When running spark 1.4.0 in a single machine, I can add worker by using this command "./bin/spark-class org.apache.spark.deploy.worker.Worker myhostname:7077". The official documentation points out another way by adding "myhostname:7077" to the "conf/slaves" file followed by executing the command "sbin/start-all.sh" which invoke the master and all workers listed in conf/slaves file. However, the later method doesn't work for me (with time-out error). Can anyone help me with this?
Here is my conf/slaves file (assume the master URL is myhostname:700):
myhostname:700
The conf.slaves file should just be the list of the hostnames, you don't need to include the port # that spark runs on (I think if you do it will try and ssh on that port which is probably where the timeout comes from).
Related
I want to run multiple worker daemons on single machine. As per damienfrancois's answer on what is the minimum number of computers for a slurm cluster it can be done. Problem is currently I am able to execute only 1 worker daemon on one machine. for example
When I run
sudo slurmd -N linux1 -cDvv
sudo slurmd -N linux2 -cDvv
linux1 goes down when I run linux2. Is it possible to run multiple worker daemons on one machine?
Here is my slurm.conf file
as your intention seems to be just testing the behavior of Slurm, I would recommend you to use the front-end mode, where you can create dummy computation nodes in the same machine.
In their FAQ, you have more details, but basically you must configure your installation to work with this mode:
./configure --enable-front-end
And configure the nodes in slurm.conf
NodeName=test[1-100] NodeHostName=localhost
In that guide, they also explain how to launch more than one real daemons in the same node by changing the ports, but for my testing purposes it was not necessary.
Good luck!
I got the same issue as you, I resolved it by modifying the paths of log files as mentioned there multiple slurmd support.
In your slurm.conf for example
SlurmdLogFile=/var/log/slurm/slurmd.log
SlurmdPidFile=/var/run/slurmd.pid
SlurmdSpoolDir=/var/spool/slurmd
must be
SlurmdLogFile=/var/log/slurm/slurmd.%n.log
SlurmdPidFile=/var/run/slurmd.%n.pid
SlurmdSpoolDir=/var/spool/slurmd.%n
Now you can launch multiple slurmd.
Note : I tried with your slurm conf, I think some parameters are missing like define two NodeName instead of one and add which Port to use for each of Nodes.
This works for me
# COMPUTE NODES
NodeName=linux[1-10] NodeHostname=linux0 Port=17004 CPUs=1 State=UNKNOWN
NodeName=linux[11-19] NodeHostname=linux0 Port=17005 CPUs=1 State=UNKNOWN
# PARTITIONS
PartitionName=main Nodes=linux1 Default=YES MaxTime=INFINITE State=UP
PartitionName=dev Nodes=linux11 Default=YES MaxTime=INFINITE State=UP
I have downloaded MSOpenTech Redis version 3.x which includes the long awaited clustering feature. My redis database is all working and I can start my cluster on the min 3 nodes required (in cluster mode). Does anyone know how to configure the cluster (it seems no one knows)?
Installing Linux and running the native Linux version is not an option for me sadly.
Any help would be greatly appreciated.
You can follow the Redis Cluster Tutorial and to create the cluster you can use the redis-trib.rb ruby script, for which you need to install Ruby for Windows.
For example:
> C:\Ruby22\Bin\ruby.exe redis-trib.rb create --replicas 1 192.168.1.1:7000 192.168.1.1:7001 192.168.1.1:7002 192.168.1.1:7003 192.168.1.1:7004 192.168.1.1:7005
Did not have the option to install Ruby on Windows but found the manual steps worked for me. The Ruby script seems to do a lot of checking stuff is setup correctly and is the preferred setup route. So Beware, here be dragons.
Set each node to run in Cluster mode. Edit the redis.windows-service.conf file and uncomment
cluster-enabled yes
cluster-config-file nodes-6379.conf
cluster-node-timeout 15000
restart the service.
Run a powershell window and change to the Redis installed folder and start the redis-cli. e.g.
cd "C:\Program Files\Redis"
.\redis-cli.exe
Now you can join other nodes. Run CLUSTER MEET IPADDRESS PORT for each of the other nodes, than the instance you happen to be on. e.g.
