在 java 中，使用 byte 或 short 代替 int 和 float 代替 double 更有效吗？

我注意到我总是使用 int 和 double，不管数值需要多小或多大。那么在 java 中，使用 byte或者 short而不是 int和 float而不是 double是否更有效呢？

假设我有一个包含大量 int 和 double 的程序。如果我知道这个数字是合适的，那么是否值得查看并将 int 改为 byte 或 short？

我知道 java 没有无符号类型，但是如果我知道这个数字只是正数，我还能做些什么呢？

我所说的高效主要是指处理。我假设如果所有变量的大小都减半，那么垃圾收集器会快得多，而且计算可能也会快一些。 (我想既然我在 Android 上工作，我也需要担心一下内存)

(我假设垃圾收集器只处理 Object，而不是原语，但是仍然会删除废弃对象中的所有原语，对吗?)

我用一个小的 Android 应用程序尝试了一下，但是没有发现有什么不同。(尽管我没有“科学地”测量任何东西。)

我认为它应该更快、更有效率，这种想法是错误的吗？我可不想在一个庞大的程序里改变一切结果发现我浪费了时间。

当我开始一个新项目的时候，从头开始值得吗？(我的意思是，我认为每一点都会有所帮助，但如果是这样，为什么似乎没有人这样做。)

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The difference is hardly noticeable! It's more a question of design, appropriateness, uniformity, habit, etc... Sometimes it's just a matter of taste. When all you care about is that your program gets up and running and substituting a float for an int would not harm correctness, I see no advantage in going for one or another unless you can demonstrate that using either type alters performance. Tuning performance based on types that are different in 2 or 3 bytes is really the last thing you should care about; Donald Knuth once said: "Premature optimization is the root of all evil" (not sure it was him, edit if you have the answer).

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最佳答案

Am I wrong in assuming it should be faster and more efficient? I'd hate to go through and change everything in a massive program to find out I wasted my time.

Short answer

Yes, you are wrong. In most cases, it makes little difference in terms of space used.

It is not worth trying to optimize this ... unless you have clear evidence that optimization is needed. And if you do need to optimize memory usage of object fields in particular, you will probably need to take other (more effective) measures.

Longer answer

The Java Virtual Machine models stacks and object fields using offsets that are (in effect) multiples of a 32 bit primitive cell size. So when you declare a local variable or object field as (say) a byte, the variable / field will be stored in a 32 bit cell, just like an int.

There are two exceptions to this:

  • long and double values require 2 primitive 32-bit cells
  • arrays of primitive types are represent in packed form, so that (for example) an array of bytes hold 4 bytes per 32bit word.

So it might be worth optimizing use of long and double ... and large arrays of primitives. But in general no.

In theory, a JIT might be able to optimize this, but in practice I've never heard of a JIT that does. One impediment is that the JIT typically cannot run until after there instances of the class being compiled have been created. If the JIT optimized the memory layout, you could have two (or more) "flavors" of object of the same class ... and that would present huge difficulties.

Revisitation

Looking at the benchmark results in @meriton's answer, it appears that using short and byte instead of int incurs a performance penalty for multiplication. Indeed, if you consider the operations in isolation, the penalty is significant. (You shouldn't consider them in isolation ... but that's another topic.)

I think the explanation is that JIT is probably doing the multiplications using 32bit multiply instructions in each case. But in the byte and short case, it executes extra instructions to convert the intermediate 32 bit value to a byte or short in each loop iteration. (In theory, that conversion could be done once at the end of the loop ... but I doubt that the optimizer would be able to figure that out.)

Anyway, this does point to another problem with switching to short and byte as an optimization. It could make performance worse ... in an algorithm that is arithmetic and compute intensive.

Secondary questions

I know java doesn't have unsigned types but is there anything extra I could do if I knew the number would be positive only?

No. Not in terms of performance anyway. (There are some methods in Integer, Long, etc for dealing with int, long, etc as unsigned. But these don't give any performance advantage. That is not their purpose.)

(I'd assume the garbage collector only deals with Objects and not primitive but still deletes all the primitives in abandoned objects right? )

Correct. A field of an object is part of the object. It goes away when the object is garbage collected. Likewise the cells of an array go away when the array is collected. When the field or cell type is a primitive type, then the value is stored in the field / cell ... which is part of the object / array ... and that has been deleted.

小开

byte is generally considered to be 8 bits. short is generally considered to be 16 bits.

