Java Performance Tuning

Java Performance Tuning Atthakorn Chanthong

What is software tuning?

User Experience The software has poor response time. I need it runs more faster

Software tuning is to make application runs faster

Many people think Java application is slow, why?

There are two major reasons

The first is the Bottleneck

The Bottleneck Increased Memory Use Lots of Casts Automatic memory management by Garbage Collector All Object are allocated on the Heap. Java application is not native

The second is The Bad Coding Practice

How to make it run faster?

The bottleneck is unavoidable

But the man could have a good coding practice

A good design

A good coding practice

Java application normally run fast enough

So the tuning game comes into play

Knowing the strategy

Tuning Strategy 1 Identify the main causes 2 Choose the quickest and easier one to fix 3 Fix it, and repeat again for other root cause

Inside the strategy

Tuning Strategy Need more faster, repeat again Profile, Measure Problem Priority Yes, it’s better Identify the location of bottleneck Test and compare Still bad? Before/after alteration The result Think a hypothesis isn’t good enough Code alteration Create a test scenario

How to measure the software performance?

We use the profiler

Profiler is a programming tool that can track the performance of another computer program

The two common usages of profiler are to analyze a software problem Profiler Profile application Monitor application performance memory usage

How we get the profiler?

Don’t pay for it!

An opensource profiler is all around

Some interesting opensource profilers

Opensource Profiler JConsole http://java.sun.com/developer/technicalArticles/J2SE/jconsole.html

Opensource Profiler Eclipse TPTP http://www.eclipse.org/tptp/index.php

Opensource Profiler NetBeans Built-in Profiler http://profiler.netbeans.org/

Opensource Profiler This is pulled out from NetBeans to act as standalone profiler VisualVM https://visualvm.dev.java.net/

And much more …

Opensource Profiler JRat Cougaar DrMem InfraRED Profiler4j Jmeasurement TIJMP

We love opensource

Make the brain smart with good code practice

1st Rule Avoid Object-Creation

Object-Creation causes problem Why?

Avoid Object-Creation Lots of objects in memory means GC does lots of work Program is slow down when GC starts

Avoid Object-Creation Creating object costs time and CPU effort for application

Reuse objects where possible

Pool Management Most container (e.g. Vector) objects could be reused rather than created and thrown away

Pool Management VectorPoolManager V1 V3 V4 V5 getVector() returnVector() V2

Pool Management public void doSome() { for (int i=0; i < 10; i++) { Vector v = new Vector() … do vector manipulation stuff } } public static VectorPoolManager vpl = new VectorPoolManager(25) public void doSome() { for (int i=0; i < 10; i++) { Vector v = vectorPoolManager.getVector( ); … do vector manipulation stuff vectorPoolManager.returnVector(v); } }

Canonicalizing Objects Replace multiple object by a single object or just a few

Canonicalizing Objects public class VectorPoolManager { private static final VectorPoolManager poolManager; private Vector[] pool; private VectorPoolManager(int size) { .... } public static Vector getVector() { if (poolManager== null) poolManager = new VectorPoolManager(20); ... return pool[pool.length-1]; } } Singleton Pattern

Canonicalizing Objects Boolean b1 = new Boolean(true); Boolean b2 = new Boolean(false); Boolean b3 = new Boolean(false); Boolean b4 = new Boolean(false); 4 objects in memory Boolean b1 = Boolean.TRUE Boolean b2 = Boolean.FALSE Boolean b3 = Boolean.FALSE Boolean b4 = Boolean.FALSE 2 objects in memory

Canonicalizing Objects String string = quot;55quot;; Integer theInt = new Integer(string); No Cache String string = quot;55quot;; Integer theInt = Integer.valueOf(string); Object Cached

Canonicalizing Objects private static class IntegerCache { private IntegerCache(){} static final Integer cache[] = new Integer[-(-128) + 127 + 1]; static { for(int i = 0; i < cache.length; i++) cache[i] = new Integer(i - 128); } } public static Integer valueOf(int i) { final int offset = 128; if (i >= -128 && i <= 127) { // must cache return IntegerCache.cache[i + offset]; } return new Integer(i); } Caching inside Integer.valueOf(…)

Keyword, ‘final’ Use the final modifier on variable to create immutable internally accessible object

Keyword, ‘final’ public void doSome(Dimension width, Dimenstion height) { //Re-assign allow width = new Dimension(5,5); ... } public void doSome(final Dimension width, final Dimenstion height) { //Re-assign disallow width = new Dimension(5,5); ... }

