Configuração de perfis do IAM para contas de serviço (IRSA) do spark-submit

Crie um arquivo de política para permitir acesso somente leitura ao objeto do Amazon S3 do qual você fez upload:

cat >my-policy.json <<EOF
{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:GetObject",
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::<my-spark-jar-bucket>",
                "arn:aws:s3:::<my-spark-jar-bucket>/*"
            ]
        }
    ]
}
EOF

Crie a política do IAM.

aws iam create-policy --policy-name my-policy --policy-document file://my-policy.json

Crie um perfil do IAM e associe-o a uma conta de serviço do Kubernetes para o driver do Spark

eksctl create iamserviceaccount --name my-spark-driver-sa --namespace spark-operator \
--cluster my-cluster --role-name "my-role" \
--attach-policy-arn arn:aws:iam::111122223333:policy/my-policy --approve

Crie um arquivo YAML com as permissões obrigatórias para a conta de serviço do driver do Spark:

cat >spark-rbac.yaml <<EOF
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  namespace: default
  name: emr-containers-role-spark
rules:
- apiGroups:
  - ""
  resources:
  - pods
  verbs:
  - "*"
- apiGroups:
  - ""
  resources:
  - services
  verbs:
  - "*"
- apiGroups:
  - ""
  resources:
  - configmaps
  verbs:
  - "*"
- apiGroups:
  - ""
  resources:
  - persistentvolumeclaims
  verbs:
  - "*"
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: spark-role-binding
  namespace: default
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: Role
  name: emr-containers-role-spark
subjects:
- kind: ServiceAccount
  name: emr-containers-sa-spark
  namespace: default
EOF

Aplique as configurações de associação de perfil do cluster.

kubectl apply -f spark-rbac.yaml

O comando kubectl deve retornar a confirmação da conta criada.

serviceaccount/emr-containers-sa-spark created
clusterrolebinding.rbac.authorization.k8s.io/emr-containers-role-spark configured

Certifique-se de ter concluído as etapas em Setting up spark-submit for Amazon EMR on EKS.

Defina os valores para as seguintes variáveis ​​de ambiente:

export SPARK_HOME=spark-home
export MASTER_URL=k8s://Amazon EKS-cluster-endpoint

Agora, envie a aplicação do Spark com o seguinte comando:

$SPARK_HOME/bin/spark-submit \
 --class org.apache.spark.examples.SparkPi \
 --master $MASTER_URL \
 --conf spark.kubernetes.container.image=895885662937.dkr.ecr.us-west-2.amazonaws.com/spark/emr-6.15.0:latest \
 --conf spark.kubernetes.authenticate.driver.serviceAccountName=emr-containers-sa-spark \
 --deploy-mode cluster \
 --conf spark.kubernetes.namespace=default \
 --conf "spark.driver.extraClassPath=/usr/lib/hadoop-lzo/lib/*:/usr/lib/hadoop/hadoop-aws.jar:/usr/share/aws/aws-java-sdk/*:/usr/share/aws/emr/emrfs/conf:/usr/share/aws/emr/emrfs/lib/*:/usr/share/aws/emr/emrfs/auxlib/*:/usr/share/aws/emr/security/conf:/usr/share/aws/emr/security/lib/*:/usr/share/aws/hmclient/lib/aws-glue-datacatalog-spark-client.jar:/usr/share/java/Hive-JSON-Serde/hive-openx-serde.jar:/usr/share/aws/sagemaker-spark-sdk/lib/sagemaker-spark-sdk.jar:/home/hadoop/extrajars/*" \
 --conf "spark.driver.extraLibraryPath=/usr/lib/hadoop/lib/native:/usr/lib/hadoop-lzo/lib/native:/docker/usr/lib/hadoop/lib/native:/docker/usr/lib/hadoop-lzo/lib/native" \
 --conf "spark.executor.extraClassPath=/usr/lib/hadoop-lzo/lib/*:/usr/lib/hadoop/hadoop-aws.jar:/usr/share/aws/aws-java-sdk/*:/usr/share/aws/emr/emrfs/conf:/usr/share/aws/emr/emrfs/lib/*:/usr/share/aws/emr/emrfs/auxlib/*:/usr/share/aws/emr/security/conf:/usr/share/aws/emr/security/lib/*:/usr/share/aws/hmclient/lib/aws-glue-datacatalog-spark-client.jar:/usr/share/java/Hive-JSON-Serde/hive-openx-serde.jar:/usr/share/aws/sagemaker-spark-sdk/lib/sagemaker-spark-sdk.jar:/home/hadoop/extrajars/*" \
 --conf "spark.executor.extraLibraryPath=/usr/lib/hadoop/lib/native:/usr/lib/hadoop-lzo/lib/native:/docker/usr/lib/hadoop/lib/native:/docker/usr/lib/hadoop-lzo/lib/native" \
 --conf spark.hadoop.fs.s3.customAWSCredentialsProvider=com.amazonaws.auth.WebIdentityTokenCredentialsProvider \
 --conf spark.hadoop.fs.s3.impl=com.amazon.ws.emr.hadoop.fs.EmrFileSystem \
 --conf spark.hadoop.fs.AbstractFileSystem.s3.impl=org.apache.hadoop.fs.s3.EMRFSDelegate \
 --conf spark.hadoop.fs.s3.buffer.dir=/mnt/s3 \
 --conf spark.hadoop.fs.s3.getObject.initialSocketTimeoutMilliseconds="2000" \
 --conf spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version.emr_internal_use_only.EmrFileSystem="2" \
 --conf spark.hadoop.mapreduce.fileoutputcommitter.cleanup-failures.ignored.emr_internal_use_only.EmrFileSystem="true" \
 s3://my-pod-bucket/spark-examples.jar 20

Depois que o driver do Spark terminar o trabalho do Spark, você verá uma linha de log no final do envio indicando que o trabalho do Spark foi concluído.

23/11/24 17:02:14 INFO LoggingPodStatusWatcherImpl: Application org.apache.spark.examples.SparkPi with submission ID default:org-apache-spark-examples-sparkpi-4980808c03ff3115-driver finished
23/11/24 17:02:14 INFO ShutdownHookManager: Shutdown hook called