JRuby Compiler Update, and a Nice Peformance Milestone. Cool stuff.
Tag: jruby
JRuby/Glassfish Investigation
I’ve been keeping an eye on the JRuby scene for a while now and I recently went about benchmarking again. JRuby is interesting because it has the potential to bring robust Java deployment and tools to the Ruby world.
I made a simple widgets application as outlined here and installed JRuby/Glassfish as outlined here (both great articles at AD TechFL) and then proceeded to benchmark:
Glassfish/Jruby on httperf:
Elena:~/Applications/jruby/lib vishnu$ time httperf --client=0/1 --server=localhost --port=8080 --uri=/jruby-demo/widgets/list --send-buffer=4096 --recv-buffer=16384 --num-conns=480 --rate=60 httperf --client=0/1 --server=localhost --port=8080 --uri=/jruby-demo/widgets/list --rate=60 --send-buffer=4096 --recv-buffer=16384 --num-conns=480 --num-calls=1 httperf: warning: open file limit > FD_SETSIZE; limiting max. # of open files to FD_SETSIZE Maximum connect burst length: 2 Total: connections 480 requests 480 replies 480 test-duration 7.999 s Connection rate: 60.0 conn/s (16.7 ms/conn, <=7 concurrent connections) Connection time [ms]: min 1.4 avg 24.6 max 251.3 median 15.5 stddev 35.7 Connection time [ms]: connect 0.1 Connection length [replies/conn]: 1.000 Request rate: 60.0 req/s (16.7 ms/req) Request size [B]: 83.0 Reply rate [replies/s]: min 60.0 avg 60.0 max 60.0 stddev 0.0 (1 samples) Reply time [ms]: response 24.5 transfer 0.0 Reply size [B]: header 360.0 content 1077.0 footer 0.0 (total 1437.0) Reply status: 1xx=0 2xx=438 3xx=0 4xx=0 5xx=42 CPU time [s]: user 1.42 system 5.79 (user 17.7% system 72.4% total 90.1%) Net I/O: 89.1 KB/s (0.7*10^6 bps) Errors: total 0 client-timo 0 socket-timo 0 connrefused 0 connreset 0 Errors: fd-unavail 0 addrunavail 0 ftab-full 0 other 0 real 0m8.008s user 0m1.418s sys 0m5.799s
Glassfish/Jruby on ab:
Elena:~/Applications/jruby/lib vishnu$ ab -n400 http://localhost:8080/jruby-demo/widgets/show/1
This is ApacheBench, Version 1.3d apache-1.3
Copyright (c) 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Copyright (c) 1998-2002 The Apache Software Foundation, http://www.apache.org/
Benchmarking localhost (be patient)
Completed 100 requests
Completed 200 requests
Completed 300 requests
Finished 400 requests
Server Software: Sun
Server Hostname: localhost
Server Port: 8080
Document Path: /jruby-demo/widgets/show/1
Document Length: 611 bytes
Concurrency Level: 1
Time taken for tests: 8.551 seconds
Complete requests: 400
Failed requests: 0
Broken pipe errors: 0
Total transferred: 397600 bytes
HTML transferred: 244400 bytes
Requests per second: 46.78 [#/sec] (mean)
Time per request: 21.38 [ms] (mean)
Time per request: 21.38 [ms] (mean, across all concurrent requests)
Transfer rate: 46.50 [Kbytes/sec] received
Connnection Times (ms)
min mean[+/-sd] median max
Connect: 0 0 0.0 0 0
Processing: 13 21 52.6 16 1019
Waiting: 13 21 52.6 16 1019
Total: 13 21 52.6 16 1019
Percentage of the requests served within a certain time (ms)
50% 16
66% 17
75% 17
80% 17
90% 18
95% 20
98% 37
99% 116
100% 1019 (last request)
Let’s compare. Here’s how a single Mongrel/C does with httperf:
Elena:~/Applications/jruby/lib vishnu$ time httperf --client=0/1 --server=localhost --port=3000 --uri=/widgets/list --send-buffer=4096 --recv-buffer=16384 --num-conns=480 --rate=30 httperf --client=0/1 --server=localhost --port=3000 --uri=/widgets/list --rate=30 --send-buffer=4096 --recv-buffer=16384 --num-conns=480 --num-calls=1 httperf: warning: open file limit > FD_SETSIZE; limiting max. # of open files to FD_SETSIZE Maximum connect burst length: 3 Total: connections 480 requests 480 replies 480 test-duration 16.009 s Connection rate: 30.0 conn/s (33.4 ms/conn, <=18 concurrent connections) Connection time [ms]: min 9.0 avg 56.4 max 607.6 median 9.5 stddev 99.4 Connection time [ms]: connect 0.2 Connection length [replies/conn]: 1.000 Request rate: 30.0 req/s (33.4 ms/req) Request size [B]: 72.0 Reply rate [replies/s]: min 29.4 avg 29.8 max 30.0 stddev 0.3 (3 samples) Reply time [ms]: response 55.7 transfer 0.5 Reply size [B]: header 278.0 content 1011.0 footer 0.0 (total 1289.0) Reply status: 1xx=0 2xx=480 3xx=0 4xx=0 5xx=0 CPU time [s]: user 3.91 system 11.35 (user 24.4% system 70.9% total 95.3%) Net I/O: 39.9 KB/s (0.3*10^6 bps) Errors: total 0 client-timo 0 socket-timo 0 connrefused 0 connreset 0 Errors: fd-unavail 0 addrunavail 0 ftab-full 0 other 0 real 0m16.017s user 0m3.912s sys 0m11.354s
And Mongrel/C with ab:
Elena:~/Applications/jruby/lib vishnu$ ab -n400 http://localhost:3000/widgets/list
This is ApacheBench, Version 1.3d apache-1.3
Copyright (c) 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Copyright (c) 1998-2002 The Apache Software Foundation, http://www.apache.org/
Benchmarking localhost (be patient)
Completed 100 requests
Completed 200 requests
Completed 300 requests
Finished 400 requests
Server Software: Mongrel
Server Hostname: localhost
Server Port: 3000
