| { | |
| "version":"3.0.0", | |
| "gauges":{ | |
| "api.mesosphere.marathon.core.event.impl.stream.HttpEventStreamActorMetrics.number-of-streams":{ | |
| "value":0 | |
| }, | |
| "jvm.buffers.direct.capacity":{ | |
| "value":856750 | |
| }, | |
| "jvm.buffers.direct.count":{ |
| sudo /etc/init.d/mapr-warden restart | |
| sudo maprcli node list -columns ip | |
| maprcli volume list -columns n,p | |
| hadoop fs -ls /var/mapr/local | |
| hadoop fs -stat /var/mapr/local | |
| hadoop fs -stat /var/mapr/local/demo-mapr-slave1.c.inbound-bee-664.internal | |
| hadoop fs -lsr /var/ |
sudo apt-key adv --keyserver keyserver.ubuntu.com --recv E56151BF
DISTRO=$(lsb_release -is | tr '[:upper:]' '[:lower:]')
CODENAME=$(lsb_release -cs)
echo "deb http://repos.mesosphere.io/${DISTRO} ${CODENAME} main" | sudo tee /etc/apt/sources.list.d/mesosphere.list
sudo apt-get -y update
| setup: You have a multi-purpose cluster environment used for end user web traffic and in-house analytics. In this example we have 4 running docker instances of nginx hosting our web application fronted by haproxy and 2 small and 2 medium instances of YARN running on Mapr Hadoop with MapRFS. | |
| note: most organizations underutilize their datacenter resources by separating these two concerns. In this demonstration we are co-locating these separate needs. | |
| <setup scripts> | |
| 1. look at master port 80 (web app) | |
| - technical dive: look at /etc/haproxy/haproxy.cfg on master | |
| 2. lets run a terrasort job | |
| <launch terrasort job> |
~/.ssh/config Host ec2-52-25-163-225.us-west-2.compute.amazonaws.com (this is your DNS)
Compression yes
ForwardAgent yes
this screen cast will demo how to setup an mesosphere cluster for the purposes of analytics. We will show how to provision mesosphere on Google Compute Platform along with installing Mesos-DNS, HDFS and Spark.
We will start with setting up mesosphere on GCE by directing our browser to google.mesosphere.com