I am using Spark (2.4.0) on Kubernetes, if I run the following from a pod:
$SPARK_HOME/bin/spark-submit \
--master k8s://https://master-node \
--deploy-mode cluster \
--name spark-pi \
--class org.apache.spark.examples.SparkPi \
--conf spark.executor.instances=1 \
--conf spark.executor.cores=1 \
--conf spark.kubernetes.container.image=container-image \
local:///opt/spark/examples/jars/spark-examples_2.11-2.4.0.jar 1000000
and exit the process with ctrl+c, the application (driver/executors) keeps running. This is an issue that I have with streaming jobs, when the client pod terminates, the application keeps running.
Related
I have a 1 node Hadoop Cluster, I am submitting a spark job like this
spark-submit \
--class com.compq.scriptRunning \
--master local[*] \
--deploy-mode client \
--num-executors 3 \
--executor-cores 4 \
--executor-memory 21g \
--driver-cores 2 \
--driver-memory 5g \
--conf "spark.local.dir=/data/spark_tmp" \
--conf "spark.sql.shuffle.partitions=2000" \
--conf "spark.sql.inMemoryColumnarStorage.compressed=true" \
--conf "spark.sql.autoBroadcastJoinThreshold=200000" \
--conf "spark.speculation=false" \
--conf "spark.hadoop.mapreduce.map.speculative=false" \
--conf "spark.hadoop.mapreduce.reduce.speculative=false" \
--conf "spark.ui.port=8099" \
.....
Though I define 3 executors, I see only 1 executor in spark UI page running all the time. Can we have multiple executors running in parallel with
--master local[*] \
--deploy-mode client \
Its a on-prem, plain open source hadoop flavor installed in the cluster.
I tried changing master local to local[*] and playing around with deployment modes still, I could see only 1 executor running in spark UI
We are running Spark Cluster on Kubernetes. When we submited jobs as below, driver pod and executer pods were all up and running. However, the application failed to work as expected, the root cause we suspected is that it failed to find the source path as specified by parameter "py-files". As we witnessed, the driver pod has a warning MountVolume.Setup failed for volume "spark-conf-volume".
Would you please advise?
bin/spark-submit \
--master k8s://https://k8s-master-ip:6443 \
--deploy-mode cluster \
--name algo-vm \
--py-files hdfs://{our_ip}:9000/testdata/src.zip \
--conf spark.executor.instances=2 \
--conf spark.driver.port=10000 \
--conf spark.port.maxRetries=1 \
--conf spark.blockManager.port=20000 \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.kubernetes.container.image.pullPolicy=Always \
--conf spark.kubernetes.pyspark.pythonVersion=3 \
--conf spark.kubernetes.container.image={our_ip}/sutpc/k8s-spark-242-entry/spark-py:1.0 \
--jars hdfs://hdfs-master-ip:9000/jar/spark-sql-kafka-0-10_2.11-2.4.5.jar,hdfs://{our_ip}:9000/jar/kafka-clients-0.11.0.2.jar \
hdfs://{our_ip}:9000/testdata/spark_main.py
My Mac OS/X Version : 10.15.3
Minikube Version: 1.9.2
I start the minikube use the following command without any extra configuration.
minikube start --driver=virtualbox
--image-repository='registry.cn-hangzhou.aliyuncs.com/google_containers' --cpus 4 --memory 4096 --alsologtostderr
And I download spark-2.4.5-bin-hadoop2.7 from the Spark official website and build spark images by the following command
eval $(minikube docker-env)
./bin/docker-image-tool.sh -m -t 2.4.5 build
then I run Spark-pi using the follwing command within my local machine where store the Spark 2.4.5.
kubectl create serviceaccount spark
kubectl create clusterrolebinding spark-role --clusterrole=admin --serviceaccount=default:spark --namespace=default
./bin/spark-submit \
--master k8s://https://192.168.99.104:8443 \
--deploy-mode cluster \
--name spark-pi \
--class org.apache.spark.examples.SparkPi \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.executor.instances=1 \
--conf spark.kubernetes.container.image=spark:2.4.5 \
local:///opt/spark/examples/jars/spark-examples_2.11-2.4.5.jar
I get the following error
the full log can be found at full log
Can anyone explain this error and how to solve it?
