cluster-computing

Imagine you have many clustered servers, across many hosts, in a heterogeneous network environment, such that the connections between servers may have wildly varying latencies and bandwidth. You want to build a map of the connections between servers by transferring data between them. Of course, this map may become stale over time as the network topology changes - but lets ignore those complexities for now and assume the network is relatively static. Given the latencies between nodes in this host graph, calculating the bandwidth is a relative simply timing exercise. I'm having more difficulty

I want to run a multi-node hadoop cluster, with each node inside a docker container on a different host. This image - https://github.com/sequenceiq/hadoop-docker works well to start hadoop in a pseudo distributed mode, what is the easiest way to modify this to have each node in a different container on a separate ec2 host? I did this with two containers running master and slave nodes on two different ubuntu hosts. I did the networking between containers using weave. I have added the images of the containers on docker hub account div4. I installed hadoop in the same way, as its installed on

I want to install Spark Standlone mode to a Cluster with my two virtual machines. With the version of spark-0.9.1-bin-hadoop1, I execute spark-shell successfully in each vm. I follow the offical document to make one vm(ip:xx.xx.xx.223) as both Master and Worker and to make the other(ip:xx.xx.xx.224) as Worker only. But the 224-ip vm cannot connect the 223-ip vm. Followed is 223(Master)'s master log: [@tc-52-223 logs]# tail -100f spark-root-org.apache.spark.deploy.master.Master-1-tc-52-223.out Spark Command: /usr/local/jdk/bin/java -cp :/data/test/spark-0.9.1-bin-hadoop1/conf:/data/test/spark-0

I could get access to a computing cluster, specifically one node with two 12-Core CPUs, which is running with Slurm Workload Manager . I would like to run TensorFlow on that system but unfortunately I were not able to find any information about how to do this or if this is even possible. I am new to this but as far as I understand it, I would have to run TensorFlow by creating a Slurm job and can not directly execute python/tensorflow via ssh. Has anyone an idea, tutorial or any kind of source on this topic? It's relatively simple. Under the simplifying assumptions that you request one process

I have several threads running in parallel from Python on a cluster system. Each python thread outputs to a directory mydir . Each script, before outputting checks if mydir exists and if not creates it: if not os.path.isdir(mydir): os.makedirs(mydir) but this yields the error: os.makedirs(self.log_dir) File "/usr/lib/python2.6/os.py", line 157, in makedirs mkdir(name,mode) OSError: [Errno 17] File exists I suspect it might be due to a race condition, where one job creates the dir before the other gets to it. Is this possible? If so, how can this error be avoided? I'm not sure it's a race

I'm setting up clustering/replication on Tomcat 7 on my local machine, to evaluate it for use with my environment/codebase. Setup I have two identical tomcat servers in sibling directories running on different ports. I have httpd listening on two other ports and connecting to the two tomcat instances as VirtualHosts. I can access and interact with both environments on the configured ports; everything is working as expected. The tomcat servers have clustering enabled like this, in server.xml: <Cluster className="org.apache.catalina.ha.tcp.SimpleTcpCluster" channelSendOptions="8"> <Manager

I am trying to draw circle which colour depends on a "group" attribute in my geojson. I followed a simple example with these colours: map.addSource("data", { type: "geojson", data: url, cluster: true, clusterMaxZoom: 12, // Max zoom to cluster points on clusterRadius: 20 // Radius of each cluster when clustering points (defaults to 50) }); map.addLayer({ 'id': 'population', 'type': 'circle', 'source': 'data', 'paint': { // make circles larger as the user zooms from z12 to z22 'circle-radius': { 'base': 1.75, 'stops': [[12, 2], [22, 180]] }, // color circles by ethnicity, using a match