Document Path: /widgets/list
Document Length: 1011 bytes
Concurrency Level: 1
Time taken for tests: 7.974 seconds
Complete requests: 400
Failed requests: 0
Broken pipe errors: 0
Total transferred: 515600 bytes
HTML transferred: 404400 bytes
Requests per second: 50.16 [#/sec] (mean)
Time per request: 19.93 [ms] (mean)
Time per request: 19.93 [ms] (mean, across all concurrent requests)
Transfer rate: 64.66 [Kbytes/sec] received
Connnection Times (ms)
min mean[+/-sd] median max
Connect: 0 0 0.0 0 0
Processing: 9 19 63.4 11 1167
Waiting: 9 19 63.4 11 1167
Total: 9 19 63.4 11 1167
Percentage of the requests served within a certain time (ms)
50% 11
66% 12
75% 12
80% 12
90% 13
95% 15
98% 113
99% 149
100% 1167 (last request)
Observations
- Advantage: For the same number of connections, Glassfish/Jruby versus a single instance Mongrel/C has twice the reply rate in half the benchmark time.
- Disadvantage: Request latency is more for Glassfish/Jruby. (around 5ms av. more)
- Disadvantage: JRuby Ruby/Rails support is not perfect but very good.
- Advantage: Much simpler to set up. Copy the war file to the server and deployment is done, autodeployment is also possible w/o restarting Glassfish.
- Advantage: Much simpler to install and get going on the server, just requires a JDK, glassfish installed anywhere, etc.
- Advantage: Runs on Java, so Java deployment experience will do.
- Disadvantage: Does not support C library extensions for Ruby, question: how many of them are there & useful (memcached?) ?
- Advantage: Supports Java libraries kind of easily, again question: how many of them are there, useful and relevant?
- Question: This benchmark is versus a single mongrel, how does cluster vs. cluster compare?
- Question: Is glassfish clustering easy? Observation: mongrel clustering is cumbersome at present. Maybe swiftiply will help there with dynamic addition of mongrels?
Java + Ruby
I’m going to write a bit about Ruby in Java land. Much of this post stems from the Sun stall at FOSS.in: to put it mildly, it was perhaps the most enthusiastic stall I’ve seen at a conference ever. The energy of the guys there was incredible and their enthusiasm to show things off (and Sun does have a lot of nice things to show off: dtrace, ZFS, glassfish) really made me give a second glance to the entire Java + Ruby thing: JRuby, or a Ruby implementation in Java, and Rails deployment via the Java Enterprise stack. I’ve been playing around with it for a day, and I’ve got just one thing to say. It’s cool 🙂
A bit of a background: I’m not a Java guy. Repeat, not a Java guy. So when people say that the Java toolset is amazing, I’ve always not understood what they meant. Who needs toolsets, widgets, a GUI, an administrative console; when you’ve got SSH & shell scripting? The last four months developing SlideShare however, have been a bit of a revelation: managing servers is a tough job. Our current stack includes a lighttpd->pound->mongrel chain, and monit to watch these processes and start them off if something goes wrong. Lots of glue code, and solutions that seem hacks now (a separate uploader mongrel, anyone?). Anyways, the role of a sysadmin sucks: big time, and the toolsets to manage a traditional *nix environment requires too much of manual work. [Stuff such as Puppet might negate this, but I digress…]. So it was kinda really nice to switch on Glassfish, drop a .war into an autodeploy directory and watch the application come alive. And have an actual GUI console to manage all this stuff, read up on the logs, configure routes & services, etc.
I’ve not done much: just installed Glassfish, played around with asadmin start-domain domain1 and the console, and then installing Jruby and the easy Java + Ruby integration. Look at this code, for e.g.:
#!/usr/bin/env jruby
require 'java'
set = java.util.TreeSet.new
set.add "foo"
set.add "Bar"
set.add "baz"
set.each do |v|
puts "value: #{v}"
end
string = java.lang.String.new
string = "Vishnu"
puts string
Sweet ain’t it? One of Ruby’s selling points has always been that it’s easier to drop into a low level language (C) and write extensions for expensive functionality, thus negating Ruby’s slow performance. But stuff like the code sample above should make it pure nirvana for expensive operations. I haven’t compared speeds yet: I’ll do that soon using a simple Web framework like Camping & then a simple Rails app (i.e. Camping/WebBrick on Ruby and JRuby and Camping/Mongrel vs Camping/Glassfish: if I can get it running). JRuby isn’t perfect yet: Rails applications aren’t officially supported, but I hope to get a useful app deployed on localhost soon, and if there’s interest, deploy it to my slice. It’s an upward slope though for me, since the whole Java deployment scene [making a WAR] seems so bloody complicated (why, oh why?) but a good indicator for good Ruby/Rails deployment on JRuby would be to just type in rake deploy and have your code get into the whole Glassfish stack.