CLUSTER MEET 10.10.0.2 6379
After a few seconds running
CLUSTER NODES
Should list all the nodes connected, but all will be set as MASTER.
On each of the other nodes, run CLUSTER REPLICATE MASTERNODEID. Where MASTERNODEID is the hash-looking value next the node declared "myself" on your master when running CLUSTER NODES. e.g.
CLUSTER REPLICATE b7c767ab3ab7c4a926ac2fed937cf140b96764a7
Now allocate slots to each Master. My setup has three instances, only one master.
for ($slot=0;$slot -le 16383;$slot++) {
.\redis-cli.exe -h REDMST CLUSTER ADDSLOTS $slot
}
Reconnect with redis-cli and try and save data. e.g.
SET foo bar
OK
GET foo
"bar"
Phew! Got most this from reading https://www.javacodegeeks.com/2015/09/redis-clustering.html#InstallingRedis which is not Windows specific.
for windows version:
open the command window then type below command
C:\ProgramFiles\redis>FOR /L %i IN (0,1,16383) DO ( redis-cli.exe -p **6380** CLUSTER ADDSLOTS %i )
6380 is port of master node.
I am new to spark and using spark-1.2.0 with hadoop 2.4.1. I have set up master and four slave nodes. But two of my nodes are not starting.
I have defined IP addresses of nodes in slaves file in spark-1.2.0/conf/ directory.
But when I try to run ./sbin/start-all.sh the error is as follows :
failed to launch org.apache.spark.deploy.worker.Worker
could not find or load main class org.apache.spark.deploy.worker.Worker
This is happening for two nodes. Other two are working fine.
I've also setup spark-env.sh in master as well as slaves. The master also has passwordless ssh connectiviy to the slaves.
I've also tried doing ./bin/spark-class org.apache.spark.deploy.worker.Worker spark://IP:PORT
It gives out the same error as before. Can someone help me with this. Where am I doing mistake?
So I figured out the solution. For all those who are starting new with spark, please check all the jar files in lib folder. I had spark-assembly-1.2.0-hadoop2.4.0.jar file missing in my slave.
I also encountered the same issue. If this is localmode cluster setup then you can run instead:
./sbin/start-master.sh
./sbin/start-slave.sh spark://localhost:7077
Then run:
MASTER=spark://localhost:7077 ./bin/pyspark
I was able to execute my jobs on the shell.
Do remember to setup up conf/slaves and conf/spark-env.sh as per here:
http://pulasthisupun.blogspot.com/2013/11/how-to-set-up-apache-spark-cluster-in.html
Also change localhost to your hostname.
This question already has answers here:
How to use start-all.sh to start standalone Worker that uses different SPARK_HOME (than Master)?
(3 answers)
Closed 4 months ago.
I'm setting up a [somewhat ad-hoc] cluster of Spark workers: namely, a couple of lab machines that I have sitting around. However, I've run into a problem when I attempt to start the cluster with start-all.sh: namely, Spark is installed in different directories on the various workers. But the master invokes $SPARK_HOME/sbin/start-all.sh on each one using the master's definition of $SPARK_HOME, even though the path is different for each worker.
Assuming I can't install Spark on identical paths on each worker to the master, how can I get the master to recognize the different worker paths?
EDIT #1 Hmm, found this thread in the Spark mailing list, strongly suggesting that this is the current implementation--assuming $SPARK_HOME is the same for all workers.
I'm playing around with Spark on Windows (my laptop) and have two worker nodes running by starting them manually using a script that contains the following
set SPARK_HOME=C:\dev\programs\spark-1.2.0-worker1
set SPARK_MASTER_IP=master.brad.com
spark-class org.apache.spark.deploy.worker.Worker spark://master.brad.com:7077
I then create a copy of this script with a different SPARK_HOME defined to run my second worker from. When I kick off a spark-submit I see this on Worker_1
15/02/13 16:42:10 INFO ExecutorRunner: Launch command: ...C:\dev\programs\spark-1.2.0-worker1\bin...
and this on Worker_2
15/02/13 16:42:10 INFO ExecutorRunner: Launch command: ...C:\dev\programs\spark-1.2.0-worker2\bin...