In a "pure" environment, which isn't java as all implementation of bytes and longs, and shorts, and other fun things is generally hidden from you, byte makes better use of space.

However, your computer is probably not 8 bit, and it is probably not 16 bit. this means that to obtain 16 or 8 bits in particular, it would need to resort to "trickery" which wastes time in order to pretend that it has the ability to access those types when needed.

At this point, it depends on how hardware is implemented. However from I've been tought, the best speed is achieved from storing things in chunks which are comfortable for your CPU to use. A 64 bit processor likes dealing with 64 bit elements, and anything less than that often requires "engineering magic" to pretend that it likes dealing with them.

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That depends on the implementation of the JVM, as well as the underlying hardware. Most modern hardware will not fetch single bytes from memory (or even from the first level cache), i.e. using the smaller primitive types generally does not reduce memory bandwidth consumption. Likewise, modern CPU have a word size of 64 bits. They can perform operations on less bits, but that works by discarding the extra bits, which isn't faster either.

The only benefit is that smaller primitive types can result in a more compact memory layout, most notably when using arrays. This saves memory, which can improve locality of reference (thus reducing the number of cache misses) and reduce garbage collection overhead.

Generally speaking however, using the smaller primitive types is not faster.

To demonstrate that, behold the following benchmark:

public class Benchmark {


public static void benchmark(String label, Code code) {
print(25, label);
        

try {
for (int iterations = 1; ; iterations *= 2) { // detect reasonable iteration count and warm up the code under test
System.gc(); // clean up previous runs, so we don't benchmark their cleanup
long previouslyUsedMemory = usedMemory();
long start = System.nanoTime();
code.execute(iterations);
long duration = System.nanoTime() - start;
long memoryUsed = usedMemory() - previouslyUsedMemory;
                

if (iterations > 1E8 || duration > 1E9) {
print(25, new BigDecimal(duration * 1000 / iterations).movePointLeft(3) + " ns / iteration");
print(30, new BigDecimal(memoryUsed * 1000 / iterations).movePointLeft(3) + " bytes / iteration\n");
return;
}
}
} catch (Throwable e) {
throw new RuntimeException(e);
}
}
    

private static void print(int desiredLength, String message) {
System.out.print(" ".repeat(Math.max(1, desiredLength - message.length())) + message);
}
    

private static long usedMemory() {
return Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
}


@FunctionalInterface
interface Code {
/**
* Executes the code under test.
*
* @param iterations
*            number of iterations to perform
* @return any value that requires the entire code to be executed (to
*         prevent dead code elimination by the just in time compiler)
* @throws Throwable
*             if the test could not complete successfully
*/
Object execute(int iterations);
}


public static void main(String[] args) {
benchmark("long[] traversal", (iterations) -> {
long[] array = new long[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = i;
}
return array;
});
benchmark("int[] traversal", (iterations) -> {
int[] array = new int[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = i;
}
return array;
});
benchmark("short[] traversal", (iterations) -> {
short[] array = new short[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = (short) i;
}
return array;
});
benchmark("byte[] traversal", (iterations) -> {
byte[] array = new byte[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = (byte) i;
}
return array;
});
        

benchmark("long fields", (iterations) -> {
class C {
long a = 1;
long b = 2;
}
            

C[] array = new C[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = new C();
}
return array;
});
benchmark("int fields", (iterations) -> {
class C {
int a = 1;
int b = 2;
}
            

C[] array = new C[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = new C();
}
return array;
});
benchmark("short fields", (iterations) -> {
class C {
short a = 1;
short b = 2;
}
            

C[] array = new C[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = new C();
}
return array;
});
benchmark("byte fields", (iterations) -> {
class C {
byte a = 1;
byte b = 2;
}
            

C[] array = new C[iterations];
for (int i = 0; i < iterations; i++) {
array[i] = new C();
}
return array;
});


benchmark("long multiplication", (iterations) -> {
long result = 1;
for (int i = 0; i < iterations; i++) {
result *= 3;
}
return result;
});
benchmark("int multiplication", (iterations) -> {
int result = 1;
for (int i = 0; i < iterations; i++) {
result *= 3;
}
return result;
});
benchmark("short multiplication", (iterations) -> {
short result = 1;
for (int i = 0; i < iterations; i++) {
result *= 3;
}
return result;
});
benchmark("byte multiplication", (iterations) -> {
byte result = 1;
for (int i = 0; i < iterations; i++) {
result *= 3;
}
return result;
});
}
}

