Configure SSL for Spark on Kubernetes using CLI

Prerequisites

  • An ADH cluster (4.2.0 or later) is installed and running.

  • Spark operator is deployed in Kubernetes according to the instruction.

  • SSL is enabled for the ADH cluster.

Submit Spark application

  1. Prepare the hadoop_conf.yaml Hadoop configuration file (required only if the application accesses data managed by these services; for a self-contained JAR the hadoop block can be omitted):

    hadoop_conf.yaml
    sites:
      core:
        fs.defaultFS: hdfs://adh
        hadoop.security.authentication: simple
        dfs.client.failover.proxy.provider.adh: org.apache.hadoop.hdfs.server.namenode.ha.ObserverReadProxyProvider
        dfs.ha.namenodes.adh: nn_tsn-adh-k8s-1,nn_tsn-adh-k8s-3
        dfs.namenode.rpc-address.adh.nn_tsn-adh-k8s-1: tsn-adh-k8s-1.ru-central1.internal:8020
        dfs.namenode.rpc-address.adh.nn_tsn-adh-k8s-3: tsn-adh-k8s-3.ru-central1.internal:8020
        dfs.nameservices: adh
        hadoop.ssl.enabled: true
      hdfs:
        dfs.client.read.shortcircuit: false
      ozone:
        ozone.om.address.adh.om_tsn-adh-k8s-1: tsn-adh-k8s-1.ru-central1.internal:9862
        ozone.om.address.adh.om_tsn-adh-k8s-2: tsn-adh-k8s-2.ru-central1.internal:9862
        ozone.om.address.adh.om_tsn-adh-k8s-3: tsn-adh-k8s-3.ru-central1.internal:9862
        ozone.om.nodes.adh: om_tsn-adh-k8s-1,om_tsn-adh-k8s-2,om_tsn-adh-k8s-3
        ozone.om.service.ids: adhom
      hive:
        hive.metastore.sasl.enabled: false
        hive.metastore.uris: thrift://tsn-adh-k8s-1.ru-central1.internal:9083
        metastore.use.SSL: true
  2. Initialize a Spark application:

    $ ./adc init --spark-application --hadoop-file hadoop_conf.yaml -o spark-application.yaml

    This operation creates the spark-application.yaml file with a configuration template.

  3. Edit the configuration file to your needs:

    spark-application.yaml
    apiVersion: adc.arenadata.io/v1alpha1
    kind: SparkApplication
    metadata:
      name: spark-application
      namespace: spark-applications (1)
    spec:
      image: hub.arenadata.io/adc-enterprise/spark3:<tag> (2)
    
      ## Image pull secret for a private registry.
      ## Set 'externalSecretName' to reference an existing Secret,
      ## or set 'credentials' and optionally 'secretName' to let the CLI create one.
      #imagePullSecret:
      #  # Use a Secret managed outside ADC.
      #  externalSecretName: existing-registry-secret
      #
      #  ## Or let ADC create the Secret.
      #  #secretName: custom-registry-secret
      #
      #  #credentials:
      #  #  registry: registry.example.com
      #  #  username: user
      #  #  password: pass
    
      hadoop: (3)
        core:
          dfs.client.failover.proxy.provider.adh: org.apache.hadoop.hdfs.server.namenode.ha.ObserverReadProxyProvider
          dfs.ha.namenodes.adh: nn_tsn-adh-k8s-1,nn_tsn-adh-k8s-3
          dfs.namenode.rpc-address.adh.nn_tsn-adh-k8s-1: tsn-adh-k8s-1.ru-central1.internal:8020
          dfs.namenode.rpc-address.adh.nn_tsn-adh-k8s-3: tsn-adh-k8s-3.ru-central1.internal:8020
          dfs.nameservices: adh
          fs.defaultFS: hdfs://adh
          hadoop.security.authentication: simple
          hadoop.ssl.enabled: "true"
        hdfs:
          dfs.client.read.shortcircuit: "false"
        hive:
          hive.metastore.sasl.enabled: "false"
          hive.metastore.uris: thrift://tsn-adh-k8s-1.ru-central1.internal:9083
          metastore.truststore.password: bigdata
          metastore.truststore.path: /etc/ssl/truststore.jks
          metastore.use.SSL: "true"
        ozone:
          ozone.om.address.adh.om_tsn-adh-k8s-1: tsn-adh-k8s-1.ru-central1.internal:9862
          ozone.om.address.adh.om_tsn-adh-k8s-2: tsn-adh-k8s-2.ru-central1.internal:9862
          ozone.om.address.adh.om_tsn-adh-k8s-3: tsn-adh-k8s-3.ru-central1.internal:9862
          ozone.om.nodes.adh: om_tsn-adh-k8s-1,om_tsn-adh-k8s-2,om_tsn-adh-k8s-3
          ozone.om.service.ids: adhom
    
