![Split lines by columns
String fields[] = line.split("|");
Sample timmings:
real 1m0.670s
user 1m1.252s
sys 0m6.015s
ETA: 3 hours, 18 minutes
~ 6 x slower!!! Exceeded the performance budget](https://image.slidesharecdn.com/codebits20082-122747558637-phpapp01/85/High-Performance-With-Java-14-320.jpg)
![Tune
String fields[] = split(line, '|', 3,10,11);
Sample timmings:
real 0m13.450s
user 0m13.425s
sys 0m3.965s
ETA: 44 minutes e 35 seconds
14 extra lines of java code and we’re back on track](https://image.slidesharecdn.com/codebits20082-122747558637-phpapp01/85/High-Performance-With-Java-16-320.jpg)
![Remebering old times
• In C/C++ you could map structs to
memory
• The amount of information needed is 16
bytes per SIM card (phone number, start
date, end date, type of card – 4 * 4 bytes)
• ~ 343 M if stored in a compact form (int[])
• Sort the data and wrap the array in a List
• Use Collections.binarySearch to do the
heavy lifting](https://image.slidesharecdn.com/codebits20082-122747558637-phpapp01/85/High-Performance-With-Java-22-320.jpg)
![Code snippets – A (way) faster split
public static String[] split(String l, char sep, int... columns) {
String[] fields = new String[columns.length];
int start = 0, column = 0, end, i = 0;
while((end = l.indexOf(sep, start)) != -1) {
if(column++ == columns[i]) {
fields[i] = l.substring(start, end);
if(++i == columns.length)
return fields;
}
start = end + 1;
}
if(column == columns[i])
fields[i] = l.substring(start);
return fields;
}
String fields[] = split(line, '|', 3,10,11);](https://image.slidesharecdn.com/codebits20082-122747558637-phpapp01/85/High-Performance-With-Java-31-320.jpg)
![Static in-memory “database”: Poor
man’s solution (but as fast as it gets)
public class ClientFile implements List<CardInfo>, RandomAccess {
static final int CLIENT_SIZE = 16;
int[] clients;
public ClientFile() throws FileNotFoundException, IOException {
File f = new File("clientes.db");
FileInputStream fs = new FileInputStream(f);
int client_count = (int)f.length() / CLIENT_SIZE;
clients = new int[client_count * 4];
byte b[] = new byte[(int) f.length()];
fs.read(b);
for(int i = 0;i != client_count; ++i) {
clients[i * 4] = toi(b, i * CLIENT_SIZE);
clients[i * 4 + 1] = toi(b, i * CLIENT_SIZE + 4);
clients[i * 4 + 2] = toi(b, i * CLIENT_SIZE + 8);
clients[i * 4 + 3] = toi(b, i * CLIENT_SIZE + 12);
}
}
// map byte[] to integer
public int toi(byte[] b, int offset) {
return ((0xFF & b[offset]) << 24) +
((0xFF & b[offset + 1]) << 16) +
((0xFF & b[offset + 2]) << 8) +
(0xFF & b[offset + 3]);
}
(…)](https://image.slidesharecdn.com/codebits20082-122747558637-phpapp01/85/High-Performance-With-Java-32-320.jpg)
![Static in-memory “database”:
(continued)
(…)
public CardInfo get(int index) {
return new CardInfo(clients[index * 4],
clients[index * 4 + 1],
clients[index * 4 + 2],
clients[index * 4 + 3]);
}
public CardInfo getCardInfo(String msisdn, String yymmdd, String hhmmss){
Calendar cal = Calendar.getInstance();
cal.set(i(yymmdd, 0, 1) + 2000, i(yymmdd, 2, 3) - 1, i(yymmdd, 4, 5),
i(hhmmss, 0, 1), i(hhmmss, 2, 3), i(hhmmss, 4, 5));
int idx = Collections.binarySearch(this,
new Key(i(msisdn),
(int)(cal.getTimeInMillis() / 1000)));
if (idx < 0) {
return null;
}
return get(idx);
}](https://image.slidesharecdn.com/codebits20082-122747558637-phpapp01/85/High-Performance-With-Java-33-320.jpg)
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High Performance With Java
- 1. High Performance withJava malduarte@gmail.com
- 2. Foreword In the beginningwas the Tao. The Tao gave birth to Space and Time. Therefore Space and Time are Yin and Yang of programming. Programmers that do not comprehend the Tao are always running out of time and space for their programs. Programmers that comprehend the Tao always have enough time and space to accomplish their goals. How could it be otherwise? From www.canonical.org/~kragen/tao-of-programming.htm
- 3. What is HighPerformance? •HitachiH8 8 bit cpu, 16 MHz •32 kb Ram 2 X Sun SPARC Enterprise M5000 6 Quad Core 2.4ghz - 6 MB L2 Cache,Sparc VII CPUs, 48 hw threads, 32Gb RAM Sources: Sun Microsystems: www.sun.com/servers/midrange/m5000/ WikiPedia: en.wikipedia.org/wiki/Lego_Mindstorms Aad van der Steen HPC Page - www.phys.uu.nl/~steen/web08/sparc.html
- 4. High Performance isall about “Delivering solutions which meet requirements within time and space constraints using available resources rationally” The most important resource: brain time. HW increases performance with time, brain decreases performance with time.
