charts/bitnami/spark

Apache Spark packaged by Bitnami

Apache Spark is a high-performance engine for large-scale computing tasks, such as data processing, machine learning and real-time data streaming. It includes APIs for Java, Python, Scala and R.

Overview of Apache Spark

Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

TL;DR

$ helm repo add bitnami https://charts.bitnami.com/bitnami
$ helm install my-release bitnami/spark

Introduction

This chart bootstraps an Apache Spark deployment on a Kubernetes cluster using the Helm package manager.

Apache Spark includes APIs for Java, Python, Scala and R.

Bitnami charts can be used with Kubeapps for deployment and management of Helm Charts in clusters. This Helm chart has been tested on top of Bitnami Kubernetes Production Runtime (BKPR). Deploy BKPR to get automated TLS certificates, logging and monitoring for your applications.

Prerequisites

• Kubernetes 1.19+
• Helm 3.2.0+

Installing the Chart

To install the chart with the release name my-release:

$ helm repo add bitnami https://charts.bitnami.com/bitnami
$ helm install my-release bitnami/spark

These commands deploy Apache Spark on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation.

Tip

: List all releases using helm list

Uninstalling the Chart

To uninstall/delete the my-release statefulset:

$ helm delete my-release

The command removes all the Kubernetes components associated with the chart and deletes the release. Use the option --purge to delete all persistent volumes too.

Parameters

Global parameters

Name	Description	Value
global.imageRegistry	Global Docker image registry	""
global.imagePullSecrets	Global Docker registry secret names as an array	[]

Common parameters

Name	Description	Value
kubeVersion	Force target Kubernetes version (using Helm capabilities if not set)	""
nameOverride	String to partially override common.names.fullname template (will maintain the release name)	""
fullnameOverride	String to fully override common.names.fullname template	""
extraDeploy	Array of extra objects to deploy with the release	[]
diagnosticMode.enabled	Enable diagnostic mode (all probes will be disabled and the command will be overridden)	false
diagnosticMode.command	Command to override all containers in the deployment	["sleep"]
diagnosticMode.args	Args to override all containers in the deployment	["infinity"]

Spark parameters

Name	Description	Value
image.registry	Spark image registry	docker.io
image.repository	Spark image repository	bitnami/spark
image.tag	Spark image tag (immutable tags are recommended)	3.2.0-debian-10-r73
image.pullPolicy	Spark image pull policy	IfNotPresent
image.pullSecrets	Specify docker-registry secret names as an array	[]
image.debug	Enable image debug mode	false
hostNetwork	Enable HOST Network	false

RBAC parameters

Name	Description	Value
serviceAccount.create	Enable the creation of a ServiceAccount for Spark pods	true
serviceAccount.name	The name of the ServiceAccount to use.	""
serviceAccount.annotations	Annotations for Spark Service Account	{}
serviceAccount.automountServiceAccountToken	Automount API credentials for a service account.	true

Spark master parameters

Name	Description	Value
master.configurationConfigMap	Set a custom configuration by using an existing configMap with the configuration file.	""
master.webPort	Specify the port where the web interface will listen on the master over HTTP	8080
master.webPortHttps	Specify the port where the web interface will listen on the master over HTTPS	8480
master.clusterPort	Specify the port where the master listens to communicate with workers	7077
master.hostAliases	Deployment pod host aliases	[]
master.daemonMemoryLimit	Set the memory limit for the master daemon	""
master.configOptions	Use a string to set the config options for in the form "-Dx=y"	""
master.extraEnvVars	Extra environment variables to pass to the master container	[]
master.securityContext.enabled	Enable security context	true
master.securityContext.fsGroup	Group ID for the container	1001
master.securityContext.runAsUser	User ID for the container	1001
master.securityContext.runAsGroup	Group ID for the container	0
master.securityContext.seLinuxOptions	SELinux options for the container	{}
master.podAnnotations	Annotations for pods in StatefulSet	{}
master.extraPodLabels	Extra labels for pods in StatefulSet	{}
master.podAffinityPreset	Spark master pod affinity preset. Ignored if master.affinity is set. Allowed values: soft or hard	""
master.podAntiAffinityPreset	Spark master pod anti-affinity preset. Ignored if master.affinity is set. Allowed values: soft or hard	soft
master.nodeAffinityPreset.type	Spark master node affinity preset type. Ignored if master.affinity is set. Allowed values: soft or hard	""
master.nodeAffinityPreset.key	Spark master node label key to match Ignored if master.affinity is set.	""
master.nodeAffinityPreset.values	Spark master node label values to match. Ignored if master.affinity is set.	[]
master.affinity	Spark master affinity for pod assignment	{}
master.nodeSelector	Spark master node labels for pod assignment	{}
master.tolerations	Spark master tolerations for pod assignment	[]
master.resources.limits	The resources limits for the container	{}
master.resources.requests	The requested resources for the container	{}
master.livenessProbe.enabled	Enable livenessProbe	true
master.livenessProbe.initialDelaySeconds	Initial delay seconds for livenessProbe	180
master.livenessProbe.periodSeconds	Period seconds for livenessProbe	20
master.livenessProbe.timeoutSeconds	Timeout seconds for livenessProbe	5
master.livenessProbe.failureThreshold	Failure threshold for livenessProbe	6
master.livenessProbe.successThreshold	Success threshold for livenessProbe	1
master.readinessProbe.enabled	Enable readinessProbe	true
master.readinessProbe.initialDelaySeconds	Initial delay seconds for readinessProbe	30
master.readinessProbe.periodSeconds	Period seconds for readinessProbe	10
master.readinessProbe.timeoutSeconds	Timeout seconds for readinessProbe	5
master.readinessProbe.failureThreshold	Failure threshold for readinessProbe	6
master.readinessProbe.successThreshold	Success threshold for readinessProbe	1
master.initContainers	Add initContainers to the master pods.	[]

