---
layout: page
title: "Apache Zeppelin on Spark cluster mode"
description: "This document will guide you how you can build and configure the environment on 3 types of Spark cluster manager(Standalone, Hadoop Yarn, Apache Mesos) with Apache Zeppelin using docker scripts."
group: setup/deployment 
---
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{% include JB/setup %}

# Apache Zeppelin on Spark Cluster Mode

<div id="toc"></div>

## Overview
[Apache Spark](http://spark.apache.org/) has supported three cluster manager types([Standalone](http://spark.apache.org/docs/latest/spark-standalone.html), [Apache Mesos](http://spark.apache.org/docs/latest/running-on-mesos.html) and [Hadoop YARN](http://spark.apache.org/docs/latest/running-on-yarn.html)) so far.
This document will guide you how you can build and configure the environment on 3 types of Spark cluster manager with Apache Zeppelin using [Docker](https://www.docker.com/) scripts.
So [install docker](https://docs.docker.com/engine/installation/) on the machine first.

## Spark standalone mode
[Spark standalone](http://spark.apache.org/docs/latest/spark-standalone.html) is a simple cluster manager included with Spark that makes it easy to set up a cluster.
You can simply set up Spark standalone environment with below steps.

> **Note :** Since Apache Zeppelin and Spark use same `8080` port for their web UI, you might need to change `zeppelin.server.port` in `conf/zeppelin-site.xml`.


### 1. Build Docker file
You can find docker script files under `scripts/docker/spark-cluster-managers`.

```bash
cd $ZEPPELIN_HOME/scripts/docker/spark-cluster-managers/spark_standalone
docker build -t "spark_standalone" .
```

### 2. Run docker

```bash
docker run -it \
-p 8080:8080 \
-p 7077:7077 \
-p 8888:8888 \
-p 8081:8081 \
-h sparkmaster \
--name spark_standalone \
spark_standalone bash;
```

Note that `sparkmaster` hostname used here to run docker container should be defined in your `/etc/hosts`.

### 3. Configure Spark interpreter in Zeppelin
Set Spark master as `spark://<hostname>:7077` in Zeppelin **Interpreters** setting page.

<img src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/standalone_conf.png" />

### 4. Run Zeppelin with Spark interpreter
After running single paragraph with Spark interpreter in Zeppelin, browse `https://<hostname>:8080` and check whether Spark cluster is running well or not.

<img src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/spark_ui.png" />

You can also simply verify that Spark is running well in Docker with below command.

```bash
ps -ef | grep spark
```


## Spark on YARN mode
You can simply set up [Spark on YARN](http://spark.apache.org/docs/latest/running-on-yarn.html) docker environment with below steps.

> **Note :** Since Apache Zeppelin and Spark use same `8080` port for their web UI, you might need to change `zeppelin.server.port` in `conf/zeppelin-site.xml`.

### 1. Build Docker file
You can find docker script files under `scripts/docker/spark-cluster-managers`.

```bash
cd $ZEPPELIN_HOME/scripts/docker/spark-cluster-managers/spark_yarn_cluster
docker build -t "spark_yarn" .
```

### 2. Run docker

```bash
docker run -it \
 -p 5000:5000 \
 -p 9000:9000 \
 -p 9001:9001 \
 -p 8088:8088 \
 -p 8042:8042 \
 -p 8030:8030 \
 -p 8031:8031 \
 -p 8032:8032 \
 -p 8033:8033 \
 -p 8080:8080 \
 -p 7077:7077 \
 -p 8888:8888 \
 -p 8081:8081 \
 -p 50010:50010 \
 -p 50075:50075 \
 -p 50020:50020 \
 -p 50070:50070 \
 --name spark_yarn \
 -h sparkmaster \
 spark_yarn bash;
```

Note that `sparkmaster` hostname used here to run docker container should be defined in your `/etc/hosts`.

### 3. Verify running Spark on YARN.

You can simply verify the processes of Spark and YARN are running well in Docker with below command.

```bash
ps -ef
```

You can also check each application web UI for HDFS on `http://<hostname>:50070/`, YARN on `http://<hostname>:8088/cluster` and Spark on `http://<hostname>:8080/`.

