Spark is available in the Universe and can be installed by using either the DC/OS web interface or the DC/OS CLI.
Prerequisites
- DC/OS and DC/OS CLI installed
- Depending on your security mode, Spark requires service authentication for access to DC/OS.
Security mode | Service account |
---|---|
Disabled | Not available |
Permissive | Optional |
Strict | Required |
For more information about service accounts, see Security:
Default installation
To install the DC/OS Apache Spark service, run the following command on the DC/OS CLI. This installs the Spark DC/OS service, Spark CLI, dispatcher, and, optionally, the history server. See Custom installation to install the history server.
dcos package install spark
Go to the Services > Deployments tab of the DC/OS GUI to monitor the deployment. When it has finished deploying, visit Spark at http://<dcos-url>/service/spark/
.
You can also install Spark via the DC/OS GUI.
Spark CLI
You can install the Spark CLI with this command. This is useful if you already have a Spark cluster running, but need the Spark CLI.
dcos package install spark --cli
Custom installation
You can customize the default configuration properties by creating a JSON options file and passing it to dcos package install --options
. For example, to launch the Dispatcher using the Universal Container Runtime (UCR), create a file called options.json
.
To customize the installation:
-
Create the
options.json
configuration file.{ "service": { "UCR_containerizer": true } }
-
Install Spark with the configuration specified in the
options.json
file:dcos package install --options=options.json spark
-
Run this command to see all configuration options:
dcos package describe spark --config
Customize Spark distribution
DC/OS Apache Spark does not support arbitrary Spark distributions, but Mesosphere does provide multiple pre-built distributions, primarily used to select Hadoop versions.
To use one of these distributions, select your Spark distribution from here, then select the corresponding Docker image from here, then use those values to set the following configuration variables:
{
"service": {
"docker-image": "<docker-image>"
}
}
Customize Spark user
DC/OS Spark user defaults to nobody
, to override it set the following configuration variable:
{
"service": {
"user": "<user>"
}
}
Spark runs all of its components in Docker containers. Since the Docker image contains a full Linux userspace with
its own /etc/users
file, it is possible for the user nobody
to have a different UID inside the
container than on the host system. Although user nobody
has UID 65534 by convention on many systems, this is not
always the case. As Mesos does not perform UID mapping between Linux user namespaces for Docker containerizer,
specifying a service user of nobody
in this case will cause access failures when the container user attempts to open or execute a filesystem
resource owned by a user with a different UID, preventing the service from launching. If the hosts in your cluster
have a UID for nobody
other than 65534, you will need to provide valid UID for nobody
in the configuration to run the service
successfully. For example, on RHEL/Centos based distributions:
{
"service": {
"user": "nobody",
"docker_user": "99"
}
}
Configure Spark virtual network
DC/OS Spark can be launched in a virtual network and configured with network labels.
Here’s an example of Spark configuration for DC/OS overlay network:
{
"service": {
"virtual_network_enabled": true,
"virtual_network_name": "dcos",
"virtual_network_plugin_labels": [
{"key": "key_1", "value": "value_1"},
{"key": "key_2", "value": "value_2"}
]
}
}
When DC/OS Spark deployed in virtual network, all submitted jobs will run in the same network until another network is specified in job submit arguments.
You can check the existing limitations of virtual network support here.
Minimal installation
For development purposes, use dcos-vagrant to install Spark on a local DC/OS cluster.
-
Install DC/OS Vagrant:
Install a minimal DC/OS Vagrant according to the instructions here.
-
Install Spark:
dcos package install spark
-
Run a simple job:
dcos spark run --submit-args="--class org.apache.spark.examples.SparkPi https://downloads.mesosphere.com/spark/assets/spark-examples_2.11-2.3.2.jar 30"
Also, a limited resource environment can restrict how you size your executors, for example with spark.executor.memory
.
Multiple installations
Installing multiple instances of the DC/OS Apache Spark package provides basic multi-team support. Each dispatcher displays only the jobs submitted to it by a given team, and each team can be assigned different resources.
To install multiple instances of the DC/OS Apache Spark package, set each service.name
to a unique name (e.g.: spark-dev
) in your JSON configuration file during installation. For example, create a JSON options file name multiple.json
:
{
"service": {
"name": "spark-dev"
}
}
Install Spark with the options file specified:
dcos package install --options=multiple.json spark
To specify which instance of Spark to use add --name=<service_name>
to your CLI, for example
dcos spark --name=spark-dev run ...
Installation for strict mode
If your cluster is set up for strict security then you will follow these steps to install and run Spark.