Spark worker parameters

Name	Description	Value
worker.configurationConfigMap	Set a custom configuration by using an existing configMap with the configuration file.	""
worker.webPort	Specify the port where the web interface will listen on the worker over HTTP	8081
worker.webPortHttps	Specify the port where the web interface will listen on the worker over HTTPS	8481
worker.clusterPort	Specify the port where the worker listens to communicate with the master	""
worker.hostAliases	Add deployment host aliases	[]
worker.extraPorts	Specify the port where the running jobs inside the workers listens	[]
worker.daemonMemoryLimit	Set the memory limit for the worker daemon	""
worker.memoryLimit	Set the maximum memory the worker is allowed to use	""
worker.coreLimit	Se the maximum number of cores that the worker can use	""
worker.dir	Set a custom working directory for the application	""
worker.javaOptions	Set options for the JVM in the form -Dx=y	""
worker.configOptions	Set extra options to configure the worker in the form -Dx=y	""
worker.extraEnvVars	An array to add extra env vars	[]
worker.replicaCount	Number of spark workers (will be the minimum number when autoscaling is enabled)	2
worker.podManagementPolicy	Statefulset Pod Management Policy Type	OrderedReady
worker.securityContext.enabled	Enable security context	true
worker.securityContext.fsGroup	Group ID for the container	1001
worker.securityContext.runAsUser	User ID for the container	1001
worker.securityContext.runAsGroup	Group ID for the container	0
worker.securityContext.seLinuxOptions	SELinux options for the container	{}
worker.podAnnotations	Annotations for pods in StatefulSet	{}
worker.extraPodLabels	Extra labels for pods in StatefulSet	{}
worker.podAffinityPreset	Spark worker pod affinity preset. Ignored if worker.affinity is set. Allowed values: soft or hard	""
worker.podAntiAffinityPreset	Spark worker pod anti-affinity preset. Ignored if worker.affinity is set. Allowed values: soft or hard	soft
worker.nodeAffinityPreset.type	Spark worker node affinity preset type. Ignored if worker.affinity is set. Allowed values: soft or hard	""
worker.nodeAffinityPreset.key	Spark worker node label key to match Ignored if worker.affinity is set.	""
worker.nodeAffinityPreset.values	Spark worker node label values to match. Ignored if worker.affinity is set.	[]
worker.affinity	Spark worker affinity for pod assignment	{}
worker.nodeSelector	Spark worker node labels for pod assignment	{}
worker.tolerations	Spark worker tolerations for pod assignment	[]
worker.resources.limits	The resources limits for the container	{}
worker.resources.requests	The requested resources for the container	{}
worker.livenessProbe.enabled	Enable livenessProbe	true
worker.livenessProbe.initialDelaySeconds	Initial delay seconds for livenessProbe	180
worker.livenessProbe.periodSeconds	Period seconds for livenessProbe	20
worker.livenessProbe.timeoutSeconds	Timeout seconds for livenessProbe	5
worker.livenessProbe.failureThreshold	Failure threshold for livenessProbe	6
worker.livenessProbe.successThreshold	Success threshold for livenessProbe	1
worker.readinessProbe.enabled	Enable readinessProbe	true
worker.readinessProbe.initialDelaySeconds	Initial delay seconds for readinessProbe	30
worker.readinessProbe.periodSeconds	Period seconds for readinessProbe	10
worker.readinessProbe.timeoutSeconds	Timeout seconds for readinessProbe	5
worker.readinessProbe.failureThreshold	Failure threshold for readinessProbe	6
worker.readinessProbe.successThreshold	Success threshold for readinessProbe	1
worker.initContainers	Add initContainers to the master pods.	[]
worker.autoscaling.enabled	Enable replica autoscaling depending on CPU	false
worker.autoscaling.CpuTargetPercentage	Kubernetes HPA CPU target percentage	50
worker.autoscaling.replicasMax	Maximum number of workers when using autoscaling	5