### 4. Configure Spark interpreter in Zeppelin
Set following configurations to `conf/zeppelin-env.sh`.

```bash
export HADOOP_CONF_DIR=[your_hadoop_conf_path]
export SPARK_HOME=[your_spark_home_path]
```

`HADOOP_CONF_DIR`(Hadoop configuration path) is defined in `/scripts/docker/spark-cluster-managers/spark_yarn_cluster/hdfs_conf`.

Don't forget to set Spark `spark.master` as `yarn-client` in Zeppelin **Interpreters** setting page like below.

<img src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/zeppelin_yarn_conf.png" />

### 5. Run Zeppelin with Spark interpreter
After running a single paragraph with Spark interpreter in Zeppelin, browse `http://<hostname>:8088/cluster/apps` and check Zeppelin application is running well or not.

<img src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/yarn_applications.png" />


## Spark on Mesos mode
You can simply set up [Spark on Mesos](http://spark.apache.org/docs/latest/running-on-mesos.html) docker environment with below steps.


### 1. Build Docker file

```bash
cd $ZEPPELIN_HOME/scripts/docker/spark-cluster-managers/spark_mesos
docker build -t "spark_mesos" .
```


### 2. Run docker

```bash
docker run --net=host -it \
-p 8080:8080 \
-p 7077:7077 \
-p 8888:8888 \
-p 8081:8081 \
-p 8082:8082 \
-p 5050:5050 \
-p 5051:5051 \
-p 4040:4040 \
-h sparkmaster \
--name spark_mesos \
spark_mesos bash;
```

Note that `sparkmaster` hostname used here to run docker container should be defined in your `/etc/hosts`.

### 3. Verify running Spark on Mesos.

You can simply verify the processes of Spark and Mesos are running well in Docker with below command.

```bash
ps -ef
```

You can also check each application web UI for Mesos on `http://<hostname>:5050/cluster` and Spark on `http://<hostname>:8080/`.


### 4. Configure Spark interpreter in Zeppelin

```bash
export MESOS_NATIVE_JAVA_LIBRARY=[PATH OF libmesos.so]
export SPARK_HOME=[PATH OF SPARK HOME]
```


Don't forget to set Spark `spark.master` as `mesos://127.0.1.1:5050` in Zeppelin **Interpreters** setting page like below.

<img src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/zeppelin_mesos_conf.png" />


### 5. Run Zeppelin with Spark interpreter
After running a single paragraph with Spark interpreter in Zeppelin, browse `http://<hostname>:5050/#/frameworks` and check Zeppelin application is running well or not.

<img src="{{BASE_PATH}}/assets/themes/zeppelin/img/docs-img/mesos_frameworks.png" />

### Troubleshooting for Spark on Mesos

- If you have problem with hostname, use `--add-host` option when executing `dockerrun`

```
## use `--add-host=moby:127.0.0.1` option to resolve
## since docker container couldn't resolve `moby`

: java.net.UnknownHostException: moby: moby: Name or service not known
        at java.net.InetAddress.getLocalHost(InetAddress.java:1496)
        at org.apache.spark.util.Utils$.findLocalInetAddress(Utils.scala:789)
        at org.apache.spark.util.Utils$.org$apache$spark$util$Utils$$localIpAddress$lzycompute(Utils.scala:782)
        at org.apache.spark.util.Utils$.org$apache$spark$util$Utils$$localIpAddress(Utils.scala:782)
```

- If you have problem with mesos master, try `mesos://127.0.0.1` instead of `mesos://127.0.1.1`

```
I0103 20:17:22.329269   340 sched.cpp:330] New master detected at master@127.0.1.1:5050
I0103 20:17:22.330749   340 sched.cpp:341] No credentials provided. Attempting to register without authentication
W0103 20:17:22.333531   340 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
W0103 20:17:24.040252   339 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
W0103 20:17:26.150250   339 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
W0103 20:17:26.737604   339 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
W0103 20:17:35.241714   336 sched.cpp:736] Ignoring framework registered message because it was sentfrom 'master@127.0.0.1:5050' instead of the leading master 'master@127.0.1.1:5050'
```