Mesos is slowly emerging as a data center operating system for managing all the compute resources across a data center. Mesos runs on any computer running the Linux operating system. It is built using the same principles as the Linux kernel. Let's see how we can install Mesos.
Deploying Spark on a cluster with Mesos
How to do it...
Mesosphere provides a binary distribution of Mesos. The most recent package of the Mesos distribution can be installed from the Mesosphere repositories by performing the following steps:
- Execute Mesos on a Ubuntu OS with the trusty version:
$ sudo apt-key adv --keyserver keyserver.ubuntu.com --recv E56151BF
DISTRO=$(lsb_release -is | tr '[:upper:]' '[:lower:]') CODENAME=$(lsb_release
-cs)
$ sudo vi /etc/apt/sources.list.d/mesosphere.list
deb http://repos.mesosphere.io/Ubuntu trusty main
- Update the repositories:
$ sudo apt-get -y update
- Install Mesos:
$ sudo apt-get -y install mesos
- To connect Spark to Mesos and to integrate Spark with Mesos, make Spark binaries available to Mesos and configure the Spark driver to connect to Mesos.
- Use the Spark binaries from the first recipe and upload them to HDFS:
$ hdfs dfs -put spark-2.1.0-bin-hadoop2.7.tgz spark-2.1.0-bin-hadoop2.7.tgz
- The master URL of a single master Mesos is mesos://host:5050; the master URL of a ZooKeeper-managed Mesos cluster is mesos://zk://host:2181.
- Set the following variables in spark-env.sh:
$ sudo vi spark-env.sh
export MESOS_NATIVE_LIBRARY=/usr/local/lib/libmesos.so
export SPARK_EXECUTOR_URI= hdfs://localhost:9000/user/hduser/spark-2.1.0-bin-
hadoop2.7.tgz
- Run the following commands from the Scala program:
Val conf = new SparkConf().setMaster("mesos://host:5050")
Val sparkContext = new SparkContext(conf)
- Run the following command from the Spark shell:
$ spark-shell --master mesos://host:5050
Mesos has two run modes:
- Fine-grained: In the fine-grained (default) mode, every Spark task runs as a separate Mesos task.Â
- Coarse-grained: This mode will launch only one long-running Spark task on each Mesos machine
- To run in the coarse-grained mode, set the spark.mesos.coarse property:
Conf.set("spark.mesos.coarse","true")