- 5. Why Java? • Maturetechnology • Speedy and Stable VMs (those who were burned in the early days still loath it, though) • Lots of high quality tools • Lots of high quality available libraries • Large ecosystem • NOT the language itself
- 6.
- 7. A small casestudy • Goal: Analyse 17 G (gzip’ed) worth of MSC Call Detail Records (CDRs in Mobile Operator Lingo) Snippet: 04|001|26806XXXXXXXXXX|3519XXXXXXXX|3519800049344611|||||| 081105|002559|||00062|00|000-076|015-113||||MALM1 |0|01|9XXXXXXXX|11|||2|1|MICOUT|0|0||||||||||||||||||331985|268061011305482|B AL10A|15|22|12402523|||||||||||||||||||||||||||||||02|||||100001011305482||3e3212003 4df00|||0|1|17|||1|||3||1|01|3519XXXXXXXX||||1|01|3519XXXXXXXX||25||||||0|01| 9XXXXXXXX|002559|081105|00062||2||5||||||||||||3||||||||||||||||||||||||||||||||||||||||||||||||||| |||||||||||||||| Note: Sensitive information was hidden
- 8. A bit moreinfo • Aproximatly 170 G uncompressed • Exactly 359 014 695 cdrs • Trivia: about 3 days worth of GSM call logs. • Correlate CDRs with Customer information • Peformance goal : running time must be below one hour.
- 9.
- 10. If you don’ttake a temperature you can’t find a fever • Measure the progress as the system is implemented • Make *honest* measurements. Prove yourself wrong. • Avoid premature optimization – How can you know? If you’re within your performance budget don’t worry (*) Fat Man’s Law X – “House of God” Samuel Shen - http://en.wikipedia.org/wiki/The_House_of_God
- 11. "The journey ofa thousand miles starts with a single step." Lao Tse • Line read performance 1811229 Line Sample Sample timmings: real 0m13.872s user 0m13.366s sys 0m4.056s ETA: ~45 minutes
- 12. I/O Tips • UseMemory Mapped Files (see FileChannel.map and MappedByteBuffer APIS) • Use Buffered I/O - BufferedInputStream • Optimal buffer size multiple of OS page size (usually 8k) • If the process is I/O bound and have fast CPUs, consider processing compressed files
- 13. One more step •Extract date of call and customer phone number 04|001|268061100021547|3519XXXXXXXX|3519800049344611|||||| 081105|002559|||00062|00|000-076|015-113||||MALM1 |0|01|9XXXXXXXX|11|||2|1|MICOUT|0|0||||||||||||||||||331985|2680610113 05482|BAL10A|15|22|12402523|||||||||||||||||||||||||||||||02|||||100001011305 482||3e32120034df00|||0|1|17|||1|||3||1|01|3519XXXXXXXX||||1|01|351 9XXXXXXXX||25||||||0|01|9XXXXXXXX|002559|081105|00062||2||5||||||| |||||3||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| Censored numbers to protect the innocent
- 14. Split lines bycolumns String fields[] = line.split("|"); Sample timmings: real 1m0.670s user 1m1.252s sys 0m6.015s ETA: 3 hours, 18 minutes ~ 6 x slower!!! Exceeded the performance budget
- 15. When in doubt,profile ~85% spent splitting fields!
