[SPARK-22648][K8S] Spark on Kubernetes - Documentation

What changes were proposed in this pull request?

This PR contains documentation on the usage of Kubernetes scheduler in Spark 2.3, and a shell script to make it easier to build docker images required to use the integration. The changes detailed here are covered by #19717 and #19468 which have merged already.

How was this patch tested?
The script has been in use for releases on our fork. Rest is documentation.

cc rxin mateiz (shepherd)
k8s-big-data SIG members & contributors: foxish ash211 mccheah liyinan926 erikerlandson ssuchter varunkatta kimoonkim tnachen ifilonenko
reviewers: vanzin felixcheung jiangxb1987 mridulm

TODO:
- [x] Add dockerfiles directory to built distribution. (#20007)
- [x] Change references to docker to instead say "container" (#19995)
- [x] Update configuration table.
- [x] Modify spark.kubernetes.allocation.batch.delay to take time instead of int (#20032)

Author: foxish <ramanathana@google.com>

Closes #19946 from foxish/update-k8s-docs.

docs/_layouts/global.html

@@ -99,6 +99,7 @@
  <li><a href="spark-standalone.html">Spark Standalone</a></li>
  <li><a href="running-on-mesos.html">Mesos</a></li>
  <li><a href="running-on-yarn.html">YARN</a></li>
+ <li><a href="running-on-kubernetes.html">Kubernetes</a></li>
  </ul>
  </li>
 

docs/building-spark.md

@@ -49,7 +49,7 @@ To create a Spark distribution like those distributed by the
 to be runnable, use `./dev/make-distribution.sh` in the project root directory. It can be configured
 with Maven profile settings and so on like the direct Maven build. Example:
 
- ./dev/make-distribution.sh --name custom-spark --pip --r --tgz -Psparkr -Phadoop-2.7 -Phive -Phive-thriftserver -Pmesos -Pyarn
+ ./dev/make-distribution.sh --name custom-spark --pip --r --tgz -Psparkr -Phadoop-2.7 -Phive -Phive-thriftserver -Pmesos -Pyarn -Pkubernetes
 
 This will build Spark distribution along with Python pip and R packages. For more information on usage, run `./dev/make-distribution.sh --help`
 
@@ -90,6 +90,10 @@ like ZooKeeper and Hadoop itself.
 ## Building with Mesos support
 
  ./build/mvn -Pmesos -DskipTests clean package
+
+## Building with Kubernetes support
+
+ ./build/mvn -Pkubernetes -DskipTests clean package
 
 ## Building with Kafka 0.8 support
 

docs/cluster-overview.md

@@ -52,11 +52,8 @@ The system currently supports three cluster managers:
 * [Apache Mesos](running-on-mesos.html) -- a general cluster manager that can also run Hadoop MapReduce
  and service applications.
 * [Hadoop YARN](running-on-yarn.html) -- the resource manager in Hadoop 2.
-* [Kubernetes (experimental)](https://github.com/apache-spark-on-k8s/spark) -- In addition to the above,
-there is experimental support for Kubernetes. Kubernetes is an open-source platform
-for providing container-centric infrastructure. Kubernetes support is being actively
-developed in an [apache-spark-on-k8s](https://github.com/apache-spark-on-k8s/) Github organization. 
-For documentation, refer to that project's README.
+* [Kubernetes](running-on-kubernetes.html) -- [Kubernetes](https://kubernetes.io/docs/concepts/overview/what-is-kubernetes/)
+is an open-source platform that provides container-centric infrastructure.
 
 A third-party project (not supported by the Spark project) exists to add support for
 [Nomad](https://github.com/hashicorp/nomad-spark) as a cluster manager.

docs/configuration.md

@@ -2376,6 +2376,8 @@ can be found on the pages for each mode:
 
 #### [Mesos](running-on-mesos.html#configuration)
 
+#### [Kubernetes](running-on-kubernetes.html#configuration)
+
 #### [Standalone Mode](spark-standalone.html#cluster-launch-scripts)
 
 # Environment Variables

docs/index.md

@@ -81,6 +81,7 @@ options for deployment:
 * [Standalone Deploy Mode](spark-standalone.html): simplest way to deploy Spark on a private cluster
 * [Apache Mesos](running-on-mesos.html)
 * [Hadoop YARN](running-on-yarn.html)
+* [Kubernetes](running-on-kubernetes.html)
 