Auto-Boxing/Unboxing Use Auto-Boxing as need not as always

Auto-Boxing/UnBoxing Integer i = 0; //Counting by 10M while (i < 100000000) { i++; } Takes 2313 ms Why it takes 2313/125 =~ 20 times longer? int p = 0; //Counting by 10M while (p < 100000000) { p++; } Takes 125 ms

Auto-Boxing/UnBoxing Object-Creation made every time we wrap primitive by boxing

2nd Rule Knowing String Better

String is the Object mostly used in the application

Overlook the String The software may have the poor performance

Compile-Time String Initialization Use the string concatenation (+) operator to create Strings at compile-time.

Compile-Time Initialization for (int i =0; i < loop; i++) { //Looping 10M rounds String x = quot;Helloquot; + quot;,quot; +quot; quot;+ quot;Worldquot;; } Takes 16 ms for (int i =0; i < loop; i++) { //Looping 10M rounds String x = new String(quot;Helloquot; + quot;,quot; +quot; quot;+ quot;Worldquot;); } Takes 672 ms

Runtime String Initialization Use StringBuffers/StringBuilder to create Strings at runtime.

Runtime String Initialization String name = quot;Smithquot;; for (int i =0; i < loop; i++) { //Looping 1M rounds String x = quot;Helloquot;; x += quot;,quot;; x += quot; Mr.quot;; x += name; } Takes 10298 ms String name = quot;Smithquot;; for (int i =0; i < loop; i++) { //Looping 1M rounds String x = (new StringBuffer()).append(quot;Helloquot;) .append(quot;,quot;).append(quot; quot;) .append(name).toString(); } Takes 6187 ms

String comparison Use appropriate method to compare the String

To Test String is Empty for (int i =0; i < loop; i++) { //10m loops if (a != null && a.equals(quot;quot;)) { } }. Takes 125 ms for (int i =0; i < loop; i++) { //10m loops if (a != null && a.length() == 0) { } } Takes 31 ms

If two strings have the same length String a = “abc” String b = “cdf” for (int i =0; i < loop; i++) { if (a.equalsIgnoreCase(b)) { } } Takes 750 ms String a = “abc” String b = “cdf” for (int i =0; i < loop; i++) { if (a.equals(b)) { } Takes 125 ms }

If two strings have different length String a = “abc” String b = “cdfg” for (int i =0; i < loop; i++) { if (a.equalsIgnoreCase(b)) { } } Takes 780 ms String a = “abc” String b = “cdfg” for (int i =0; i < loop; i++) { if (a.equals(b)) { } Takes 858 ms }

String.equalsIgnoreCase() does only 2 steps It checks for identity and then for Strings being the same size

Intern String To compare String by identity

Intern String Normally, string can be created by two ways

Intern String By new String(…) String s = new String(“This is a string literal.”); By String Literals String s = “This is a string literal.”;

Intern String Create Strings by new String(…) JVM always allocate a new memory address for each new String created even if they are the same.

Intern String String a = new String(“This is a string literal.”); String b = new String(“This is a string literal.”); a “This is a string literal.” The different memory address b “This is a string literal.”

Intern String Create Strings by Literals Strings will be stored in Pool Double create Strings by laterals They will share as a unique instances

Intern String String a = “This is a string literal.”; String b = “This is a string literal.”; a Same memory address “This is a string literal.” b

Intern String We can point two Stings variable to the same address if they are the same values. By using String.intern() method

Intern String String a = new String(“This is a string literal.”).intern(); String b = new String(“This is a string literal.”).intern(); a Same memory address “This is a string literal.” b

Intern String The idea is … Intern String could be used to compare String by identity

Intern String What “compare by identity” means?

Intern String If (a == b) Identity comparison (by reference) If (a.equals(b)) Value comparison

Intern String By using reference so identity comparison is fast

Intern String In traditionally style String must be compare by equals() to avoid the negative result

Intern String But Intern String… If Strings have different value they also have different address. If Strings have same value they also have the same address.