Service accounts and secrets
-
Install the
dcos-enterprise-cli
to get CLI security commands (if you have not already done so):dcos package install dcos-enterprise-cli
-
Create a 2048-bit RSA public-private key pair using the Enterprise DC/OS CLI. Create a public-private key pair and save each value into a separate file within the current directory.
dcos security org service-accounts keypair <your-private-key>.pem <your-public-key>.pem
For example:
dcos security org service-accounts keypair private-key.pem public-key.pem
-
Create a new service account,
service-account-id
(for example,spark-principal
) containing the public key,your-public-key.pem
.dcos security org service-accounts create -p <your-public-key>.pem -d "Spark service account" <service-account>
For example:
dcos security org service-accounts create -p public-key.pem -d "Spark service account" spark-principal
In Mesos parlance, a
service-account
is called aprincipal
and so we use the terms interchangeably here.You can verify your new service account using the following command.
dcos security org service-accounts show <service-account>
-
Create a secret (for example,
spark/<secret-name>
) with your service account,service-account
, and private key specified,your-private-key.pem
.# permissive mode dcos security secrets create-sa-secret <your-private-key>.pem <service-account> spark/<secret-name> # strict mode dcos security secrets create-sa-secret --strict <private-key>.pem <service-account> spark/<secret-name>
For example, on a strict-mode DC/OS cluster:
dcos security secrets create-sa-secret --strict private-key.pem spark-principal spark/spark-secret
-
Use the
dcos security secrets list /
command to verify that the secrets were created:dcos security secrets list /
Assigning permissions
Permissions must be created so that the Spark service will be able to start Spark jobs and so the jobs themselves can launch the executors that perform the work on their behalf. There are a few points to keep in mind depending on your cluster:
- Spark runs by default under the Mesos default role, which is represented by the
*
symbol. You can deploy multiple instances of Spark without modifying this default. If you want to override the default Spark role, you must modify these code samples accordingly. We usespark-service-role
to designate the role used below.
Permissions can also be assigned through the UI.
-
Run the following to create the required permissions for Spark:
dcos security org users grant <service-account> dcos:mesos:master:task:user:<user> create --description "Allows the Linux user to execute tasks" dcos security org users grant <service-account> dcos:mesos:master:framework:role:<spark-service-role> create --description "Allows a framework to register with the Mesos master using the Mesos default role" dcos security org users grant <service-account> dcos:mesos:master:task:app_id:/<service_name> create --description "Allows reading of the task state"
Note that above the
dcos:mesos:master:task:app_id:/<service_name>
will likely bedcos:mesos:master:task:app_id:/spark
For example, continuing from above:
dcos security org users grant spark-principal dcos:mesos:master:task:user:nobody create --description "Allows the Linux user to execute tasks" dcos security org users grant spark-principal dcos:mesos:master:framework:role:* create --description "Allows a framework to register with the Mesos master using the Mesos default role" dcos security org users grant spark-principal dcos:mesos:master:task:app_id:/spark create --description "Allows reading of the task state"
Here, we are using the service account
spark-principal
and the usernobody
. -
If you are running the Spark service as
nobody
(as we are in this example) you will need to add an additional permission for Marathon:dcos security org users grant dcos_marathon dcos:mesos:master:task:user:nobody create --description "Allow Marathon to launch containers as nobody"
Install Spark with necessary configuration
-
Make a configuration file with the following before installing Spark, these settings can also be set through the UI:
cat spark-strict-options.json { "service": { "service_account": "<service-account-id>", "user": "<user>", "service_account_secret": "spark/<secret_name>" } }
A minimal example would be:
{ "service": { "service_account": "spark-principal", "user": "nobody", "service_account_secret": "spark/spark-secret" } }
-
Then install:
dcos package install spark --options=spark-strict-options.json
Additional configuration for Spark jobs
You must add configuration parameters to your Spark jobs when submitting them.
Running jobs in strict mode cluster
To run a job on a strict mode cluster, you must add the principal
to the command line. For example:
dcos spark run --verbose --submit-args=" \
--conf spark.mesos.principal=<service-account> \
--conf spark.mesos.containerizer=mesos \
--class org.apache.spark.examples.SparkPi http://downloads.mesosphere.com/spark/assets/spark-examples_2.11-2.3.2.jar 100"
nobody
Running jobs as If you want to use the Docker Engine instead of the Universal Container Runtime, you must specify the user through the SPARK_USER
environment variable:
dcos spark run --verbose --submit-args="\
--conf spark.mesos.driverEnv.SPARK_USER=nobody \
--class org.apache.spark.examples.SparkPi http://downloads.mesosphere.com/spark/assets/spark-examples_2.11-2.3.2.jar 100"
If the hosts in your cluster have a UID for nobody
other than 65534 (see Customize Spark user), you will need to provide a valid UID as a parameter to Docker containerizer via
--conf spark.mesos.executor.docker.parameters=user=UID
:
dcos spark run --verbose --submit-args="\
--conf spark.mesos.driverEnv.SPARK_USER=nobody \
--conf spark.mesos.executor.docker.parameters=user=99 \
--class org.apache.spark.examples.SparkPi http://downloads.mesosphere.com/spark/assets/spark-examples_2.11-2.3.2.jar 100"
Running jobs in virtual network
To run a job in a virtual network and/or with network plugin labels assigned, one need to specify network name and labels in submit arguments:
dcos spark run --verbose --submit-args="\
--conf spark.mesos.network.name=dcos \
--conf spark.mesos.network.labels=key_1:value_1,key_2:value_2 \
--class org.apache.spark.examples.GroupByTest http://downloads.mesosphere.com/spark/assets/spark-examples_2.11-2.3.2.jar"