      ## Kerberos configuration for authentication.
      #kerberos:
      #  principal: user@EXAMPLE.COM
      #
      #  # CLI reads the local files and creates the kerberos-ccache Secret on 'adc apply'.
      #  # Alternative - keytab mode: replace this block with:
      #  #   keytab:
      #  #     secretName: <name-of-existing-keytab-secret>
      #  ticketCache:
      #    #secretName: custom-ticket-cache
      #    externalSecretName: existing-ticket-cache
      #    #ticketPath: /tmp/krb5cc_1000
      #    #krb5ConfPath: /etc/krb5.conf
    
      ## Ranger plugin configuration.
      ## Uncomment and fill the lines below. adc apply derives the rest.
      #ranger:
      #  # fill ranger.plugin.spark.policy.rest.url below with Ranger endpoint, e.g. https://adps-adc.ru-central1.internal:6182
      #  # fill ranger.plugin.spark.service.name below with Ranger service name you want to use for product, e.g. adc_spark_id_1
      #  security:
      #    ranger.plugin.spark.policy.rest.url: ""
      #    ranger.plugin.spark.service.name: ""
      #
      #  # fill xasecure.audit.destination.solr.zookeepers below with Zookeepers endpoints to resolve solr service, e.g. adps-adc.ru-central1.internal:2181/Arenadata.Hadoop-2.solr.server
      #  audit:
      #    xasecure.audit.destination.solr.zookeepers: ""
      #
      #  # Local Ranger files 'adc apply' writes into the configs Secret.
      #  # Relative paths are resolved against the config file.
      #  files:
      #    jceksStorePath: /path/to/ranger.jceks
    
      ## Java KeyStore/TrustStore certificate configuration.
      ## Set externalSecretName to reference an existing Secret,
      ## or set files and optional secretName to have ADC create it.
      ssl: (4)
      #  ## Name of the Secret containing Java keystores.
        secretName: ssl-secret
      #  externalSecretName: existing-ssl-secret
      #
      #  # Key in the Secret containing the truststore file.
        trustStoreKey: truststore.jks
      #
      #  ## Password for the truststore (optional).
        trustStorePassword: bigdata
      #
      #  ## Key in the Secret containing the keystore file (optional).
      #  #keyStoreKey: keystore.jks
      #
      #  ## Password for the keystore (optional).
      #  #keyStorePassword: bigdata
      #
      #  ## Local files 'adc apply' puts into the Secret named by ssl.secretName.
      #  ## Relative paths are resolved against the config file.
        files:
          trustStorePath: /etc/ssl/truststore.jks
      #  #  #keyStorePath: /path/to/keystore.jks
    
      ## Use an external Hadoop configs Secret instead of the one rendered by ADC.
      #hadoopConfigsSecret:
      #  # Use a Secret managed outside ADC.
      #  externalSecretName: existing-spark-hadoop-configs
      #
      #  ## Or let ADC create the Secret.
      #  #secretName: custom-spark-hadoop-configs
    
      ## Use an external Ranger configs Secret instead of the one rendered by ADC.
      #rangerConfigsSecret:
      #  # Use a Secret managed outside ADC.
      #  externalSecretName: existing-spark-ranger-configs
      #
      #  ## Or let ADC create the Secret.
      #  #secretName: custom-spark-ranger-configs
    
      # Spark application main resource (e.g. local:///opt/spark/examples/jars/spark-examples.jar).
      mainApplicationFile: "local:///opt/spark/examples/jars/spark-examples.jar" (5)
    