Please check the Kubernetes version you launched with Minikube.
Spark v2.4.5 fabric8 Kubernetes client v4.6.1 is compatible with Kubernetes API up to 1.15.2 (refer answer).
You can launch the specific Kubernetes API version with Minikube by adding --kubernetes-version flag to minikube start command (refer docs).
Also the issue might be caused by OkHttp library bug described in the comment of this qustion.
Another spark image (from gcr.io/spark-operator/spark) worked for me, without downgrading the version of Kubernetes.
bin/spark-submit \
--master k8s://https://192.168.99.100:8443 \
--deploy-mode cluster \
--name spark-pi \
--class org.apache.spark.examples.SparkPi \
--conf spark.driver.cores=1 \
--conf spark.driver.memory=512m \
--conf spark.executor.instances=2 \
--conf spark.executor.memory=512m \
--conf spark.executor.cores=1 \
--conf spark.kubernetes.container.image=gcr.io/spark-operator/spark:v2.4.5 \
--conf spark.kubernetes.container.image.pullPolicy=IfNotPresent \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
local:///opt/spark/examples/jars/spark-examples_2.11-2.4.5.jar
I am trying to submit a spark job to a kubernetes cluster in cluster mode from a client in the cluster with --packages attribute to enable dependencies are downloaded by driver and executer but it is not working. It refers to path on submitting client. ( kubectl proxyis on )
here it the the submit options
/usr/local/bin/spark-submit \
--verbose \
--master=k8s://http://127.0.0.1:8001 \
--deploy-mode cluster \
--class org.apache.spark.examples.SparkPi \
--conf spark.kubernetes.authenticate.driver.serviceAccountName=spark \
--conf spark.kubernetes.namespace=spark \
--conf spark.kubernetes.container.image= <...> \
--conf spark.executor.instances=2 \
--conf spark.kubernetes.pyspark.pythonVersion=3 \
--conf spark.kubernetes.driver.secretKeyRef.AWS_ACCESS_KEY_ID=datazone-s3-secret:AWS_ACCESS_KEY_ID \
--conf spark.kubernetes.driver.secretKeyRef.AWS_SECRET_ACCESS_KEY=datazone-s3-secret:AWS_SECRET_ACCESS_KEY \
--packages com.amazonaws:aws-java-sdk:1.7.4,org.apache.hadoop:hadoop-aws:2.7.3 \
s3.py 10
On the logs I can see that packages are referring my local file system.
Spark config:
(spark.kubernetes.namespace,spark)
(spark.jars,file:///Users/<my username>/.ivy2/jars/com.amazonaws_aws-java-sdk-1.7.4.jar,file:///Users/<my username>/.ivy2/jars/org.apache.hadoop_hadoop-aws-2.7.3.jar,file:///Users/<my username>/.ivy2/jars/joda-time_joda-time-2.10.5.jar, ....
Did someone face this problem?
I am running a sample spark job in kubernetes cluster with following command:
bin/spark-submit \
--deploy-mode cluster \
--class org.apache.spark.examples.SparkPi \
--master k8s://https://XXXXX \
--kubernetes-namespace sidartha-spark-cluster \
--conf spark.executor.instances=2 \
--conf spark.app.name=spark-pi \
--conf spark.kubernetes.driver.docker.image=kubespark/spark-driver:v2.1.0-kubernetes-0.1.0-rc1 \
--conf spark.kubernetes.executor.docker.image=kubespark/spark-executor:v2.1.0-kubernetes-0.1.0-rc1 \
examples/jars/spark-examples_2.11-2.1.0-k8s-0.1.0-SNAPSHOT.jar 1000
I am building the spark from apache-spark-on-k8s
I am not able find the jar for org.apache.spark.deploy.kubernetes.submit.Client Class.
This issue is resolved. We need to build the spark/resource-manager/kubernetes from the source.