.toString()
    }
}

suspend fun checkFunction(myFunctionName: String, s3BucketName: String, myS3Key: String, myHandler: String, myRole: String): String {
    println("Checking to see if the function exists. If not, a new AWS Lambda function will be created for use in this workflow.")
    var functionArn: String
    try {
        // Does this function already exist.
        val functionRequest = GetFunctionRequest {
            functionName = myFunctionName
        }
        LambdaClient { region = "us-west-2" }.use { lambdaClient ->
            val response = lambdaClient.getFunction(functionRequest)
            functionArn = response.configuration?.functionArn.toString()
            println("$functionArn exists")
        }
    } catch (e: LambdaException) {
        println(e.message + " A new function will be created")
        functionArn = createNewFunction(myFunctionName, s3BucketName, myS3Key, myHandler, myRole)
    }
    return functionArn
}

// Checks to see if the SageMaker role exists. If not, this method creates it.
suspend fun checkSageMakerRole(roleNameVal: String): String {
    println("Checking to see if the role exists. If not, a new role will be created for AWS SageMaker to use.")
    var roleArn: String
    try {
        val roleRequest = GetRoleRequest {
            roleName = roleNameVal
        }
        IamClient { region = "AWS_GLOBAL" }.use { iamClient ->
            val response = iamClient.getRole(roleRequest)
            roleArn = response.role?.arn.toString()
            println(roleArn)
        }
    } catch (e: IamException) {
        println(e.message + " A new role will be created")
        roleArn = createSageMakerRole(roleNameVal)
    }
    return roleArn
}

suspend fun createSageMakerRole(roleNameVal: String): String {
    val sageMakerRolePolicies = getSageMakerRolePolicies()
    println("Creating a role to use with SageMaker.")
    val assumeRolePolicy = "{" +
        "\"Version\": \"2012-10-17\"," +
        "\"Statement\": [{" +
        "\"Effect\": \"Allow\"," +
        "\"Principal\": {" +
        "\"Service\": [" +
        "\"sagemaker.amazonaws.com\"," +
        "\"sagemaker-geospatial.amazonaws.com\"," +
        "\"lambda.amazonaws.com\"," +
        "\"s3.amazonaws.com\"" +
        "]" +
        "}," +
        "\"Action\": \"sts:AssumeRole\"" +
        "}]" +
        "}"

    val request = CreateRoleRequest {
        roleName = roleNameVal
        assumeRolePolicyDocument = assumeRolePolicy
        description = "Created using the AWS SDK for Kotlin"
    }
    IamClient { region = "AWS_GLOBAL" }.use { iamClient ->
        val roleResult = iamClient.createRole(request)

        // Attach the policies to the role.
        for (policy in sageMakerRolePolicies) {
            val attachRequest = AttachRolePolicyRequest {
                roleName = roleNameVal
                policyArn = policy
            }
            iamClient.attachRolePolicy(attachRequest)
        }

        // Allow time for the role to be ready.
        TimeUnit.SECONDS.sleep(15)
        System.out.println("Role ready with ARN ${roleResult.role?.arn}")
        return roleResult.role?.arn.toString()
    }
}

// Checks to see if the Lambda role exists. If not, this method creates it.
suspend fun checkLambdaRole(roleNameVal: String): String {
    println("Checking to see if the role exists. If not, a new role will be created for AWS Lambda to use.")
    var roleArn: String
    val roleRequest = GetRoleRequest {
        roleName = roleNameVal
    }

    try {
        IamClient { region = "AWS_GLOBAL" }.use { iamClient ->
            val response = iamClient.getRole(roleRequest)
            roleArn = response.role?.arn.toString()
            println(roleArn)
        }
    } catch (e: IamException) {
        println(e.message + " A new role will be created")
        roleArn = createLambdaRole(roleNameVal)
    }

    return roleArn
}

private suspend fun createLambdaRole(roleNameVal: String): String {
    val lambdaRolePolicies = getLambdaRolePolicies()
    val assumeRolePolicy = "{" +
        "\"Version\": \"2012-10-17\"," +
        "\"Statement\": [{" +
        "\"Effect\": \"Allow\"," +
        "\"Principal\": {" +
        "\"Service\": [" +
        "\"sagemaker.amazonaws.com\"," +
        "\"sagemaker-geospatial.amazonaws.com\"," +
        "\"lambda.amazonaws.com\"," +
        "\"s3.amazonaws.com\"" +
        "]" +
        "}," +
        "\"Action\": \"sts:AssumeRole\"" +
        "}]" +
        "}"

    val request = CreateRoleRequest {
        roleName = roleNameVal
        assumeRolePolicyDocument = assumeRolePolicy
        description = "Created using the AWS SDK for Kotlin"
    }

    IamClient { region = "AWS_GLOBAL" }.use { iamClient ->
        val roleResult = iamClient.createRole(request)

        // Attach the policies to the role.
        for (policy in lambdaRolePolicies) {
            val attachRequest = AttachRolePolicyRequest {
                roleName = roleNameVal
                policyArn = policy
            }
            iamClient.attachRolePolicy(attachRequest)
        }

        // Allow time for the role to be ready.
        TimeUnit.SECONDS.sleep(15)
        println("Role ready with ARN " + roleResult.role?.arn)
        return roleResult.role?.arn.toString()
    }
}

fun getLambdaRolePolicies(): Array<String?> {
    val lambdaRolePolicies = arrayOfNulls<String>(5)
    lambdaRolePolicies[0] = "arn:aws:iam::aws:policy/AmazonSageMakerFullAccess"
    lambdaRolePolicies[1] = "arn:aws:iam::aws:policy/AmazonSQSFullAccess"
    lambdaRolePolicies[2] = "arn:aws:iam::aws:policy/service-role/" + "AmazonSageMakerGeospatialFullAccess"
    lambdaRolePolicies[3] = "arn:aws:iam::aws:policy/service-role/" + "AmazonSageMakerServiceCatalogProductsLambdaServiceRolePolicy"
    lambdaRolePolicies[4] = "arn:aws:iam::aws:policy/service-role/" + "AWSLambdaSQSQueueExecutionRole"
    return lambdaRolePolicies
}

fun getSageMakerRolePolicies(): Array<String?> {
    val sageMakerRolePolicies = arrayOfNulls<String>(3)
    sageMakerRolePolicies[0] = "arn:aws:iam::aws:policy/AmazonSageMakerFullAccess"
    sageMakerRolePolicies[1] = "arn:aws:iam::aws:policy/service-role/" + "AmazonSageMakerGeospatialFullAccess"
    sageMakerRolePolicies[2] = "arn:aws:iam::aws:policy/AmazonSQSFullAccess"
    return sageMakerRolePolicies
}