Use ASK to create Spark tasks

Procedure

1. Deploy the ack-spark-operator chart by using one of the following methods:
   • Log on to the Container Service for Kubernetes console. In the left-side navigation pane, choose Marketplace > App Catalog and select ack-spark-operator to deploy the chart.
   • Run the helm command to manually deploy the chart.
     Note The helm version must be V3 or later.

     #Create a service account
     kubectl create serviceaccount spark
     #Bind permissions
     kubectl create clusterrolebinding spark-role --clusterrole=edit --serviceaccount=default:spark --namespace=default
     #Install the operator
     helm repo add incubator http://storage.googleapis.com/kubernetes-charts-incubator
     helm install incubator/sparkoperator --namespace default  --set operatorImageName=registry.cn-hangzhou.aliyuncs.com/acs/spark-operator  --set operatorVersion=ack-2.4.5-latest  --generate-name

   After you deploy the chart, run the following command to check whether spark-operator is started:

   kubectl -n spark-operator get pod

   NAME                                  READY   STATUS      RESTARTS   AGE
   ack-spark-operator-7698586d7b-pvwln   1/1     Running     0          5m9s
   ack-spark-operator-init-26tvh         0/1     Completed   0          5m9s

2. Create the spark-pi.yaml file and copy the following content into the file:

   apiVersion: "sparkoperator.k8s.io/v1beta2"
   kind: SparkApplication
   metadata:
     name: spark-pi
     namespace: default
   spec:
     arguments:
     - "1000"
     sparkConf:
       "spark.scheduler.maxRegisteredResourcesWaitingTime": "3000s"
       "spark.kubernetes.allocation.batch.size": "1"
       "spark.rpc.askTimeout": "36000s"
       "spark.network.timeout": "36000s"
       "spark.rpc.lookupTimeout": "36000s"
       "spark.core.connection.ack.wait.timeout": "36000s"
       "spark.executor.heartbeatInterval": "10000s"
     type: Scala
     mode: cluster
     image: "registry.cn-shenzhen.aliyuncs.com/ringtail/spark-pi:0.4"
     imagePullPolicy: Always
     mainClass: org.apache.spark.examples.SparkPi
     mainApplicationFile: "local:///opt/spark/examples/jars/spark-examples_2.11-2.4.5.jar"
     sparkVersion: "2.4.5"
     restartPolicy:
       type: Never
     args:
     driver:
       cores: 4
       coreLimit: "4"
       annotations:
         k8s.aliyun.com/eci-image-cache: "true"
       memory: "6g"
       memoryOverhead: "2g"
       labels:
         version: 2.4.5
       serviceAccount: spark
     executor:
       annotations:
         k8s.aliyun.com/eci-image-cache: "true"
       cores: 2
       instances: 1
       memory: "3g"
       memoryOverhead: "1g"
       labels:
         version: 2.4.5

3. Run the following command to deploy a Spark task:

   kubectl apply -f spark-pi.yaml

4. Run the following commands to check the state of the pod.

   Run the following command to deploy a Spark task:

   kubectl apply -f spark-pi.yaml

   sparkapplication.sparkoperator.k8s.io/spark-pi created

   Run the following command to query the pod:

   kubectl get pod

   NAME              READY   STATUS    RESTARTS   AGE
   spark-pi-driver   1/1     Running   0          2m12s

   Run the following command to query the pod:

   kubectl get pod

   NAME              READY   STATUS      RESTARTS   AGE
   spark-pi-driver   0/1     Completed   0          2m54s

5. Run the following command to view the computing result of the Spark task:

   kubectl logs spark-pi-driver|grep Pi

   20/04/30 07:27:51 INFO DAGScheduler: ResultStage 0 (reduce at SparkPi.scala:38) finished in 11.031 s
   20/04/30 07:27:51 INFO DAGScheduler: Job 0 finished: reduce at SparkPi.scala:38, took 11.137920 s
   Pi is roughly 3.1414371514143715

6. Optional:To use a preemptible instance, add a preemptible instance annotation to the pod.
   For more information about how to add a preemptible instance annotation, see Use preemptible instances.