Pod template files can also define multiple containers. ensure that once the driver pod is deleted from the cluster, all of the applications executor pods will also be deleted. See the Kubernetes documentation for specifics on configuring Kubernetes with custom resources. Kubernetes dashboard if installed on frequently used with Kubernetes. spark-submit is used by default to name the Kubernetes resources created like drivers and executors. The driver pod uses this service account when requesting The Spark scheduler attempts to delete these pods, but if the network request to the API server fails use the spark service account, a user simply adds the following option to the spark-submit command: To create a custom service account, a user can use the kubectl create serviceaccount command. For Spark on Kubernetes, since the driver always creates executor pods in the Users can kill a job by providing the submission ID that is printed when submitting their job. In cluster mode, if this is not set, the driver pod name is set to "spark.app.name" For example if user has set a specific namespace as follows kubectl config set-context minikube --namespace=spark Acceldata Torch can be installed on an existing Kubernetes cluster and supports installation with embedded Kubernetes. It acts as If no volume is set as local storage, Spark uses temporary scratch space to spill data to disk during shuffles and other operations. Open the Azure Monitor workspaces menu in the Azure portal and select your cluster.. A tag already exists with the provided branch name. do not provide a scheme). In order to use an alternative context users can specify the desired context via the Spark configuration property spark.kubernetes.context e.g. same namespace, a Role is sufficient, although users may use a ClusterRole instead. Apache Spark 3.0 brings native support for monitoring with Prometheus in Kubernetes (see Part 1 ). Security features like authentication are not enabled by default. We recommend 3 CPUs and 4g of memory to be able to start a simple Spark application with a single When this property is set, its highly recommended to make it unique across all jobs in the same namespace. spark-submit. executor. K8s IP Family Policy for Driver Service. You must have appropriate permissions to list, create, edit and delete. Path to store files at the spark submit side in cluster mode. which in turn decides whether the executor is removed and replaced, or placed into a failed state for debugging. do not Spark application to access secured services. do not provide a scheme). Spark creates a Spark driver running within a. The container name will be assigned by spark ("spark-kubernetes-driver" for the driver container, and spark.master in the applications configuration, must be a URL with the format k8s://:. For a complete list of available options for each supported type of volumes, please refer to the Spark Properties section below. To do so, specify the spark properties spark.kubernetes.driver.podTemplateFile and spark.kubernetes.executor.podTemplateFile In client mode, use. using --conf as means to provide it (default value for all K8s pods is 30 secs). driver pod to be routable from the executors by a stable hostname. Spark (starting with version 2.3) ships with a Dockerfile that can be used for this Specify the grace period in seconds when deleting a Spark application using spark-submit. The driver pod name will be overwritten with either the configured or default value of. Introducing Apache Spark + Kubernetes. If you create custom ResourceProfiles be sure to include all necessary resources there since the resources from the template file will not be propagated to custom ResourceProfiles. Spark counts the total number of created PVCs which the job can have, and holds on a new executor creation Overview. In the world of Kubernetes, an ingress controller is a key component that allows incoming traffic to be routed to the appropriate service within a cluster. Similarly, the The resources reserved toDaemonSetsdepends on your setup, but note that DaemonSets are popular for log and metrics collection, networking, and security. will be the driver or executor container. Namespaces are ways to divide cluster resources between multiple users (via resource quota). Were targeting a release early 2021. Comma separated list of Kubernetes secrets used to pull images from private image registries. It acts as an entry point for HTTP and HTTPs traffic, enabling the exposure of services to the outside world. to indicate which container should be used as a basis for the driver or executor. So, application names connect without TLS on a different port, the master would be set to k8s://http://example.com:8080. OwnerReference, which in turn will Specify the local location of the krb5.conf file to be mounted on the driver and executors for Kerberos interaction. This sets the major Python version of the docker image used to run the driver and executor containers. Sometimes users may need to specify a custom the services label selector will only match the driver pod and no other pods; it is recommended to assign your driver 'PYSPARK_PYTHON' and 'PYSPARK_DRIVER_PYTHON' environment variables. use namespaces to launch Spark applications. In client mode, use, Path to the client cert file for authenticating against the Kubernetes API server from the driver pod when To enable spot nodes in Kubernetes you should create multiple node pools (some on-demand and some spot) and then use node-selectors and node affinities to put the driver on an on-demand node and executors preferably on spot nodes. Specify this as a path as opposed to a URI (i.e. When the app is running, the Spark UI is served by the Spark driver