- 16. Tune String fields[] =split(line, '|', 3,10,11); Sample timmings: real 0m13.450s user 0m13.425s sys 0m3.965s ETA: 44 minutes e 35 seconds 14 extra lines of java code and we’re back on track
- 17. Must get SIMcard data • SIM card Type (prepaid, postpaid, ...) • ~ 15 million record table • Database constantly under load • 4000 querys/s (0.25 ms/q) spare capacity
- 18. Database Tips (JDBC) –Reuse connections! – Read only ? setReadOnly(true) – Allways use PreparedStatements – Allways explicitly close ResultSet (GC friendly) – Turn off autocommit – Use batched operations and transactions in CRUD type accesses – Large ResultSets? Increase fetch size! rs.setFetchSize(XXX)
- 19. Ooops • Too slow! •Assuming an average rate of 4000 q/s: ETA: ~ 1 day, 56 minutes
- 20. Alternatives • TimesTen • SolidDb InMemory Databases • H2 • Hsqldb • Derby Emebeded Relational • BerkeyleyDb • Infinitydb Others Embebed
- 21. Must keep abalance Performance Cost, Complexity, Learning Curve (aka neuron Time), Maintenance
- 22. Remebering old times •In C/C++ you could map structs to memory • The amount of information needed is 16 bytes per SIM card (phone number, start date, end date, type of card – 4 * 4 bytes) • ~ 343 M if stored in a compact form (int[]) • Sort the data and wrap the array in a List • Use Collections.binarySearch to do the heavy lifting
- 23. Way faster! • Noextra libraries, 40 lines of simple java code ETA: 1 hour, 30 minutes e 35 seconds Above the budget
- 24. Put those extracores to work • 6 Quad Core 2.4ghz - 6 MB L2 Cache,Sparc VII CPUs, 48 hw threads, 32Gb RAM • Split the data in work units • Split the work units among the threads • Collect the results when the treads finish
- 25. Concurrent tips • Concurrentprogramming is really hard! • But you’re not going to be able to avoid it (cpu speed increases per core stalled, cores are increasing in number) • Don’t share R/W data among threads • Locking will kill performance • Be aware of memory architecture java.sun.com/javase/6/docs/technotes/guide s/concurrency/index.html
- 26. Mission Acomplished • With8 threads of the 48 possible Real running time: 10 minutes, 23 seconds Near linear scaling! There’s no point in optimizing more. We’ve just entered the Law of Diminishing returns en.wikipedia.org/wiki/Diminishing_returns
- 27. What about NetworkI/O • 1 thread per client using blocking I/O does not scale • Use Nonblocking I/O • VM implementors will (problaby) use the best API in the host OS (/dev/epoll in Linux Kernel 2.6 for example) • NBIO is hard. Don’t reinvent the wheel. See Apache Mina - mina.apache.org • Scales to over 10.000k connections easily!
- 28. A few extratips • Know your VM • Not all VMs are created equal • Even without changing a line of code you can improve things, if you know what you’re doing • If you’re using the SUN VM try the Server VM (default is Client VM) • Plenty of options to fiddle blogs.sun.com/watt/resource/jvm-options- list.html
- 29. What about designingand maintaining complex systems • Implement a feature complete solution in small scale • Learn the performance characteristics. Implement benchmarks. • Change the architecture if needed • How much does it cost? It’s all about €€€€€ (licensing, hardware, human resources, rack space, energy, cooling requirements, maintenance,...)
- 30. Keep measuaring afterthe system goes live “The only man I know who behaves sensibly is my tailor; he takes my measurements anew each time he sees me. The rest go on with their old measurements and expect me to fit them.” George Bernard Shaw - en.wikiquote.org/wiki/George_Bernard_Shaw • Specially if you keep adding features
- 31. Code snippets –A (way) faster split public static String[] split(String l, char sep, int... columns) { String[] fields = new String[columns.length]; int start = 0, column = 0, end, i = 0; while((end = l.indexOf(sep, start)) != -1) { if(column++ == columns[i]) { fields[i] = l.substring(start, end); if(++i == columns.length) return fields; } start = end + 1; } if(column == columns[i]) fields[i] = l.substring(start); return fields; } String fields[] = split(line, '|', 3,10,11);
- 32. Static in-memory “database”:Poor man’s solution (but as fast as it gets) public class ClientFile implements List<CardInfo>, RandomAccess { static final int CLIENT_SIZE = 16; int[] clients; public ClientFile() throws FileNotFoundException, IOException { File f = new File("clientes.db"); FileInputStream fs = new FileInputStream(f); int client_count = (int)f.length() / CLIENT_SIZE; clients = new int[client_count * 4]; byte b[] = new byte[(int) f.length()]; fs.read(b); for(int i = 0;i != client_count; ++i) { clients[i * 4] = toi(b, i * CLIENT_SIZE); clients[i * 4 + 1] = toi(b, i * CLIENT_SIZE + 4); clients[i * 4 + 2] = toi(b, i * CLIENT_SIZE + 8); clients[i * 4 + 3] = toi(b, i * CLIENT_SIZE + 12); } } // map byte[] to integer public int toi(byte[] b, int offset) { return ((0xFF & b[offset]) << 24) + ((0xFF & b[offset + 1]) << 16) + ((0xFF & b[offset + 2]) << 8) + (0xFF & b[offset + 3]); } (…)
- 33. Static in-memory “database”: (continued) (…) publicCardInfo get(int index) { return new CardInfo(clients[index * 4], clients[index * 4 + 1], clients[index * 4 + 2], clients[index * 4 + 3]); } public CardInfo getCardInfo(String msisdn, String yymmdd, String hhmmss){ Calendar cal = Calendar.getInstance(); cal.set(i(yymmdd, 0, 1) + 2000, i(yymmdd, 2, 3) - 1, i(yymmdd, 4, 5), i(hhmmss, 0, 1), i(hhmmss, 2, 3), i(hhmmss, 4, 5)); int idx = Collections.binarySearch(this, new Key(i(msisdn), (int)(cal.getTimeInMillis() / 1000))); if (idx < 0) { return null; } return get(idx); }
- 34. Questions? • Answers1 € •Answers that require thought5 € • Correct Answers20 € • Dumb looksFor Free!