Intern String So we can say that (a == b) is equivalent to (a.equals(b))

Intern String For these string variables String a = quot;abcquot;; String b = quot;abcquot;; String c = new String(quot;abcquot;).intern() They are pointed to the same address with the same value

Intern String for (int i =0; i < loop; i++) { if (a.equals(b)) { } } Takes 312 ms for (int i =0; i < loop; i++) { if (a == b) { } Takes 32 ms }

Intern String Wow, Intern String is good Unfortunately, it makes code hard understand, use it carefully

Intern String String.intern() comes with overhead as there is a step to cache Use Intern String if they are planed to compare two or more times

char array instead of String Avoid doing some stuffs by String object itself for optimal performance

char array String x = quot;abcdefghijklmnquot;; for (int i =0; i < loop; i++) { if (x.charAt(5) == 'x') { } } Takes 281 ms String x = quot;abcdefghijklmnquot;; char y[] = x.toCharArray(); for (int i =0; i < loop; i++) { if ( (20 < y.length && 20 >= 0) && y[20] == 'x') { } } Takes 156 ms

3rd Rule Exception and Cast

Stop exception to be thrown if it is possible Exception is really expensively to execute

Avoid Exception Object obj = null; for (int i =0; i < loop; i++) { try { obj.hashCode(); } catch (Exception e) {} } Takes 18563 ms Object obj = null; for (int i =0; i < loop; i++) { if (obj != null) { obj.hashCode(); } Takes 16 ms }

Cast as Less We can reduce runtime cost by grouping cast object which is several used

Cast as Less Integer io = new Integer(0); Object obj = (Object)io; for (int i =0; i < loop; i++) { if (obj instanceof Integer) { byte x = ((Integer) obj).byteValue(); double d = ((Integer) obj).doubleValue(); float f = ((Integer) obj).floatValue(); } } Takes 31 ms for (int i =0; i < loop; i++) { if (obj instanceof Integer) { Integer icast = (Integer)obj; byte x = icast.byteValue(); double d = icast.doubleValue(); float f = icast.floatValue(); } } Takes 16 ms

4th Rule The Rhythm of Motion

Loop Optimization There are several ways to make a faster loop

Don’t terminate loop with method calls

Eliminate Method Call byte x[] = new byte[loop]; for (int i = 0; i < x.length; i++) { for (int j = 0; j < x.length; j++) { } } Takes 109 ms byte x[] = new byte[loop]; int length = x.length; for (int i = 0; i < length; i++) { for (int j = 0; j < length; j++) { } Takes 62 ms }

Method Call generates some overhead in Object Oriented Paradigm

Use int to iterate over loop

Iterate over loop by int for (int i = 0; i < length; i++) { for (int j = 0; j < length; j++) { } } Takes 62 ms for (short i = 0; i < length; i++) { for (short j = 0; j < length; j++) { } } Takes 125 ms

VM is optimized to use int for loop iteration not by byte, short, char

Use System.arraycopy(…) for copying object instead of running over loop

System.arraycopy(….) for (int i = 0; i < length; i++) { x[i] = y[i]; } Takes 62 ms System.arraycopy(x, 0, y, 0, x.length); Takes 16 ms

System.arraycopy() is native function It is efficiently to use

Terminate loop by primitive use not by function or variable

Terminate Loop by Primitive for(int i = 0; i < countArr.length; i++) { for(int j = 0; j < countArr.length; j++) { } } Takes 424 ms for(int i = countArr.length-1; i >= 0; i--) { for(int j = countArr.length-1; j >= 0; j--) { } } Takes 298 ms

Primitive comparison is more efficient than function or variable comparison

The average time of switch vs. if-else is about equally in random case

Switch vs. If-else for(int i = 0; i < loop; i++) for(int i = 0; i < loop; i++) { { if (i%10== 0) switch (i%10) { { case 0: break; } else if (i%10 == 1) case 1: break; { ... ... case 7: break; } else if (i%10 == 8) case 8: break; { default: break; } else if (i%10 == 9) } { } } } Takes 2623 ms Takes 2608 ms

Switch is quite fast if the case falls into the middle but slower than if-else in case of falling at the beginning or default case ** Test against a contiguous range of case values eg, 1,2,3,4,..

Recursive Algorithm Recursive function is easy to read but it costs for each recursion

Tail Recursion A recursive function for which each recursive call to itself is a reduction of the original call.

