将 Kubernetes 中的 Spark Driver 和 Worker 标准输出 stderr 日志暴露给历史服务器

Question

I'm using Spark 3.0.0 with Kubernetes master. I am using a cluster mode to rung the spark job. Please find the spark submit command as below

./spark-submit \
--master=k8s://https://api.k8s.my-domain.com \
--deploy-mode cluster \
--name sparkle \
--num-executors 2 \
--executor-cores 2 \
--executor-memory 2g \
--driver-memory 2g \
--class com.myorg.sparkle.Sparkle \
--conf spark.driver.extraJavaOptions=-Dlog4j.configuration=file:/opt/spark/conf/log4j.properties \
--conf spark.executor.extraJavaOptions=-Dlog4j.configuration=file:/opt/spark/conf/log4j.properties \
--conf spark.kubernetes.submission.waitAppCompletion=false \
--conf spark.kubernetes.allocation.batch.delay=10s \
--conf spark.kubernetes.appKillPodDeletionGracePeriod=20s \
--conf spark.kubernetes.node.selector.workloadType=spark \
--conf spark.kubernetes.driver.pod.name=sparkle-driver \
--conf spark.kubernetes.container.image=custom-registry/spark:latest \
--conf spark.kubernetes.namespace=spark \
--conf spark.eventLog.dir='s3a://my-bucket/spark-logs' \
--conf spark.history.fs.logDirectory='s3a://my-bucket/spark-logs' \
--conf spark.eventLog.enabled='true' \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.kubernetes.authenticate.executor.serviceAccountName=spark \
--conf spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem \
--conf spark.hadoop.fs.s3a.aws.credentials.provider=com.amazonaws.auth.WebIdentityTokenCredentialsProvider \
--conf spark.kubernetes.driver.annotation.iam.amazonaws.com/role=K8sRoleSpark \
--conf spark.kubernetes.executor.annotation.iam.amazonaws.com/role=K8sRoleSpark \
--conf spark.kubernetes.driver.secretKeyRef.AWS_ACCESS_KEY_ID=aws-secrets:key \
--conf spark.kubernetes.driver.secretKeyRef.AWS_SECRET_ACCESS_KEY=aws-secrets:secret \
--conf spark.kubernetes.executor.secretKeyRef.AWS_ACCESS_KEY_ID=aws-secrets:key \
--conf spark.kubernetes.executor.secretKeyRef.AWS_SECRET_ACCESS_KEY=aws-secrets:secret \
--conf spark.hadoop.fs.s3a.endpoint=s3.ap-south-1.amazonaws.com \
--conf spark.hadoop.com.amazonaws.services.s3.enableV4=true \
--conf spark.yarn.maxAppAttempts=4 \
--conf spark.yarn.am.attemptFailuresValidityInterval=1h \
s3a://dp-spark-jobs/sparkle/jars/sparkle.jar \
--commonConfigPath https://my-bucket.s3.ap-south-1.amazonaws.com/sparkle/configs/prod_main_configs.yaml \
--jobConfigPath https://my-bucket.s3.ap-south-1.amazonaws.com/sparkle/configs/cc_configs.yaml \
--filePathDate 2021-03-29 20000

I have hosted a different pod running history server with the same image. The history server is able to read all the event logs and shows details. The job is executed successfully.

I do not see driver pod and worker pod's stdout and stderr logs in History server. How can I enable it?

Similar to this question

Answer 1

Unfortunately, it appears that there is no way for the driver-scoped logs to be piped to the spark-submit scope. From the docs :

Logs can be accessed using the Kubernetes API and the kubectl CLI. When a Spark application is running, it's possible to stream logs from the application using:

kubectl -n=<namespace> logs -f <driver-pod-name>