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Hardware Agnostic: Cassandra on Raspberry Pi
Andy Cobley | Lecturer, University of Dundee, Scotland
*Cassandra is hardware agnostic
*So why not run it on a Raspberry Pi ?
*How hard can it be ?
*What can we do with it once it works?
Cassandra on Raspberry Pi
*Andy Cobley
*School of Computing
*University of Dundee
*Twitter: @andycobley
Who Am I ?
*Single chip Linux computer
*500 Meg ram
*Boots off an SD card
*Ethernet port
*(graphics and all you need for a general purpose computer)
Whats a Raspberry Pi ?
Pi with pound coin
*And here’s the Cassandra cluster *
And, here’s one for real
* Power Permitting !
*Cassandra is designed to be fast, fast at writing, fast at reading.
*This laptop with one instance of Cassandra will do 12,000 write
operations
*Raspberry Pi will do 200 !
The Bad News
*Running a external USB drive is actually worse !
*Probably be hardware feature
More bad news !
Raspberry Pi Schematic
*Oracle Java vs OpenJDK
And then there’s Java!
*Raspbian is Debian for the PI
*Uses the Hard floating point accelerator
*Much faster than Debian
*Current Oracle JDK won’t run on it !
And Raspbian
*http://www.oracle.com/technetwork/java/embedded/downloads/java
se/index.html
*Java SE Embedded version 6
*Cassandra might prefer 6
*But
*https://blogs.oracle.com/henrik/entry/oracle_releases_jdk_for_linux
*Preview at:
*https://jdk8.java.net/fxarmpreview/
Oracle java
*Actually not much difference in performance
Hard vs Soft Float
*Cassandra uses compression for performance
*Started in version 1.0
2x-4x reduction in data size
25-35% performance improvement on reads
5-10% performance improvement on writes
The Problem with compression
*Two types:
Google Snappy Compressor (Faster read/writes)
DeflateCompressor (Java zip, slower , better
compression)
*Snappy Compression not available on Pi
(requires native methods, so someone might get it to
work!)
Compression types
*Startup script allocates memory
*Calculates based on number of processors
*Pi reports Zero processors !
*Boom !
*Now fixed
And the startup script
*In Cassandra-env.sh
*JVM_OPTS="$JVM_OPTS -
Djava.rmi.server.hostname=192.168.1.15”
*Or else nodetool will not work between nodes
JMX Config
*C* 1.22. added UseCondCardMark as a JVM Opt
*"for better lock handling especially on hotspot with multicore
processor”
*In cassandra-env.sh
#if [ "$JVM_VERSION" > "1.7" ] ; then
# JVM_OPTS="$JVM_OPTS -
XX:+UseCondCardMark"
#fi
JVM OPT UseCondCardMark
Data stax cassandra_summit_2013_cassandra_raspberrypi-rc1
*We’ve forgotten one thing
*The Pi cost £25
*You can power 4 from USB hub (no need for a power supply on
each one)
*So:
The Good News !
So, have a 64 node computer for £2000
University of Southhampton
*32 node Beowolf cluster:
*Joshua Kiepert, Boise University
Or this
*Adding nodes adds performance
*Adding nodes adds replicas of data
*BUT
*Make sure your ring is balanced,
*Pi’s don’t like to be unbalanced.
Adding nodes is good
*Vnodes (in 1.2) would be very nice
*However at this point I haven’t got 1.2 on Pi running on a cluster
Vnodes
Performance with 3/4 nodes
Performance with 5/6 nodes
*./stress -d 192.168.1.10,192.168.1.11,192.168.1.12 -o insert -I
DeflateCompressor
*Note: nodes to use
*You will get different performance if you insert to less nodes than
you have in your ring
Stress test commands
*Adding a node (in the absence of Vnodes)
Must seed form a known node
Use a program to calculate new keys
Bring up new node with the correct key in
cassandra.yaml
Use node tool to move other nodes
Adding Nodes Procedure
*Python code
import sys
if (len(sys.argv) > 1):
num = int(sys.argv[1])
else:
num = int(raw_input("How many nodes? :"))
for i in range(0,num):
print 'node %d: %d' % (i, (i*(2**127)/num))
Calculating keys
*Use nodetool
sudo ./nodetool -h 192.168.1.10 move
42535295865117307932921825928971026432
*And cleanup
./nodetool -h 192.168.1.10 cleanup
Moving existing nodes
*On Debian, you can free memory from the graphics chip
Cd /boot
sudo cp start.elf start.elf.old
sudo cp arm224_start.elf to start.elf
reboot
Getting more memory
*Under Rasbian
*Run with a monitor plugged for the first time
*Set options for screen memory
*Perhaps disable boot to GUI
Getting more Memory
*I prefer static network addresses
*Edit /etc/network/interfaces
iface eth0 inet static
address 192.168.1.41
netmask 255.255.255.0
network 192.168.1.0
broadcast 192.168.1.255
gateway 192.168.1.254
*
Network address
*Make a master SD card
*Copy it !
*Make sure the master version has no data on it.
*Consider ”Puppet” (though I don’t use it)
Multiple nodes
*See https://github.com/acobley/CassandraStartup
*Put the file in /etc/init.d
*update-rc.d cassandra defaults
Starting as a service
*So for £200 we get an 8 node C* cluster
*It can be reconfigured, blown away, stress tested and generally
abused
*We can simulate data racks, data centers and I hope even long
network delays.
*Hopefully our upcoming MSc in Data Science will use these clusters
Pi is for teaching
*We know C* can be configured to be aware of:
Network racks
Data Centers
*We know we can have replicas are stored across these racks
*How can we play with this cheaply ?
C* is network aware
Proposed teaching tool
10mbs
Hubb
Noise
injection
Switch
2
Switch
1
Pi 1
Pi 2
Pi 3
Pi 1
Pi 2
Pi 3
*Cassandra wouldn’t run on a PI
*It does now.
*Running it on a Pi shook out some Cassandra bugs
*You can run it in a secure lab
Pi is discovery
*Most important, this was pure Geeky Fun
Pi is for fun
*Data Science:
*http://www.computing.dundee.ac.uk/study/postgrad/degreedetails.a
sp?17
Obligatory Plug
*Raspberry Pi is cheap
*C* needs some work to run on it
*You can make clusters cheaply for experimentation
*It’s fun !
C* is Hardware Agnostic
THANK YOU

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Data stax cassandra_summit_2013_cassandra_raspberrypi-rc1

Notes de l'éditeur

  1. (Picture Credits below: Glenn Harris 2012) http://www.southampton.ac.uk/~sjc/raspberrypi/pi_supercomputer_southampton.htm