      ## HDFS or local directory for the Spark event log.
      ## When set, the CLI adds spark.eventLog.enabled=true, spark.eventLog.dir,
      ## spark.eventLog.rolling.enabled=true and spark.eventLog.rolling.interval=30s to sparkConf.
      #eventLogDir: ""
    
      ## Fully-qualified main class name. Required for Java/Scala applications.
      mainClass: "org.apache.spark.examples.sql.SparkSQLExample" (6)
    
      # ServiceAccount used by the Spark driver, also injected into
      # spark.kubernetes.authenticate.driver.serviceAccountName. The CLI creates it, plus a Role
      # and RoleBinding for Spark pods, by default (create: true). Set create: false to skip that
      # and only reference a ServiceAccount managed elsewhere.
      # The Role rules are managed by the CLI and cannot be customized.
      serviceAccount: (7)
        create: true
        name: spark-application
      job: (8)
        ## true (default) deletes the spark-submit Job pod after it finishes; set false to keep it for debugging.
        deleteOnTermination: false
    
        #resources:
        #  limits:
        #    cpu: "1"
        #    memory: 512Mi
        #  requests:
        #    cpu: 500m
        #    memory: 64Mi
    
        ## Component arguments. Key-value pairs passed to the component configuration.
        #args:
        #  executor-memory: 1g
        #  num-executors: "2"
    
      ## Application arguments appended after mainApplicationFile.
      args:
        - "100"
    
      # Spark configuration entries (spark.*).
      sparkConf: (9)
        spark.artifactory.dir.path: /tmp/artifacts
        spark.jars.ivy: /tmp/ivy
        spark.local.dir: /tmp/data
        spark.sql.catalog.spark_catalog: org.apache.iceberg.spark.SparkSessionCatalog
        spark.sql.extensions: org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions
        spark.sql.security.confblacklist: spark.sql.extensions
    
      ## Seconds after the application finishes (Succeeded, or Failed with no
      ## retries left) before the SparkApplication is deleted. Omit to keep it
      ## until explicit deletion.
      #ttlSecondsAfterFinished: 3600 (10)
    
      ## Celeborn remote shuffle service for Spark.
      ## tiers mirror the cluster's storage.tiers: local (SSD/HDD) and MEMORY advertise their name only,
      ## remote (S3/HDFS) also set dir (and, for S3, credentials). Ozone is an HDFS tier with an ofs:// dir.
      #celeborn:
      #  # Storage tiers mirroring the cluster's storage.tiers so the client advertises the same layers.
      #  # type: SSD, HDD, S3, HDFS, MEMORY. SSD/HDD and MEMORY are advertise-only here (no dir; worker-only
      #  # fields ignored); remote S3/HDFS set dir (s3a:// for S3; hdfs:// or ofs:// for Ozone on HDFS). Example:
      #  #   - type: MEMORY   # cache tier; pair with a durable tier below, no dir
      #  #   - type: SSD      # advertise-only on the client, no dir needed
      #  #   - dir: s3a://bucket/celeborn
      #  #     s3: { endpoint: https://s3:9878, region: us-east-1 }
      #  #     type: S3
      #  #   - dir: hdfs://nn/celeborn   # or ofs://om/volume/bucket/celeborn for Ozone
      #  #     type: HDFS
      #  tiers:
      #    - dir: s3a://shuffle/my-cluster
      #      s3:
      #        accessKey: <access-key>
      #        endpoint: https://s3.endpoint:443
      #        pathStyleAccess: true
      #        region: <region>
      #        secretKey: <secret-key>
      #      type: S3
      #  masterEndpoint: ""
      #  extraSparkConf:
      #    spark.sql.adaptive.enabled: "true"
      #
      #  # Enable TLS on the client's RPC connection to the Celeborn cluster.
      #  # When true the CLI renders spark.celeborn.ssl.* into the Spark conf
      #  # and requires the ssl section with trustStoreKey.
      #  rpcEncryption: false
      #
      #  # Enable TLS on the client's data module, which carries shuffle push/fetch
      #  # traffic between executors and workers. Requires the ssl section with trustStoreKey.
      #  dataEncryption: false
    
