# Overview This bundle provides a complete deployment of [Apache Spark][] in standalone HA mode as provided by [Apache Bigtop][]. Ganglia and rsyslog applications are included to monitor cluster health and syslog activity. [Apache Spark]: http://spark/apache.org/ [Apache Bigtop]: http://bigtop.apache.org/ ## Bundle Composition The applications that comprise this bundle are spread across 6 units as follows: * Spark (Master and Worker) * 2 separate units * Zookeeper * 3 separate units * Ganglia (Web interface for monitoring cluster metrics) * Rsyslog (Aggregate cluster syslog events in a single location) * Colocated on the Ganglia unit Deploying this bundle results in a fully configured Apache Bigtop Spark cluster on any supported cloud, which can be easily scaled to meet workload demands. # Deploying A working Juju installation is assumed to be present. If Juju is not yet set up, please follow the [getting-started][] instructions prior to deploying this bundle. > **Note**: This bundle requires hardware resources that may exceed limits of Free-tier or Trial accounts on some clouds. To deploy to these environments, modify a local copy of [bundle.yaml][] with `zookeeper: num_units: 1` and `machines: 'X': constraints: mem=3G` as needed to satisfy account limits. Deploy this bundle from the Juju charm store with the `juju deploy` command: juju deploy spark-processing > **Note**: The above assumes Juju 2.0 or greater. If using an earlier version of Juju, use [juju-quickstart][] with the following syntax: `juju quickstart spark-processing`. Alternatively, deploy a locally modified `bundle.yaml` with: juju deploy /path/to/bundle.yaml > **Note**: The above assumes Juju 2.0 or greater. If using an earlier version of Juju, use [juju-quickstart][] with the following syntax: `juju quickstart /path/to/bundle.yaml`. The charms in this bundle can also be built from their source layers in the [Bigtop charm repository][]. See the [Bigtop charm README][] for instructions on building and deploying these charms locally. ## Network-Restricted Environments Charms can be deployed in environments with limited network access. To deploy in this environment, configure a Juju model with appropriate proxy and/or mirror options. See [Configuring Models][] for more information. [getting-started]: https://jujucharms.com/docs/stable/getting-started [bundle.yaml]: https://github.com/apache/bigtop/blob/master/bigtop-deploy/juju/spark-processing/bundle.yaml [juju-quickstart]: https://launchpad.net/juju-quickstart [Bigtop charm repository]: https://github.com/apache/bigtop/tree/master/bigtop-packages/src/charm [Bigtop charm README]: https://github.com/apache/bigtop/blob/master/bigtop-packages/src/charm/README.md [Configuring Models]: https://jujucharms.com/docs/stable/models-config # Verifying ## Status The applications that make up this bundle provide status messages to indicate when they are ready: juju status This is particularly useful when combined with `watch` to track the on-going progress of the deployment: watch -n 2 juju status The message for each unit will provide information about that unit's state. Once they all indicate that they are ready, perform application smoke tests to verify that the bundle is working as expected. ## Smoke Test The spark and zookeeper charms provide a `smoke-test` action that can be used to verify the respective application is functioning as expected. Run these actions as follows: juju run-action spark/0 smoke-test juju run-action zookeeper/0 smoke-test > **Note**: The above assumes Juju 2.0 or greater. If using an earlier version of Juju, the syntax is `juju action do /0 smoke-test`. Watch the progress of the smoke test actions with: watch -n 2 juju show-action-status > **Note**: The above assumes Juju 2.0 or greater. If using an earlier version of Juju, the syntax is `juju action status`. Eventually, all of the actions should settle to `status: completed`. If any report `status: failed`, that application is not working as expected. Get more information about the smoke-test