Zeppelin Interpreter on Docker
Zeppelin service runs on local server. Zeppelin is able to run the interpreter in the docker container, Isolating the operating environment of the interpreter through the docker container. Zeppelin can be easily used without having to install python, spark, etc. on the local node.
Key benefits are
- Interpreter environment isolating
- Not need to install python, spark, etc. environment on the local node
- Docker does not need to pre-install zeppelin binary package, Automatically upload local zeppelin interpreter lib files to the container
- Automatically upload local configuration files (such as spark-conf, hadoop-conf-dir, keytab file, ...) to the container, so that the running environment in the container is exactly the same as the local.
- Zeppelin server runs locally, making it easier to manage and maintain
Prerequisites
- apache/zeppelin docker image
- Spark >= 2.2.0 docker image (in case of using Spark Interpreter)
- Docker 1.6+ Install Docker
- Use docker's host network, so there is no need to set up a network specifically
Docker Configuration
Because DockerInterpreterProcess
communicates via docker's tcp interface.
By default, docker provides an interface as a sock file, so you need to modify the configuration file to open the tcp interface remotely.
vi /etc/docker/daemon.json
, Add tcp://0.0.0.0:2375
to the hosts
configuration item.
{
...
"hosts": ["tcp://0.0.0.0:2375","unix:///var/run/docker.sock"]
}
hosts
property reference: https://docs.docker.com/engine/reference/commandline/dockerd/
Security warning
Making the Docker daemon available over TCP is potentially dangerous: as you can read here, the docker daemon typically has broad privileges, so only trusted users should have access to it. If you expose the daemon over TCP, you must use firewalling to make sure only trusted users can access the port. This also includes making sure the interpreter docker containers that are started by Zeppelin do not have access to this port.
Quickstart
Modify these 2 configuration items in
zeppelin-site.xml
.<property> <name>zeppelin.run.mode</name> <value>docker</value> <description>'auto|local|k8s|docker'</description> </property> <property> <name>zeppelin.docker.container.image</name> <value>apache/zeppelin</value> <description>Docker image for interpreters</description> </property>
set timezone in zeppelin-env.sh
Set to the same time zone as the zeppelin server, keeping the time zone in the interpreter docker container the same as the server. E.g,
"America/New_York"
or"Asia/Shanghai"
export ZEPPELIN_DOCKER_TIME_ZONE="America/New_York"
Build Zeppelin image manually
To build Zeppelin image, support Kerberos certification & install spark binary.
Use the /scripts/docker/interpreter/Dockerfile
to build the image.
FROM apache/zeppelin:0.8.0
MAINTAINER Apache Software Foundation <dev@zeppelin.apache.org>
ENV SPARK_VERSION=2.3.3
ENV HADOOP_VERSION=2.7
# support Kerberos certification
RUN export DEBIAN_FRONTEND=noninteractive && apt-get update && apt-get install -yq krb5-user libpam-krb5 && apt-get clean
RUN apt-get update && apt-get install -y curl unzip wget grep sed vim tzdata && apt-get clean
# auto upload zeppelin interpreter lib
RUN rm -rf /zeppelin
RUN rm -rf /spark
RUN wget https://www-us.apache.org/dist/spark/spark-${SPARK_VERSION}/spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION}.tgz
RUN tar zxvf spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION}.tgz
RUN mv spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION} spark
RUN rm spark-${SPARK_VERSION}-bin-hadoop${HADOOP_VERSION}.tgz
Then build docker image.
# build image. Replace <tag>.
$ docker build -t <tag> .
How it works
Zeppelin interpreter on Docker
Zeppelin service runs on local server, it auto configure itself to use DockerInterpreterLauncher
.
DockerInterpreterLauncher
via DockerInterpreterProcess
launcher creates each interpreter in a container using docker image.
DockerInterpreterProcess
uploads the binaries and configuration files of the local zeppelin service to the container:
- ${ZEPPELIN_HOME}/bin
- ${ZEPPELIN_HOME}/lib
- ${ZEPPELIN_HOME}/interpreter/${interpreterGroupName}
- ${ZEPPELIN_HOME}/conf/zeppelin-site.xml
- ${ZEPPELIN_HOME}/conf/log4j.properties
- ${ZEPPELIN_HOME}/conf/log4j_yarn_cluster.properties
- HADOOP_CONF_DIR
- SPARK_CONF_DIR
- /etc/krb5.conf
- Keytab file configured in the interpreter properties
- zeppelin.shell.keytab.location
- spark.yarn.keytab
- submarine.hadoop.keytab
- zeppelin.jdbc.keytab.location
- zeppelin.server.kerberos.keytab
All file paths uploaded to the container, Keep the same path as the local one. This will ensure that all configurations are used correctly.
Spark interpreter on Docker
When interpreter group is spark
, Zeppelin sets necessary spark configuration automatically to use Spark on Docker.
Supports all running modes of local[*]
, yarn-client
, and yarn-cluster
of zeppelin spark interpreter.
SPARK_CONF_DIR
Configuring in the zeppelin-env.sh
Because there are only spark binary files in the interpreter image, no spark conf files are included. The configuration file in the
spark-<version>/conf/
local to the zeppelin service needs to be uploaded to the/spark/conf/
directory in the spark interpreter container. So you need to settingexport SPARK_CONF_DIR=/spark-<version>-path/conf/
in thezeppelin-env.sh
file.Configuring in the spark Properties
You can also configure it in the spark interpreter properties.
properties name Value Description SPARK_CONF_DIR /spark- -path.../conf/ Spark- -path/conf/ path local on the zeppelin service
HADOOP_CONF_DIR
Configuring in the zeppelin-env.sh
Because there are only spark binary files in the interpreter image, no configuration files are included. The configuration file in the
hadoop-<version>/etc/hadoop
local to the zeppelin service needs to be uploaded to the spark interpreter container. So you need to settingexport HADOOP_CONF_DIR=hadoop-<version>-path/etc/hadoop
in thezeppelin-env.sh
file.Configuring in the spark Properties
You can also configure it in the spark interpreter properties.
properties name Value Description HADOOP_CONF_DIR hadoop- -path/etc/hadoop hadoop- -path/etc/hadoop path local on the zeppelin service
Accessing Spark UI (or Service running in interpreter container)
Because the zeppelin interpreter container uses the host network, the spark.ui.port port is automatically allocated, so do not configure spark.ui.port=xxxx
in spark-defaults.conf
Future work
- Configuring container resources that can be used by different interpreters by configuration.
Development
Instead of build Zeppelin distribution package and docker image everytime during development, Zeppelin can run locally (such as inside your IDE in debug mode) and able to run Interpreter using DockerInterpreterLauncher by configuring following environment variables.
- zeppelin-site.xml
Configuration variable | Value | Description |
---|---|---|
ZEPPELIN_RUN_MODE |
docker |
Make Zeppelin run interpreter on Docker |
ZEPPELIN_DOCKER_CONTAINER_IMAGE |
<image>:<version> |
Zeppelin interpreter docker image to use |