Security parameters

Name	Description	Value
security.passwordsSecretName	Name of the secret that contains all the passwords	""
security.rpc.authenticationEnabled	Enable the RPC authentication	false
security.rpc.encryptionEnabled	Enable the encryption for RPC	false
security.storageEncryptionEnabled	Enables local storage encryption	false
security.certificatesSecretName	Name of the secret that contains the certificates.	""
security.ssl.enabled	Enable the SSL configuration	false
security.ssl.needClientAuth	Enable the client authentication	false
security.ssl.protocol	Set the SSL protocol	TLSv1.2
security.ssl.existingSecret	Name of the existing secret containing the TLS certificates	""
security.ssl.autoGenerated	Create self-signed TLS certificates. Currently only supports PEM certificates	false
security.ssl.keystorePassword	Set the password of the JKS Keystore	""
security.ssl.truststorePassword	Truststore password.	""
security.ssl.resources.limits	The resources limits for the container	{}
security.ssl.resources.requests	The requested resources for the container	{}

Traffic Exposure parameters

Name	Description	Value
service.type	Kubernetes Service type	ClusterIP
service.clusterPort	Spark cluster port	7077
service.webPort	Spark client port for HTTP	80
service.webPortHttps	Spark client port for HTTPS	443
service.nodePorts.cluster	Kubernetes cluster node port	""
service.nodePorts.web	Kubernetes web node port for HTTP	""
service.nodePorts.webHttps	Kubernetes web node port for HTTPS	""
service.loadBalancerIP	Load balancer IP if spark service type is LoadBalancer	""
service.annotations	Annotations for spark service	{}
ingress.enabled	Enable ingress controller resource	false
ingress.pathType	Ingress path type	ImplementationSpecific
ingress.apiVersion	Force Ingress API version (automatically detected if not set)	""
ingress.hostname	Default host for the ingress resource	spark.local
ingress.path	The Path to Spark. You may need to set this to '/*' in order to use this with ALB ingress controllers.	/
ingress.annotations	Additional annotations for the Ingress resource. To enable certificate autogeneration, place here your cert-manager annotations.	{}
ingress.tls	Enable TLS configuration for the hostname defined at ingress.hostname parameter	false
ingress.extraHosts	The list of additional hostnames to be covered with this ingress record.	[]
ingress.extraPaths	Any additional arbitrary paths that may need to be added to the ingress under the main host.	[]
ingress.extraTls	The tls configuration for additional hostnames to be covered with this ingress record.	[]
ingress.secrets	If you're providing your own certificates, please use this to add the certificates as secrets	[]

Metrics parameters

Name	Description	Value
metrics.enabled	Start a side-car prometheus exporter	false
metrics.masterAnnotations	Annotations for the Prometheus metrics on master nodes	{}
metrics.workerAnnotations	Annotations for the Prometheus metrics on worker nodes	{}
metrics.podMonitor.enabled	If the operator is installed in your cluster, set to true to create a PodMonitor Resource for scraping metrics using PrometheusOperator	false
metrics.podMonitor.extraMetricsEndpoints	Add metrics endpoints for monitoring the jobs running in the worker nodes	[]
metrics.podMonitor.namespace	Specify the namespace in which the podMonitor resource will be created	""
metrics.podMonitor.interval	Specify the interval at which metrics should be scraped	30s
metrics.podMonitor.scrapeTimeout	Specify the timeout after which the scrape is ended	""
metrics.podMonitor.additionalLabels	Additional labels that can be used so PodMonitors will be discovered by Prometheus	{}
metrics.prometheusRule.enabled	Set this to true to create prometheusRules for Prometheus	false
metrics.prometheusRule.namespace	Namespace where the prometheusRules resource should be created	""
metrics.prometheusRule.additionalLabels	Additional labels that can be used so prometheusRules will be discovered by Prometheus	{}
metrics.prometheusRule.rules	Custom Prometheus rules	[]

Specify each parameter using the --set key=value[,key=value] argument to helm install. For example,

$ helm install my-release \
  --set master.webPort=8081 bitnami/spark

The above command sets the spark master web port to 8081.

Alternatively, a YAML file that specifies the values for the parameters can be provided while installing the chart. For example,

$ helm install my-release -f values.yaml bitnami/spark

Tip

: You can use the default values.yaml

Configuration and installation details

Rolling vs Immutable tags

It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.

Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.

Define custom configuration

To use a custom configuration, a ConfigMap should be created with the spark-env.sh file inside the ConfigMap. The ConfigMap name must be provided at deployment time.