Recursive vs. Tail-Recursive public static long factorial1(int n) { if (n < 2) return 1L; else return n*factorial1(n-1); } Takes 172 ms public static long factorial1a(int n) { if (n < 2) return 1L; else return factorial1b(n, 1L); } public static long factorial1b(int n, long result) { if (n == 2) return 2L*result; else return factorial1b(n-1, result*n); Takes 125 ms }

Dynamic Cached Recursive Do cache to gain more speed

Dynamic-Cached Recursive public static long factorial1(int n) { if (n < 2) return 1L; else return n*factorial1(n-1); } Takes 172 ms public static final int CACHE_SIZE = 15; public static final long[ ] factorial3Cache = new long[CACHE_SIZE]; public static long factorial3(int n) { if (n < 2) return 1L; else if (n < CACHE_SIZE) { if (factorial3Cache[n] == 0) factorial3Cache[n] = n*factorial3(n-1); return factorial3Cache[n]; } else return n*factorial3(n-1); Takes 94 ms }

Recursion Summary Dynamic-Cached Tail Recursive is better than Tail Recursive is better than Recursive

5th Rule Use Appropriate Collection

Accession ArrayList vs. LinkedList

Random Access ArrayList al = new ArrayList(); for (int i =0; i < loop; i++) { al.get(i); } Takes 281 ms LinkedList ll = new LinkedList(); for (int i =0; i < loop; i++) { ll.get(i); } Takes 5828 ms

Sequential Access ArrayList al = new ArrayList(); for (Iterator i = al.iterator(); i.hasNext();) { i.next(); } Takes 1375 ms LinkedList ll = new LinkedList(); for (Iterator i = ll.iterator(); i.hasNext();) { i.next(); } Takes 1047 ms

ArrayList is good for random access LinkedList is good for sequential access

Random vs. Sequential Access ArrayList al = new ArrayList(); for (int i =0; i < loop; i++) { al.get(i); } Takes 281 ms LinkedList ll = new LinkedList(); for (Iterator i = ll.iterator(); i.hasNext();) { i.next(); } Takes 1047 ms

Random Access is better than Sequential Access

Insertion ArrayList vs. LinkedList

Insertion at zero index ArrayList al = new ArrayList(); for (int i =0; i < loop; i++) { al.add(0, Integer.valueOf(i)); } Takes 328 ms LinkedList ll = new LinkedList(); for (int i =0; i < loop; i++) { ll.add(0, Integer.valueOf(i)); } Takes 109 ms

LinkedList does insertion better than ArrayList

Vector is likely to ArrayList but it is synchronized version

Accession and Insertion Vector vs. ArrayList

Random Accession ArrayList al = new ArrayList(); for (int i =0; i < loop; i++) { al.get(i); } Takes 281 ms Vector vt = new Vector(); for (int i =0; i < loop; i++) { vt.get(i); } Takes 422 ms

Sequential Accession ArrayList al = new ArrayList(); for (Iterator i = al.iterator(); i.hasNext();) { i.next(); } Takes 1375 ms Vector vt = new Vector(); for (Iterator i = vt.iterator(); i.hasNext();) { i.next(); } Takes 1890 ms

Insertion ArrayList al = new ArrayList(); for (int i =1; i < loop; i++) { al.add(0, Integer.valueOf(i)); } Takes 328 ms Vector vt = new Vector(); for (int i =0; i < loop; i++) { vt.add(0, Integer.valueOf(i)); } Takes 360 ms

Vector is slower than ArrayList in every method Use Vector if only synchronize needed

Summary Type Random Sequential Insertion (get) (Iterator) ArrayList 281 1375 328 LinkedList 5828 1047 109 Vector 422 1890 360

Addition and Accession Hashtable vs HashMap

Addition Hashtable ht = new Hashtable(); for (int i =0; i < loop; i++) { ht.put(Integer.valueOf(i), Integer.valueOf(i)); } Takes 453 ms HashMap hm = new HashMap(); for (int i =0; i < loop; i++) { hm.put(Integer.valueOf(i), Integer.valueOf(i)); } Takes 328 ms

Accession Hashtable ht = new Hashtable(); for (int i =0; i < loop; i++) { ht.get(Integer.valueOf(i)); } Takes 94 ms HashMap hm = new HashMap(); for (int i =0; i < loop; i++) { hm.get(Integer.valueOf(i)); } Takes 47 ms

Hashtable is synchronized so it is slower than HashMap

Reference O'Reilly Java Performance Tuning 2nd http://www.javaperformancetuning.com http://www.glenmccl.com/jperf/

Future Topic I/O Logging, and Console Output Sorting Threading Tweak JVM and GC Strategy

The End

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Java Performance Tuning

by Atthakorn Chanthong on Oct 14, 2008

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