 # Where to Go from Here
 
@@ -112,7 +113,7 @@ options for deployment:
  * [Mesos](running-on-mesos.html): deploy a private cluster using
  [Apache Mesos](http://mesos.apache.org)
  * [YARN](running-on-yarn.html): deploy Spark on top of Hadoop NextGen (YARN)
- * [Kubernetes (experimental)](https://github.com/apache-spark-on-k8s/spark): deploy Spark on top of Kubernetes
+ * [Kubernetes](running-on-kubernetes.html): deploy Spark on top of Kubernetes
 
 **Other Documents:**
 

docs/running-on-yarn.md

@@ -18,7 +18,9 @@ Spark application's configuration (driver, executors, and the AM when running in
 
 There are two deploy modes that can be used to launch Spark applications on YARN. In `cluster` mode, the Spark driver runs inside an application master process which is managed by YARN on the cluster, and the client can go away after initiating the application. In `client` mode, the driver runs in the client process, and the application master is only used for requesting resources from YARN.
 
-Unlike [Spark standalone](spark-standalone.html) and [Mesos](running-on-mesos.html) modes, in which the master's address is specified in the `--master` parameter, in YARN mode the ResourceManager's address is picked up from the Hadoop configuration. Thus, the `--master` parameter is `yarn`.
+Unlike other cluster managers supported by Spark in which the master's address is specified in the `--master`
+parameter, in YARN mode the ResourceManager's address is picked up from the Hadoop configuration.
+Thus, the `--master` parameter is `yarn`.
 
 To launch a Spark application in `cluster` mode:
 

docs/submitting-applications.md

@@ -127,6 +127,16 @@ export HADOOP_CONF_DIR=XXX
  http://path/to/examples.jar \
  1000
 
+# Run on a Kubernetes cluster in cluster deploy mode
+./bin/spark-submit \
+ --class org.apache.spark.examples.SparkPi \
+ --master k8s://xx.yy.zz.ww:443 \
+ --deploy-mode cluster \
+ --executor-memory 20G \
+ --num-executors 50 \
+ http://path/to/examples.jar \
+ 1000
+
 {% endhighlight %}
 
 # Master URLs
@@ -155,6 +165,12 @@ The master URL passed to Spark can be in one of the following formats:
   <code>client</code> or <code>cluster</code> mode depending on the value of <code>--deploy-mode</code>.
   The cluster location will be found based on the <code>HADOOP_CONF_DIR</code> or <code>YARN_CONF_DIR</code> variable.
 </td></tr>
+<tr><td> <code>k8s://HOST:PORT</code> </td><td> Connect to a <a href="running-on-kubernetes.html">Kubernetes</a> cluster in
+  <code>cluster</code> mode. Client mode is currently unsupported and will be supported in future releases.
+  The <code>HOST</code> and <code>PORT</code> refer to the [Kubernetes API Server](https://kubernetes.io/docs/reference/generated/kube-apiserver/).
+  It connects using TLS by default. In order to force it to use an unsecured connection, you can use
+  <code>k8s://http://HOST:PORT</code>.
+</td></tr>
 </table>
 
 

sbin/build-push-docker-images.sh

@@ -0,0 +1,68 @@
+#!/usr/bin/env bash
+
+# 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.
+#
+
+# This script builds and pushes docker images when run from a release of Spark
+# with Kubernetes support.
+
+declare -A path=( [spark-driver]=kubernetes/dockerfiles/driver/Dockerfile \
+ [spark-executor]=kubernetes/dockerfiles/executor/Dockerfile )
+
+function build {
+ docker build -t spark-base -f kubernetes/dockerfiles/spark-base/Dockerfile .
+ for image in "${!path[@]}"; do
+ docker build -t ${REPO}/$image:${TAG} -f ${path[$image]} .
+ done
+}
+
+
+function push {
+ for image in "${!path[@]}"; do
+ docker push ${REPO}/$image:${TAG}
+ done
+}
+
+function usage {
+ echo "This script must be run from a runnable distribution of Apache Spark."
+ echo "Usage: ./sbin/build-push-docker-images.sh -r <repo> -t <tag> build"
+ echo " ./sbin/build-push-docker-images.sh -r <repo> -t <tag> push"
+ echo "for example: ./sbin/build-push-docker-images.sh -r docker.io/myrepo -t v2.3.0 push"
+}
+
+if [[ "$@" = *--help ]] || [[ "$@" = *-h ]]; then
+ usage
+ exit 0
+fi
+
+while getopts r:t: option
+do
+ case "${option}"
+ in
+ r) REPO=${OPTARG};;
+ t) TAG=${OPTARG};;
+ esac
+done
+
+if [ -z "$REPO" ] || [ -z "$TAG" ]; then
+ usage
+else
+ case "${@: -1}" in
+ build) build;;
+ push) push;;
+ *) usage;;
+ esac
+fi