To set the configuration on the master use master.configurationConfigMap=configMapName. To set the configuration on the worker, use worker.configurationConfigMap=configMapName.

These values can be set at the same time in a single ConfigMap or using two ConfigMaps. An additional spark-defaults.conf file can be provided in the ConfigMap. You can use both files or one without the other.

Submit an application

To submit an application to the Apache Spark cluster, use the spark-submit script, which is available at https://github.com/apache/spark/tree/master/bin.

The command below illustrates the process of deploying one of the sample applications included with Apache Spark. Replace the k8s-apiserver-host, k8s-apiserver-port, spark-master-svc, and spark-master-port placeholders with the correct master host/IP address and port for your deployment.

$ ./bin/spark-submit \
    --class org.apache.spark.examples.SparkPi \
    --conf spark.kubernetes.container.image=bitnami/spark:3 \
    --master k8s://https://k8s-apiserver-host:k8s-apiserver-port \
    --conf spark.kubernetes.driverEnv.SPARK_MASTER_URL=spark://spark-master-svc:spark-master-port \
    --deploy-mode cluster \
    ./examples/jars/spark-examples_2.12-3.2.0.jar 1000

This command example assumes that you have downloaded a Spark binary distribution, which can be found at Download Apache Spark.

For a complete walkthrough of the process using a custom application, refer to the detailed Apache Spark tutorial or Spark's guide to Running Spark on Kubernetes.

Be aware that it is currently not possible to submit an application to a standalone cluster if RPC authentication is configured. Learn more about the issue.

Configuring Spark Master as reverse proxy

Spark offers configuration to enable running Spark Master as reverse proxy for worker and application UIs. This can be useful as the Spark Master UI may otherwise use private IPv4 addresses for links to Spark workers and Spark apps.

Coupled with ingress configuration, you can set master.configOptions and worker.configOptions to tell Spark to reverse proxy the worker and application UIs to enable access without requiring direct access to their hosts:

master:
  configOptions:
    -Dspark.ui.reverseProxy=true
    -Dspark.ui.reverseProxyUrl=https://spark.your-domain.com
worker:
  configOptions:
    -Dspark.ui.reverseProxy=true
    -Dspark.ui.reverseProxyUrl=https://spark.your-domain.com
ingress:
  enabled: true
  hostname: spark.your-domain.com

See the Spark Configuration docs for detail on the parameters.

Configure security for Apache Spark

Configure SSL communication

In order to enable secure transport between workers and master, deploy the Helm chart with the ssl.enabled=true chart parameter.

Create certificate and password secrets

It is necessary to create two secrets for the passwords and certificates. The names of the two secrets should be configured using the security.passwordsSecretName and security.ssl.existingSecret chart parameters.

The keys for the certificate secret must be named spark-keystore.jks and spark-truststore.jks, and the content must be text in JKS format. Use this script to generate certificates for test purposes if required.

The secret for passwords should have three keys: rpc-authentication-secret, ssl-keystore-password and ssl-truststore-password.

Refer to the chart documentation for more details on configuring security and an example.

It is currently not possible to submit an application to a standalone cluster if RPC authentication is configured. Learn more about this issue.

Set Pod affinity

This chart allows you to set your custom affinity using the XXX.affinity parameter(s). Find more information about Pod affinity in the Kubernetes documentation.

As an alternative, you can use the preset configurations for pod affinity, pod anti-affinity, and node affinity available at the bitnami/common chart. To do so, set the XXX.podAffinityPreset, XXX.podAntiAffinityPreset, or XXX.nodeAffinityPreset parameters.

Troubleshooting

Find more information about how to deal with common errors related to Bitnami's Helm charts in this troubleshooting guide.

Upgrading

To 5.0.0

This version standardizes the way of defining Ingress rules. When configuring a single hostname for the Ingress rule, set the ingress.hostname value. When defining more than one, set the ingress.extraHosts array. Apart from this case, no issues are expected to appear when upgrading.

To 4.0.0

On November 13, 2020, Helm v2 support formally ended. This major version is the result of the required changes applied to the Helm Chart to be able to incorporate the different features added in Helm v3 and to be consistent with the Helm project itself regarding the Helm v2 EOL.

Learn more about this change and related upgrade considerations.

To 3.0.0

• This version introduces bitnami/common, a library chart as a dependency. More documentation about this new utility could be found here. Please, make sure that you have updated the chart dependencies before executing any upgrade.

• Spark container images are updated to use Hadoop 3.2.x: Notable Changes: 3.0.0-debian-10-r44

Note: Backwards compatibility is not guaranteed due to the above mentioned changes. Please make sure your workloads are compatible with the new version of Hadoop before upgrading. Backups are always recommended before any upgrade operation.

License

Copyright © 2022 Bitnami

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.