      ## YuniKorn scheduler configuration for queue selection and Gang scheduling.
      ## Uncomment the block to route the Spark job into a YuniKorn queue; the CLI renders the
      ## scheduler name, queue labels and gang annotations into sparkConf.
      #yunikorn:
      #  queue: root.analytics
      #  taskGroups:
      #    - minMember: 1
      #      minResource:
      #        cpu: "1"
      #        memory: 1433Mi
      #      name: spark-driver
      #    - minMember: 2
      #      minResource:
      #        cpu: "1"
      #        memory: 1433Mi
      #      name: spark-executor
    
      ## Monitoring configuration.
      #monitoring:
      #  # Enables Prometheus metrics export from this product's pods.
      #  exportMetrics: true
    1 Namespace that the Spark application will use.
    2 URL to the Spark image in your repository.
    3 Hadoop settings derived from the hadoop_conf.yaml file.
    4 SSL settings.
    5 URL to the application job file (JAR or .py).
    6 Main class name for Java/Scala applications.
    7 Service account settings.
    8 Job settings. Once the job is completed, the application pods are deleted by default. To keep the job and driver pods for debugging after the execution ends (e.g. to inspect logs), set the deleteOnTermination parameter to false. To keep the executor pods accessible, set the deleteOnTermination parameter to false inside the spark.executor block — it’s not included in the generated minimal configuration, so you need to add it manually.
    9 Spark configuration.
    10 Amount of time after which the Spark application deployment is deleted regardless of the execution result.
  4. You can check the configuration about to be applied by running the apply command with the --dry-run option:

    $ ./adc apply -f spark-application.yaml --dry-run > spark-application-render.yaml
    spark-application-render.yaml
    ---
    apiVersion: v1
    kind: Secret
    metadata:
      name: spark-application-configs
      namespace: spark-applications
    stringData:
      core-site.xml: |-
        <configuration>
          <property>
            <name>dfs.client.failover.proxy.provider.adh</name>
            <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
          </property>
          <property>
            <name>dfs.client.read.shortcircuit</name>
            <value>false</value>
          </property>
          <property>
            <name>dfs.ha.namenodes.adh</name>
            <value>nn_tsn-adh-k8s-1,nn_tsn-adh-k8s-3</value>
          </property>
          <property>
            <name>dfs.namenode.rpc-address.adh.nn_tsn-adh-k8s-1</name>
            <value>tsn-adh-k8s-1.ru-central1.internal:8020</value>
          </property>
          <property>
            <name>dfs.namenode.rpc-address.adh.nn_tsn-adh-k8s-3</name>
            <value>tsn-adh-k8s-3.ru-central1.internal:8020</value>
          </property>
          <property>
            <name>dfs.nameservices</name>
            <value>adh</value>
          </property>
          <property>
            <name>fs.defaultFS</name>
            <value>hdfs://adh</value>
          </property>
          <property>
            <name>hadoop.security.authentication</name>
            <value>simple</value>
          </property>
          <property>
            <name>hadoop.ssl.enabled</name>
            <value>true</value>
          </property>
        </configuration>
      hive-site.xml: |-
        <configuration>
          <property>
            <name>hive.metastore.sasl.enabled</name>
            <value>false</value>
          </property>
          <property>
            <name>hive.metastore.uris</name>
            <value>thrift://tsn-adh-k8s-1.ru-central1.internal:9083</value>
          </property>
          <property>
            <name>metastore.truststore.password</name>
            <value>bigdata</value>
          </property>
          <property>
            <name>metastore.truststore.path</name>
            <value>/etc/ssl/truststore.jks</value>
          </property>
          <property>
            <name>metastore.use.SSL</name>
            <value>true</value>
          </property>
        </configuration>
    type: Opaque
    ---
    apiVersion: v1
    data:
      truststore.jks: <encoded-truststore>
    kind: Secret
    metadata:
      name: ssl-secret
      namespace: spark-applications
    type: Opaque
    ---
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: spark-application
      namespace: spark-applications
    ---
    apiVersion: rbac.authorization.k8s.io/v1
    kind: Role
    metadata:
      name: spark-application
      namespace: spark-applications
    rules:
    - apiGroups:
      - ""
      resources:
      - pods
      - configmaps
      - persistentvolumeclaims
      - services
      - secrets
      verbs:
      - get
      - list
      - watch
      - create
      - update
      - patch
      - delete
      - deletecollection
    - apiGroups:
      - networking.k8s.io
      resources:
      - networkpolicies
      verbs:
      - get
      - list
      - watch
      - create
      - update
      - patch
      - delete
    - apiGroups:
      - events.k8s.io
      resources:
      - events
      verbs:
      - create
      - patch
      - update
    ---
    apiVersion: rbac.authorization.k8s.io/v1
    kind: RoleBinding
    metadata:
      name: spark-application
      namespace: spark-applications
    roleRef:
      apiGroup: rbac.authorization.k8s.io
      kind: Role
      name: spark-application
    subjects:
    - kind: ServiceAccount
      name: spark-application
      namespace: spark-applications
    ---
    apiVersion: spark.arenadata.io/v1alpha1
    kind: SparkApplication
    metadata:
      name: spark-application
      namespace: spark-applications
    spec:
      args:
      - "100"
      driver:
        metadata: {}
        spec:
          image: hub.adsw.io/adc-enterprise/spark3:3.5.4.4-adh-4.3.0-x86_64
          imagePullPolicy: Always
      executor:
        metadata: {}
        spec:
          image: hub.arenadata.io/adc-enterprise/spark3:3.5.4.4-adh-4.3.0-x86_64
          imagePullPolicy: Always
      hadoopConfigsSecretName: spark-application-configs
      job:
        deleteOnTermination: false
        metadata: {}
        spec:
          image: hub.arenadata.io/adc-enterprise/spark3:3.5.4.4-adh-4.3.0-x86_64
          imagePullPolicy: Always
      mainApplicationFile: local:///opt/spark/examples/jars/spark-examples.jar
      mainClass: org.apache.spark.examples.sql.SparkSQLExample
      serviceAccountName: spark-application
      sparkConf:
        spark.artifactory.dir.path: /tmp/artifacts
        spark.driver.extraJavaOptions: -Djavax.net.ssl.trustStore=/etc/ssl/truststore.jks
          -Djavax.net.ssl.trustStorePassword=bigdata
        spark.jars.ivy: /tmp/ivy
        spark.kubernetes.authenticate.driver.serviceAccountName: spark-application
        spark.kubernetes.namespace: spark-applications
        spark.local.dir: /tmp/data
        spark.sql.catalog.spark_catalog: org.apache.iceberg.spark.SparkSessionCatalog
        spark.sql.extensions: org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions
        spark.sql.security.confblacklist: spark.sql.extensions
      ssl:
        secretName: ssl-secret
        trustStoreKey: truststore.jks
    status: {}
  5. If the manifest is correct, submit the Spark application:

    $ ./adc apply -f spark-application.yaml

    The expected output contains a confirmation of success:

    time="20260826124237UTC" level="info" msg="cluster spark-application applied to namespace spark-applications"
  6. Verify that the Spark application pods are running:

    $ kubectl get pods -n spark-applications

    The expected output is:

    NAME                                              READY   STATUS    RESTARTS   AGE
    spark-application-463920a03e1814e6-driver         1/1     Running   0          8s
    spark-application-k4hdq                           1/1     Running   0          12s
    spark-sql-basic-example-71f9a4a03e182681-exec-1   1/1     Running   0          3s
    spark-sql-basic-example-71f9a4a03e182681-exec-2   1/1     Running   0          3s

    Once the job finishes, the executor pods are deleted and the status of the application pods changes to Completed:

    NAME                                        READY   STATUS      RESTARTS   AGE
    spark-application-463920a03e1814e6-driver   0/1     Completed   0          4m57s
    spark-application-k4hdq                     0/1     Completed   0          5m1s
  7. Inspect the output in the logs of the driver pod:

    $ kubectl logs spark-application-463920a03e1814e6-driver -n spark-applications

    The logs should contain lines regarding the job.

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