directly on port 4040. The service account credentials used by the driver pods must be allowed to create pods, services and configmaps. Kubernetes is used to automate deployment, scaling and management of containerized apps most commonly Docker containers. When running an application in client mode, To mount a volume of any of the types above into the driver pod, use the following configuration property: Specifically, VolumeType can be one of the following values: hostPath, emptyDir, nfs and persistentVolumeClaim. Shuffles are the expensive all-to-all data exchanges executors. A Zeppelin server running outside or inside a k8s cluster spark-submit started with deployMode = client/cluster Spark-submit deployMode determines where the driver Time to wait between each round of executor pod allocation. For example, by default, on-demand PVCs are owned by executors and For example, See the below table for the full list of pod specifications that will be overwritten by spark. In other words, the total The client scheme is supported for the application jar, and dependencies specified by properties spark.jars, spark.files and spark.archives. ClassicFullStack vs CloudNativeFullStack in Kubernetes Monitoring in Container platforms 04 May 2023; Data is missing from Dynatrace for Kubernetes Cluster applications in Container platforms 03 May 2023; Data is missing from Dynatrace for Kubernetes Cluster applications in Container platforms 03 May 2023 To access it, you should, When the app is completed, you can replay the Spark UI by running the Spark History Server and configuring it to read the Spark event logs from a persistent storage. Onboard from Container insights. The port must always be specified, even if its the HTTPS port 443. This removes the need for the job user when requesting executors. Users can mount the following types of Kubernetes volumes into the driver and executor pods: NB: Please see the Security section of this document for security issues related to volume mounts. In Kubernetes clusters with RBAC enabled, users can configure Use the exact prefix spark.kubernetes.authenticate for Kubernetes authentication parameters in client mode. Custom container image to use for the driver. to stream logs from the application using: The same logs can also be accessed through the However, if there file must be located on the submitting machine's disk. Check out ourblog post covering Spark 3.1releaseto dive deeper into this. To get some basic information about the scheduling decisions made around the driver pod, you can run: If the pod has encountered a runtime error, the status can be probed further using: Status and logs of failed executor pods can be checked in similar ways. That means operations will affect all Spark applications matching the given submission ID regardless of namespace. list of PODs then this delta time is taken as the accepted time difference between the executors. Overview. Once the Spark driver is up, it will communicate directly with Kubernetes to request Spark executors, which will also be scheduled on pods (one pod per executor). RAM backed volumes. Note that currently only driver/job level PodGroup is supported in Volcano Feature Step. If no directories are explicitly specified then a default directory is created and configured appropriately. TOTAL_DURATION policy chooses an executor with the biggest total task time. Spark only supports setting the resource limits. Finally, deleting the driver pod will clean up the entire spark Specify the local file that contains the driver, Specify the container name to be used as a basis for the driver in the given, Specify the local file that contains the executor, Specify the container name to be used as a basis for the executor in the given. {driver/executor}.scheduler.name configuration. /etc/secrets in both the driver and executor containers, add the following options to the spark-submit command: To use a secret through an environment variable use the following options to the spark-submit command: Kubernetes allows defining pods from template files. Azure Kubernetes Service (AKS) provides additional, supported functionality for your cluster using add-ons and extensions. and newly started executors are protected by spark.kubernetes.executor.minTasksPerExecutorBeforeRolling. For this reason, were developing Data Mechanics Delight, a new and improved Spark UIwith new metrics and visualizations. For example if you have diskless nodes with remote storage mounted over a network, having lots of executors doing IO to this remote storage may actually degrade performance. Specify whether executor pods should be deleted in case of failure or normal termination. This means your Spark executors will request exactly the 3.6 CPUs available, and Spark will schedule up to 4 tasks in parallel on this executor. registration time and the time of the polling. be used by the driver pod through the configuration property Or use any of the available Kubernetes clients with the language of your choice. Specifying values less than 1 second may lead to For that reason, the user must specify a discovery script that gets run by the executor on startup to discover what resources are available to that executor. do not provide a scheme). The context from the user Kubernetes configuration file used for the initial Request timeout in milliseconds for the kubernetes client in driver to use when requesting executors. Running Spark Over Kubernetes A big difference between running Spark over Kubernetes and using an enterprise deployment of Spark is that you dont need YARN to manage resources, as the task is delegated to Kubernetes. Getting acquainted with RAPIDS Accelerator for Apache Spark was an amazing joy ride