action juju show-action-output > **Note**: The above assumes Juju 2.0 or greater. If using an earlier version of Juju, the syntax is `juju action fetch `. ## Utilities Applications in this bundle include Zookeeper command line and Spark web utilities that can be used to verify information about the cluster. From the command line, show the list of Zookeeper nodes with the following: juju run --unit zookeeper/0 'echo "ls /" | /usr/lib/zookeeper/bin/zkCli.sh' To access the Spark web console, find the `PUBLIC-ADDRESS` of the spark application and expose it: juju status spark juju expose spark The web interface will be available at the following URL: http://SPARK_PUBLIC_IP:8080 # Monitoring This bundle includes Ganglia for system-level monitoring of the spark and zookeeper units. Metrics are sent to a centralized ganglia unit for easy viewing in a browser. To view the ganglia web interface, find the `PUBLIC-ADDRESS` of the Ganglia application and expose it: juju status ganglia juju expose ganglia The web interface will be available at: http://GANGLIA_PUBLIC_IP/ganglia # Logging This bundle includes rsyslog to collect syslog data from the spark and zookeeper units. These logs are sent to a centralized rsyslog unit for easy syslog analysis. One method of viewing this log data is to simply cat syslog from the rsyslog unit: juju run --unit rsyslog/0 'sudo cat /var/log/syslog' Logs may also be forwarded to an external rsyslog processing service. See the *Forwarding logs to a system outside of the Juju environment* section of the [rsyslog README](https://jujucharms.com/rsyslog/) for more information. # Benchmarking The `spark` charm in this bundle provides several benchmarks to gauge the performance of the Spark cluster. Each benchmark is an action that can be run with `juju run-action`: $ juju actions spark | grep Bench connectedcomponent Run the Spark Bench ConnectedComponent benchmark. decisiontree Run the Spark Bench DecisionTree benchmark. kmeans Run the Spark Bench KMeans benchmark. linearregression Run the Spark Bench LinearRegression benchmark. logisticregression Run the Spark Bench LogisticRegression benchmark. matrixfactorization Run the Spark Bench MatrixFactorization benchmark. pagerank Run the Spark Bench PageRank benchmark. pca Run the Spark Bench PCA benchmark. pregeloperation Run the Spark Bench PregelOperation benchmark. shortestpaths Run the Spark Bench ShortestPaths benchmark. sql Run the Spark Bench SQL benchmark. stronglyconnectedcomponent Run the Spark Bench StronglyConnectedComponent benchmark. svdplusplus Run the Spark Bench SVDPlusPlus benchmark. svm Run the Spark Bench SVM benchmark. $ juju run-action spark/0 svdplusplus Action queued with id: 339cec1f-e903-4ee7-85ca-876fb0c3d28e $ juju show-action-output 339cec1f-e903-4ee7-85ca-876fb0c3d28e results: meta: composite: direction: asc units: secs value: "200.754000" raw: | SVDPlusPlus,2016-11-02-03:08:26,200.754000,85.974071,.428255,0,SVDPlusPlus-MLlibConfig,,,,,10,,,50000,4.0,1.3, start: 2016-11-02T03:08:26Z stop: 2016-11-02T03:11:47Z results: duration: direction: asc units: secs value: "200.754000" throughput: direction: desc units: x/sec value: ".428255" status: completed timing: completed: 2016-11-02 03:11:48 +0000 UTC enqueued: 2016-11-02 03:08:21 +0000 UTC started: 2016-11-02 03:08:26 +0000 UTC # Scaling By default, three spark and three zookeeper units are deployed. Scaling these applications is as simple as adding more units. To add one unit: juju add-unit spark juju add-unit zookeeper Multiple units may be added at once. For example, add four more spark units: juju add-unit -n4 spark # Contact Information - # Resources - [Apache Bigtop home page](http://bigtop.apache.org/) - [Apache Bigtop issue tracking](http://bigtop.apache.org/issue-tracking.html) - [Apache Bigtop mailing lists](http://bigtop.apache.org/mail-lists.html) - [Juju Bigtop charms](https://jujucharms.com/q/apache/bigtop) - [Juju mailing list](https://lists.ubuntu.com/mailman/listinfo/juju) - [Juju community](https://jujucharms.com/community)