Spark docker images

These images are part of the bigdata docker image series. All of the images use the same base docker image which contains advanced configuration loading. For more detailed instruction see the README in the docker-bigdata-base repository.

Configuration loading

The containers supports multiple configuration loading mechanism. (All of the configuration loading is defined in the base-docker image. The configuration methods are stored in the /opt/configuration directory and could be selected by setting the environment variable CONFIG_TYPE

You can see various example configuration, ansible and docker-compose scripts at the main umbrella repository.

The three main configuration loading mechanis is:

CONFIG_TYPE=simple: Using some simple default and configuration defined with environment variables.
CONFIG_TYPE=consul: Using configuration files (and not list of key: value pairs) stored in a consul. Supports dynamic restart if the configuration is changing.
CONFIG_TYPE=springconfig: Using configuration from the spring config server.

Simple configuration

This is the default configuration.

Main behaviours:

Every configuration file is defined with a list of key: value pairs, even if they will be converted finally to hadoop xml format
The configfile creation process follows the steps:
- Copy the defaults file (from /opt/defaults) to the destination dir (defined by the environment variable CONF_DIR). These files contain key value pairs.
- Append the configuration parameter from the environment variable according to a naming convention. For example CORE-SITE_fs.default.name=hdfs://localhost:9000 will be copied to the core-site.xml
- Transform the result file (defaults + value from env) to the final configuration based on the extension. For example if the extension is xml then the key value pairs will be converted to HADOOP xml file format.

Naming convention for set config keys from enviroment variables

To set any configuration variable you shold follow the following pattern:

NAME.EXTENSION.configkey=VALUE

The extension could be any extension which has a predefined transformation (currently xml, yaml, properties, configuration, yaml, env, sh)

In case there is a default configuration file in the /opt/defaults the EXTENSION part is optional as the extenasion (which is the base of the transformation selection) could be determined by name:

NAME.configkey=VALUE

You can also you dot instead of underscores:

NAME.EXTENSION_configkey=VALUE
NAME_configkey=VALUE

examples:

CORE-SITE_fs.default.name: "hdfs://localhost:9000"
HDFS-SITE_dfs_namenode_rpc-address: "localhost:9000"
HBASE-SITE.XML_hbase_zookeeper_quorum: "localhost"

Example

The simple directory in the bigdata-docker project contains a docker-compose example using simple configuration loading

Consul config loading

Could be activated with CONFIG_TYPE=consul

The starter script list the configuration file names based on a consul key prefix. All the files will be downloaded from the consul key value store and the application process will be started with consul-template (enable an automatic restart in case of configuration file change)
CONSUL_PATH contains the prefix of the subtree in the consul key value store (default is conf)
if CONSUL_PATH is not set you can use CONSUL_PREFIX and CONSUL_KEY values. As the default CONSUL_PREFIX is config, it's enough to set the CONSUL_KEY if the configuration is under the key config/something
Consul server location could set with CONSUL_SERVER environment variable (default is localhost:8500)

Spring conig server configuration loading

In this case the configuration files will be downloaded from spring config server with the following convention:

Spring application is used as the config file name (eg. core-site.xml and as the - is prohibiited, core_site) Spring profile is used as the configuration/component name (eg. hdfs or namenode)

The config server first download the list of the actual configuration files for the current CONFIG_TYPE. (spring application name is bigdata, profile is the $CONFIG_TYPE)

For example:

configfiles:
     hdfs:
        core_site: xml
        hdfs_site: xml
        log4j: properties
     hbase:
        core_site: xml
        hdfs_site: xml
        log4j: properties
        hbase: xml

At the next step we download the required files one by one and convert to the desired file format (properties, xml, ...)

Configuration

CONFIG_SERVER_URL: the url of the config server eg. http://localhost:8888
CONFIG_GROUP: the profile part of the config server query (eg. hdfs, namenode, etc.)
CONF_DIR: the destination directory

Running

Using the image depends from the configuration loading and the exact use case. You can find multiple examples in this repository to use the images:

on the local machine using docker-compose
on remote cluster using ansible
on remote cluster and local macine with using docker-compose downloaded from the consul image.

Smoketest

docker run elek/spark-base:latest /opt/spark/bin/run-example SparkPi 10 10

Versioning policy

The latest tag points to the latest configuration loading and the latest stable apache version.

If there is plain version tag without prefix it is synchronized with the version of the original apache software.

It there is a prefix (eg. HDP) it includes a specific version from a specific distribution.

As the configuration loading in the base image is constantly evolving even the tags of older releases may be refreshed over the time.

TODO

R interface is not yet supported (at least in this images)

flokkr/docker-spark