effort. Spark will not roll executors whose total number of tasks is smaller "spark-kubernetes-executor" for each executor container) if not defined by the pod template. Weve already covered this topic in ourYARN vs Kubernetes performance benchmarksarticle, (read How to optimize shuffle with Spark on Kubernetes) so well just give our high-level tips here: Then you would submit your Spark apps with the configurationspark.executor.cores=4right? hostname via spark.driver.host and your spark drivers port to spark.driver.port. This token value is uploaded to the driver pod as a secret. Note that this cannot be specified alongside a CA cert file, client key file, Getting acquainted with RAPIDS Accelerator for Apache Spark was an amazing joy ride effort. In addition, When deploying a cluster that is open to the internet API server. spark.kubernetes. resources, number of objects, etc on individual namespaces. Maximum number of pending PODs allowed during executor allocation for this Note that unlike the other authentication options, this must be the exact string value of See the configuration page for information on Spark configurations. The driver and executor pod scheduling is handled by Kubernetes. How long to wait for executors to shut down gracefully before a forceful kill. Users can also download a Hadoop free binary and run Spark with any Hadoop version by augmenting Sparks classpath . also counted into this limit as they will change into pending PODs by time. AVERAGE_DURATION policy chooses an executor with the biggest average task time. of the deleted executor pods if exists. is also available. application exits. This removes the need for the job user the users current context is used. WebUsing Kubernetes Volumes. authenticating proxy, kubectl proxy to communicate to the Kubernetes API. This will build using the projects provided default Dockerfiles. Class names of an extra driver pod feature step implementing When configured like this Sparks local storage usage will count towards your pods memory usage therefore you may wish to increase your memory requests by increasing the value of spark. The internal Kubernetes master (API server) address to be used for driver to request executors or Finally, notice that in the above example we specify a jar with a specific URI with a scheme of local://. persistent volume claims when there exists no reusable one. This file must be located on the submitting machine's disk, and will be uploaded to the The Spark Operator for Apache Spark has an active community of Also make sure in the derived k8s image default ivy dir If you run your driver inside a Kubernetes pod, you can use a and SPARK_PREFER_IPV6=true for Python additionally to use IPv6. actually running in a pod, keep in mind that the executor pods may not be properly deleted from the cluster when the There are several Spark on Kubernetes features that are currently being worked on or planned to be worked on. Interval between successive inspection of executor events sent from the Kubernetes API. Max size limit for a config map. Downloads are pre-packaged for a handful of popular Hadoop versions. of type Cluster IP) per Spark job after the Job submission with SparkSubmit, for instance running spark-submit && kubectl apply . to provide any kerberos credentials for launching a job. Specify this as a path as opposed to a URI (i.e. To allow the driver pod access the executor pod template requesting executors. The ConfigMap must also This file must be located on the submitting machine's disk, and will be uploaded to the driver pod as a RoleBinding or ClusterRoleBinding, a user can use the kubectl create rolebinding (or clusterrolebinding When a registered executor's POD is missing from the Kubernetes API server's polled The images are built to This is the reason why we built our managed Spark platform (Data Mechanics), to make Spark on Kubernetes as easy and accessible as it should be. TOTAL_DURATION, FAILED_TASKS, and OUTLIER (default). do not provide a scheme). The second main improvement is the ability to mount shared NFS volumes in Kubernetes (a network-backed storage that can be shared by all your Spark apps and be pre-populated with data), and the ability to dynamically provision PersistentVolumeClaims (instead of statically), which is particularly useful if youre trying to run Spark apps with dynamic allocation enabled. Specify scheduler related configurations. Spark users can similarly use template files to define the driver or executor pod configurations that Spark configurations do not support. spark-submit can be directly used to submit a Spark application to a Kubernetes cluster. Images built from the project provided Dockerfiles contain a default USER directive with a default UID of 185. # To build additional PySpark docker image, # To build additional SparkR docker image, # Specify volcano scheduler and PodGroup template, # Specify driver/executor VolcanoFeatureStep, # Specify minMember to 1 to make a driver pod, # Specify minResources to support resource reservation (the driver pod resource and executors pod resource should be considered), # It is useful for ensource the available resources meet the minimum requirements of the Spark job and avoiding the. be replaced by either the configured or default spark conf value. kubectl port-forward. It will be possible to use more advanced Read more about it here. [SecretName]=. Monitoring a Swarm cluster is essential to ensure its availability and reliability. value in client mode allows the driver to become the owner of its executor pods, which in turn allows the executor client cert file, and/or OAuth token. If `spark.kubernetes.driver.scheduler.name` or Runs after all of Spark internal feature steps.