Upload
aragozin
View
5.400
Download
2
Tags:
Embed Size (px)
DESCRIPTION
Slide deck from NoSQL day in Minsk http://www.belarusjug.org/events/nosql-meetup
Citation preview
Casual mass parallel data processing in Java
Alexey Ragozin
Mar 2014
Building new bicycle …
Build Vs. Buy
Build
• No dedicated team to support infrastructure
• Very specific tasks
• Exclusive use of infrastructure
• Reasonable scale
Buy
• Product can bought as service (internal or external)
• Large scale
• Multi tenancy
• You are going to use advanced features (e.g. map/reduce)
“Casual” computing
• Small computation farms (< 100 servers)
• Team owns both application and grid
• Java platform
• Reasonably short batches (< 24 hours)
• Reasonably small data sets (< 10 TiB)
Simple master slave topology
Master process
Task queue
Slave Slave Slave
Scheduler
AdvertiseTaskReport
Simple master slave topology
Control plane
RMI
Queue / scheduler
Simple in memory queue
May be more complex than just task queue
Data plane
…
Data plane
Never, ever, try to send data over RMI
File system Avoid network mounts!
In-memory key-value Client side sharding works best
Disk database (RDBMS or NoSQL) Consider prefetch of data
Direct socket streaming …
Distributed objects revised
Pit falls of CORBA/RMI • IDL – functional contract
• IDL – protocol
Separating concerns • Functional contract – wrapper object
• Protocol – hidden remote interface
Distributed objects revised
Renewed distributed objects paradigm
Strong • Polymorphism
• Encapsulation Network protocol, caching aspects etc
Weak • Homogenous code base required
• Synchronous network communications
Brute force Build / package
Deploy / SCP
Restart slaves
Start batch
Change code, repeat
Deployment problem
Computation grid software Compile and run batch
Behind scene
Your classes would be collected
Associated with batch
Deployed on participating slaves
Central scheduler topology
Batch controller
Slave Slave Slave
Pull task
Task
Report
Queue server
Task queueBatch controller
Add tasks
Consume
reports
Or more elaborated
Flow organized tasks
• Input data available before task starts
• e.g. Map/Reduce
Collaborative tasks
• Tasks communicate intermediate results to each other
• e.g. physic simulations
Flavors of parallel processing
Get back to data plane
Rules of thumb • Insert / delete – never update
• Write locally (reducing risks)
• Read remotely (retry on error)
• Store input as is File system
Document / column oriented NoSQL
• Input and temporary data is different Choose right store for each
Exploiting file system
Avoid network file systems
• File system concept is not designed to be distributed
• Good network file system cannot not exists
• Use simple remote file access protocols • SCP (unencrypted data transfer options added by CERN guys)
• HTTP (if you really do not want SCP)
Cheap SAN could be build from open source
Algorithmic optimization
Parallel computing • N times speed up will increase
your OPEX and CAPEX cost by N*lg(N)
Algorithmic optimization • Up front costs only
• Orders of magnitude optimization opportunities
• Exciting coding
• Ecological way of computing
Streaming algorithms
Finding N most frequent elements • Min-Count
Estimating number of unique values • HyperLogLog
Distribution histograms
https://github.com/addthis/stream-lib
https://github.com/rwl/ParallelColt
NanoCloud – drastically simplified coding for computing clusters
@Test
public void hello_remote_world() {
Cloud cloud = CloudFactory.createSimpleSshCloud();
cloud.node("myserver.acme.com").exec(new Callable<Void>(){
@Override
public Void call() throws Exception {
String localhost = InetAddress.getLocalHost().toString();
System.out.println("Hi! I'm running on " + localhost);
return null;
}
});
}
As easy as …
All you need is …
NanoCloud requirements
SSHd
Java (1.6 and above) present
Works though NAT and firewalls
Works on Amazon EC2
Works everywhere where SSH works
Master – slave communications
Master process Slave hostSSH
(Single TCP)
Slave
Slave
RMI
(TCP)
std err
std out
std in
diag
Slave
controller
Slave
controller
multiplexed slave streams Agent
Links
NanoCloud • https://code.google.com/p/gridkit/wiki/NanoCloudTutorial
• Maven Central: org.gridkit.lab:telecontrol-ssh:0.7.23
• http://blog.ragozin.info/2013/01/remote-code-execution-in-java-made.html
ANT task • https://github.com/gridkit/gridant
Thank you
Alexey Ragozin [email protected]
http://blog.ragozin.info - my articles http://code.google.com/p/gridkit http://github.com/gridkit - my open source code http://aragozin.timepad.ru - community events in Moscow