Skip to main content

Erlang nodes and /etc/hosts configuration

The basic unit of erlang distributed programming is erlang node. To find an erlang node is a prerequisite for running program on it. The configuration of /etc/hosts and domain resolving may affect. The issue came to me when I tested discoproject on two computers and got "Node failure".

Let's start with the classic example in Pragmatic Programming Erlang. First we start two erlang shell on the same machine, one named gandalf, the other named bilbo:

erl -sname gandalf
erl -sname bilbo

In node bilbo, you try "net_adm:ping(gandalf@localhost)." and you suppose to get a "pong" as response. Unfortunately, this may not happen on every computers, it is highly possible you may get a "pang" or some error massage. But you may start erlang shells in another way:

erl -sname gandalf@localhost
erl -sname bilbo@localhost

This time, you should finally get a "pong"(if you got "pang" before). The magic lies here, if start an erlang shell with "@localhost", and try "node()." you will get "gandalf@localhost". But if you start an erlang shell without "@localhost", you may get a different response when "node().", in may Ubuntu it is "gandalf@socrates-ubuntu-9". The reason are in /etc/hosts, in may Ubuntu there such two lines inside:

127.0.0.1 localhost
127.0.1.1 socrates-ubuntu-9

The second line defines a loop back domain other than localhost, and it guide the erlang shell to use it as default. Here we may comes to the distributed programming on two computers. Assume we have computers, one is "socrates-ubuntu-9" and the other is "socrates-ubuntu". On "socrates-ubuntu-9", we start an erlang shell "erl -sname gandalf", and on "socrates-ubuntu" we start an erlang shell "erl -sname bilbo". If "socrates-ubuntu-9" and "socrates-ubuntu" can find each other by domain names and we don't have a firewall issue, you may successfully get a "pong" in "socrates-ubuntu" by command:

netadm:ping( list_to_atom("gandalf@socrates-ubuntu-9")).

If no DNS available, a list of ip/name pair may be added to /etc/hosts of each computer.

Comments

Popular posts from this blog

A simple implementation of DTW(Dynamic Time Warping) in C#/python

DTW(Dynamic Time Warping) is a very useful tools for time series analysis. This is a very simple (but not very efficient) c# implementation of DTW, the source code is available at  https://gist.github.com/1966342  . Use the program as below: double[] x = {9,3,1,5,1,2,0,1,0,2,2,8,1,7,0,6,4,4,5}; double[] y = {1,0,5,5,0,1,0,1,0,3,3,2,8,1,0,6,4,4,5}; SimpleDTW dtw = new SimpleDTW(x,y); dtw.calculateDTW(); The python implementation is available at  https://gist.github.com/3265694  . from python-dtw import Dtw import math dtw = Dtw([1, 2, 3, 4, 6], [1, 2, 3, 5],           distance_func=lambda x, y: math.fabs(x - y)) print dtw.calculate() #calculate the distance print dtw.get_path() #calculate the mapping path

Change the default user when start a docker container

When run(start) a docker container from an image, we can specify the default user by passing -u option in command line(In https://docs.docker.com/engine/reference/run/#user ). For example docker run -i -t -u ubuntu ubuntu:latest /bin/bash We can also use the USER instruction in DOCKERFILE to do the same thing(In https://docs.docker.com/engine/reference/builder/#user), note that the option in command line will override the one in the DOCKERFILE. And there is actually another way to start a container with neither DOCKERFILE nor -u option, just by a command like: docker run -i -t ubuntu:latest /bin/bash # with ubuntu as the default user This happens when your start the container from an image committed by a container with ubuntu as the default user. Or in detail: Run a container from some basic images, create ubuntu user inside it, commit the container to CUSTOM_IMAGE:1 . Run a container from CUSTOM_IMAGE:1 with "-u ubuntu" option, and commit the container to CUSTOM...

Notes on Sequential Pattern Mining (2) -- Partial Order Pattern Mining and Contrast Mining

1. In , the authors induce TEIRESIAS algorithms to mining combinatorial patterns with gap constraints in biological sequences. The patterns TEIRESIAS mined is similiar with the common sequential patterns, but it could contain "." the wild card which is also in the alphbel of the sequences database standing for any other item available, for example pattern "A..B" is a length-4 pattern, with two arbitrary items between the first A and the last B. Patterns "AC.B", "AADB" are all said to be more specific than pattern "A..B". TEIRESIAS mining all the maximal patterns () with a support over a min threshold K. There some key points of TEIRESIAS algorithms: 1)The growth of the patterns The growth of the patterns is accomplished by convolute current pattern by a short length pattern. Pattern A and pattern B are convolutable if the last L(very small) characters of pattern A is the same as the first L characters of pattern B, then ...