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

Q&A

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