cluster-computing

Heroku can run Web Dynos and Worker Dynos so that Web Dynos take care of routes and worker Worker Dynos take care of processing works. Since there is a unit of Dyno , It seems using Node.js cluster module is meaningless to me on Heroku. Because Node.js cluster module is to use all cores of server CPU and Dyno seems virtual unit of CPU core to me. Am I right? Or is it still worth to run a node.js app with cluster module? I've found that it actually worth to use cluster module because each dyno has 4 CPU cores. Reference: http://www.quora.com/Heroku/How-powerful-is-one-Heroku-dyno This is an old

I have set up hadoop2.2.0 on 3 clusters. Everything is going fine. NodeManager and Datanode are started in each clusters. But, when I run wordcount example, 100% mapping takes place and it gives following exception: map 100% reduce 0% 13/11/28 09:57:15 INFO mapreduce.Job: Task Id : attempt_1385611768688_0001_r_000000_0, Status : FAILED Container launch failed for container_1385611768688_0001_01_000003 : org.apache.hadoop.yarn.exceptions. YarnException: Unauthorized request to start container. This token is expired. current time is 1385612996018 found 1385612533275 at sun.reflect

What is the difference between Spark standalone and Local mode? Spark standalone is a resource manager which can work on a cluster. It is simply the built in resource manager as opposed to an external one like yarn. Spark local runs without any resource manager, everything runs in a single jvm (you can decide the number of threads). This is aimed for testing locally. 来源： https://stackoverflow.com/questions/40828302/difference-between-spark-standalone-and-local-mode

ssh remotecluster 'bash -s' << EOF > export TEST="sdfsd" > echo $TEST > EOF This prints nothing. Also it still does not work even if I store the variable into file and copy it to remote. TEST="sdfsdf" echo $TEST > temp.par scp temp.par remotecluster ssh remotecluster 'bash -s' << EOF > export test2=`cat temp.par` > echo $test2 > EOF Still prints nothing. So my question is how to pass local variable to the remote machine as a variable ? Answers have been give in this The variable assignment TEST="sdfsd" given in the here document is no real variable assignment, i. e. the variable assignment

I need to run thousands* of models on 15 machines (each of 4 cores), all Windows. I started to learn parallel , snow and snowfall packages and read a bunch of intro's, but they mainly focus on the setup of the master. There is only a little information on how to set up the worker (slave) nodes on Windows. The information is often contradictory: some say that SOCK cluster is practically the easiest way to go , others claim that SOCK cluster setup is complicated on Windows (sshd setup) and the best way to go is MPI . So, what is an easiest way to install slave nodes on Windows? MPI, PVM, SOCK or

I'm trying to compute a dissimilarity matrix based on a big data frame with both numerical and categorical features. When I run the daisy function from the cluster package I get the error message: Error: cannot allocate vector of size X. In my case X is about 800 GB. Any idea how I can deal with this problem? Additionally it would be also great if someone could help me to run the function in parallel cores. Below you can find the function that computes the dissimilarity matrix on the iris dataset: require(cluster) d <- daisy(iris) I've had a similar issue before. Running daisy() on even 5k

I would like to connect to a clustered Oracle database described by this TNS: MYDB= (DESCRIPTION = (ADDRESS = (PROTOCOL = TCP)(HOST = host1)(PORT = 41521)) (ADDRESS = (PROTOCOL = TCP)(HOST = host2)(PORT = 41521)) (LOAD_BALANCE = yes) (CONNECT_DATA = (SERVER = DEDICATED) (SERVICE_NAME= PDSALPO) ) ) I connect normally from my application to non-clustered Oracle using the following configuration: <group name="jdbc"> <prop name="url">jdbc:oracle:thin:@host1:41521:PDSALPO</prop> <prop name="username">user</prop> <prop name="password">pass</prop> </group> Do you know how I can change that to connect