So it works, and in my case I duplicated the spark installation directory, but you may be able to get around this
You might want to consider assign the name by changing SPARK_WORKER_DIR line in the spark-env.sh file.
A similar question was asked here
The solution I used was to create a symbolic link mimicking the master node's installation path on each worker node so when the start-all.sh executing on the master node does its SSH into the worker node, it will see identical pathing to run the worker scripts.
Example in my case, I had 2 Macs and 1 Linux machine. Both Macs had spark installed under /Users/<user>/spark however the Linux machine had it under /home/<user>/spark. One of the Macs was the master node so running the start-all.sh it would error each time on the Linux machine due to pathing (error: /Users/<user>/spark does not exist)).
The simple solution was to mimic the Mac's pathing on the Linux machine using a symbolic link:
open terminal
cd / <-- go to the root of the drive
sudo ln -s home Users <-- create a sym link "Users" pointing to the actual "home" directory.
Hi I am new to Hadoop.
Hadoop Version (2.2.0)
Goals:
Setup Hadoop standalone - Ubuntu 12 (Completed)
Setup Hadoop standalone - Windows 7 (cygwin being used for only sshd) (Completed)
Setup cluster with Ubuntu Master and Windows 7 slave (This is mostly for learning purposes and setting up a env for development) (Stuck)
Setup in relationship with the questions below:
Master running on Ubuntu with hadoop 2.2.0
Slaves running on Windows 7 with a self compiled version from hadoop 2.2.0 source. I am using cygwin only for the sshd
password less login setup and i am able to login both ways using ssh
from outside hadoop. Since my Ubuntu and Windows machine have
different usernames I have set up a config file in the .ssh folder
which maps Hosts with users
Questions:
In a cluster does the username in the master need to be same as in the slave. The reason I am asking this is that post configuration of the cluster when I try to use start-dfs.sh the logs say that they are able to ssh into the slave nodes but were not able to find the location "/home/xxx/hadoop/bin/hadoop-daemon.sh" in the slave. The "xxx" is my master username and not the slaveone. Also since my slave in pure Windows version the install is under C:/hadoop/... Does the master look at the env variable $HADOOP_HOME to check where the install is in the slave? Is there any other env variables that I need to set?
My goal was to use the Windows hadoop build on slave since hadoop is officially supporting windows now. But is it better to run the Linux build under cygwin to accomplish this. The question comes since I am seeing that the start-dfs.sh is trying to execute hadoop-daemon.sh and not some *.cmd.
If this setup works out in future, a possible question that I have is whether Pig, Mahout etc will run in this kind of a setup as I have not seen a build of Pig, Mahout for Windows. Does these components need to be present only on the master node or do they need to be in the slave nodes too. I saw 2 ways of running mahout when experimenting with standalone mode first using the mahout script which I was able to use in linux and second using the yarn jar command where I passed in the mahout jar while using the windows version. In the case Mahout/ Pig (when using the provided sh script) will assume that the slaves already have the jars in place then the Ubuntu + Windows combo does not seem to work. Please advice.
As I mentioned this is more as an experiment rather than an implementation plan. Our final env will be completely on linux. Thank you for your suggestions.
You may have more success going with more standard ways of deploying hadoop. Try out using ubuntu vm's for master and slaves.
You can also try to do a pseudo-distributed deployment in which all of the processes run on a single VM and thus avoid the need to even consider multiple os's.
I have only worked with the same username. In general SSH allows to login with a different login name with the -l command. But this might get tricky. You have to list your slaves in the slaves file.
At least at the manual https://hadoop.apache.org/docs/r0.19.1/cluster_setup.html#Slaves I did not find anything to add usernames. it might be worth trying to add -l login_name to the slavenode in the slave conf file and see if it works.