dongjoon-hyun commented on code in PR #113: URL: https://github.com/apache/spark-kubernetes-operator/pull/113#discussion_r1762254410
########## docs/architecture.md: ########## @@ -0,0 +1,64 @@ +<!-- +Licensed to the Apache Software Foundation (ASF) under one +or more contributor license agreements. See the NOTICE file +distributed with this work for additional information +regarding copyright ownership. The ASF licenses this file +to you 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. +--> + +# Design & Architecture + +**Spark-Kubernetes-Operator** (Operator) acts as a control plane to manage the complete +deployment lifecycle of Spark applications. The Operator can be installed on a Kubernetes +cluster using Helm. In most production environments it is typically deployed in a designated +namespace and controls Spark deployments in one or more managed namespaces. The custom resource +definition (CRD) that describes the schema of a SparkApplication is a cluster wide resource. +For a CRD, the declaration must be registered before any resources of that CRDs kind(s) can be +used, and the registration process sometimes takes a few seconds. + +Users can interact with the operator using the kubectl or k8s API. The Operator continuously +tracks cluster events relating to the SparkApplication custom resources. When the operator +receives a new resource update, it will take action to adjust the Kubernetes cluster to the +desired state as part of its reconciliation loop. The initial loop consists of the following +high-level steps: + +* User submits a SparkApplication custom resource(CR) using kubectl / API +* Operator launches driver and observes its status +* Operator observes driver-spawn resources (e.g. executors) till app terminates +* Operator releases all Spark-app owned resources to cluster +* The SparkApplication CR can be (re)applied on the cluster any time - e.g. to issue proactive Review Comment: `CR` -> `CRD`? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
