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The New Virtual Cluster

I ‘ve decided to go virtual, it’s not just that the old cluster takes up a load of room, makes a noise like a jet engine and makes the lights dim in the house. It’s more because I want more flexibility, there are so many interesting things happening at the moment and so many different versions and options that I want to be able to fire up a cluster, shut it down and bring up something else all on the same hardware for benchmarking (and space!) reasons. I got the excellent book “7 databases in 7 weeks” at christmas, some of my classmates at Dundee have run clusters of Mongo and Cassandra which I want to look at and I also want to have a play with Neo4J for the graphing side of protein interactions

So with that in mind I gave the credit card a good workout at overclockers.co.uk and ended up with this lot.

8-core AMD piledriver 4*2Tb disks, 256Gb SSD, 990FX motherboard, 32Gb RAM, a cool case and a fan with blue LEDs (couldn’t resist a bit of bling). I already had a 1Tb drive on another PC that I’ve recycled into this setup too.

Here it all is, just as the fun bit begins – I love building PCs, it looks like you’re a genius at work whereas in fact components are so easy to work with now it’s a doddle to do…

So we’re all up an running, I’m using Windows 7 on the host and I’ve gone for VMware to run the virtual images. The only reason for picking VMWare is that I know how to configure it and I’ve got a Teradata Aster (for work) setup running in VMWare so it made sense.

first of all get a nice Ubuntu template VM up and running, I followed my own instructions of this site to get a good base image running. There are a couple of changes as follows. I’ve used the 64bit version of Ubuntu as I’ve got plenty of RAM to play with

JAVA: I’ve decided to go for the open JDK this time, mainly because it’s a simple $sudo apt-get install openjdk-6-jre from the command line, doesn’t seem to be any compatibility issues so far

NETWORK: I added a second NAT network adapter, the idea is to have one dynamic ip address which will allow the VM to connect to he internet and one with a hardcoded IP address on the 192.168.100.xxx range which I can add to the hosts files in linux which will let the VMs communicate with each other. It also means I can run the Hadoop monitoring tools in IE on the host machine

So armed with my pre-configured template-VM, I copied it onto each of the 4 2Tb drives, setup one with 1*core and 4Gb ram for the namenode and three with 2*cores and 4Gb ram for the datanodes. I fired them all up and spent a bit of time getting the network connectivity all sorted, my /etc/hosts/ file looks like this

#127.0.0.1 localhost
#127.0.1.1 ubuntu
192.168.100.11  hadoop1 localhost
192.168.100.12  hadoop2
192.168.100.13  hadoop3
192.168.100.14  hadoop4

Note that the loopback 127.0.0.1 address are commented, this saves you a load of problems when you come to firing up the cluster later.

I downloaded the Apache version of Hadoop 1.0.4 (latest stable release) and followed the instruction on the Install Hadoop tab, there are a few tools around to help automate this process but I wanted to get stuck in and do it all manually, it’s been a while since I did this so I wanted to get back in to what all the config. steps are. A few things have changed since the last version I installed 0.23 – such as it’s no longer HADOOP_HOME but HADOOP_PREFIX but it’s more or less the same. I did make the effort to set up rcp this time and it made things easier copying the config files around.

The install all went pretty smoothly, I did have one new error that I’ve not seen before… when trying to run my first MapReduce job, it failed with this error.

java.lang.Throwable: Child Error
at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:271)
Caused by: java.io.IOException: Task process exit with nonzero status of 137.
at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:258)

it turns out this was caused by me changing the amount of memory available to each task in the mapred-site.xml file, I deleted this bit and we’re off it’s all running and looks pretty cool too!

I checked out Michael Noll’s excellent site for some advice on Benchmarking and ran the tesdfsio and terasort benchmarks.

http://www.michael-noll.com/blog/2011/04/09/benchmarking-and-stress-testing-an-hadoop-cluster-with-terasort-testdfsio-nnbench-mrbench/

this is the result from the read benchmark

13/02/23 13:27:38 INFO fs.TestDFSIO: ----- TestDFSIO ----- : read
13/02/23 13:27:38 INFO fs.TestDFSIO:            Date & time: Sat Feb 23 13:27:38 PST 2013
13/02/23 13:27:38 INFO fs.TestDFSIO:        Number of files: 10
13/02/23 13:27:38 INFO fs.TestDFSIO: Total MBytes processed: 9212
13/02/23 13:27:38 INFO fs.TestDFSIO:      Throughput mb/sec: 73.95932510644002
13/02/23 13:27:38 INFO fs.TestDFSIO: Average IO rate mb/sec: 92.9056167602539
13/02/23 13:27:38 INFO fs.TestDFSIO:  IO rate std deviation: 47.10222517657025
13/02/23 13:27:38 INFO fs.TestDFSIO:     Test exec time sec: 61.645

 

looks OK to me but if anyone has any info. on what’s good/bad/indifferent in terms of IO – I’d love to know.

Next Steps:

  • Install the rest of the eco-system (pig hive etc. etc.)
  • set up Eclipse and the hadoop plugin (apparently it’s quite a challenge with 1.0.4)
  • make sure all my current MR jobs still run as expected.
  • Crack on with some pratical work on the PhD

 

 

 

 

 

 

  • http://twitter.com/iamBaird Michael Baird

    Hi Chris

    Thought I’d mention my Honours project at Dundee is also working with the Mass Spec. data from Life Sciences, my research guided me to your blog. Noticing a lot of common ground, so it’s been really useful to me so far.

    New PC looks pretty sweet, can understand why you’d want this over the cluster you had before. :)

    Looking at the benchmark, I wasn’t aware such a tool existed, so I ran them on the very basic 2-node cluster of lab computers (i5, 4GB RAM) that I set up last week with the following results. I’m not sure what should be expected, but here they are for your reference.

    13/02/25 21:05:58 INFO fs.TestDFSIO: —– TestDFSIO —– : read
    13/02/25 21:05:58 INFO fs.TestDFSIO: Date & time: Mon Feb 25 21:05:58 GMT 2013
    13/02/25 21:05:58 INFO fs.TestDFSIO: Number of files: 10
    13/02/25 21:05:58 INFO fs.TestDFSIO: Total MBytes processed: 10000
    13/02/25 21:05:58 INFO fs.TestDFSIO: Throughput mb/sec: 56.78237020969729
    13/02/25 21:05:58 INFO fs.TestDFSIO: Average IO rate mb/sec: 62.727989196777344
    13/02/25 21:05:58 INFO fs.TestDFSIO: IO rate std deviation: 18.78827229993447
    13/02/25 21:05:58 INFO fs.TestDFSIO: Test exec time sec: 63.092

    Did you run this IO test on your old cluster? Would be an interesting comparison.

    Michael

    • chillax7

      Sounds good, we must catch up next time I’m in Dundee, I’d love to hear about what you’ve been doing. Are you school of computing or life sciences?

      Your io numbers are at least in the same order of magnitude as mine so we can’t be that far off. One of the masters students has sent me some info on disk testing and io, I’ll run the tests he suggested over th next few days and write it up on here.

      Cheers

      Chris

      • http://twitter.com/iamBaird Michael Baird

        Sure, let me know when you’re next up here. I’m final year BSc Applied Computing.

        My project began as developing a way to visualise the proteomics data, but has now evolved into a small Hadoop cluster and an intuitive interface to try better chain and coordinate the various MapReduce stages required.