Run with OpenJDK 14 on my Intel Core i7 CPU @ 3.5 GHz, this prints:

     long[] traversal     3.206 ns / iteration      8.007 bytes / iteration
int[] traversal     1.557 ns / iteration      4.007 bytes / iteration
short[] traversal     0.881 ns / iteration      2.007 bytes / iteration
byte[] traversal     0.584 ns / iteration      1.007 bytes / iteration
long fields    25.485 ns / iteration     36.359 bytes / iteration
int fields    23.126 ns / iteration     28.304 bytes / iteration
short fields    21.717 ns / iteration     20.296 bytes / iteration
byte fields    21.767 ns / iteration     20.273 bytes / iteration
long multiplication     0.538 ns / iteration      0.000 bytes / iteration
int multiplication     0.526 ns / iteration      0.000 bytes / iteration
short multiplication     0.786 ns / iteration      0.000 bytes / iteration
byte multiplication     0.784 ns / iteration      0.000 bytes / iteration

As you can see, the only significant speed savings occur when traversing large arrays; using smaller object fields yields negligible benefit, and computations are actually slightly slower on the small datatypes.

Overall, the performance differences are quite minor. Optimizing algorithms is far more important than the choice of primitive type.

小开

Using byte instead of int can increase performance if you are using them in a huge amount. Here is an experiment:

import java.lang.management.*;


public class SpeedTest {


/** Get CPU time in nanoseconds. */
public static long getCpuTime() {
ThreadMXBean bean = ManagementFactory.getThreadMXBean();
return bean.isCurrentThreadCpuTimeSupported() ? bean
.getCurrentThreadCpuTime() : 0L;
}


public static void main(String[] args) {
long durationTotal = 0;
int numberOfTests=0;


for (int j = 1; j < 51; j++) {
long beforeTask = getCpuTime();
// MEASURES THIS AREA------------------------------------------
long x = 20000000;// 20 millions
for (long i = 0; i < x; i++) {
TestClass s = new TestClass();
                

}
// MEASURES THIS AREA------------------------------------------
long duration = getCpuTime() - beforeTask;
System.out.println("TEST " + j + ": duration = " + duration + "ns = "
+ (int) duration / 1000000);
durationTotal += duration;
numberOfTests++;
}
double average = durationTotal/numberOfTests;
System.out.println("-----------------------------------");
System.out.println("Average Duration = " + average + " ns = "
+ (int)average / 1000000 +" ms (Approximately)");
        

}
}

This class tests the speed of creating a new TestClass. Each tests does it 20 million times and there are 50 tests.

Here is the TestClass:

 public class TestClass {
int a1= 5;
int a2= 5;
int a3= 5;
int a4= 5;
int a5= 5;
int a6= 5;
int a7= 5;
int a8= 5;
int a9= 5;
int a10= 5;
int a11= 5;
int a12=5;
int a13= 5;
int a14= 5;
}

I've run the SpeedTest class and in the end got this:

 Average Duration = 8.9625E8 ns = 896 ms (Approximately)

Now I'm changing the ints into bytes in the TestClass and running it again. Here is the result:

 Average Duration = 6.94375E8 ns = 694 ms (Approximately)

I believe this experiment shows that if you are instancing a huge amount of variables, using byte instead of int can increase efficiency

小开

One of the reason for short/byte/char being less performant is for lack of direct support for these data types. By direct support, it means, JVM specifications do not mention any instruction set for these data types. Instructions like store, load, add etc. have versions for int data type. But they do not have versions for short/byte/char. E.g. consider below java code:

void spin() {
int i;
for (i = 0; i < 100; i++) {
; // Loop body is empty
}
}

Same gets converted into machine code as below.

0 iconst_0 // Push int constant 0
1 istore_1 // Store into local variable 1 (i=0)
2 goto 8 // First time through don't increment
5 iinc 1 1 // Increment local variable 1 by 1 (i++)
8 iload_1 // Push local variable 1 (i)
9 bipush 100 // Push int constant 100
11 if_icmplt 5 // Compare and loop if less than (i < 100)
14 return // Return void when done

Now, consider changing int to short as below.

void sspin() {
short i;
for (i = 0; i < 100; i++) {
; // Loop body is empty
}
}

The corresponding machine code will change as follows:

0 iconst_0
1 istore_1
2 goto 10
5 iload_1 // The short is treated as though an int
6 iconst_1
7 iadd
8 i2s // Truncate int to short
9 istore_1
10 iload_1
11 bipush 100
13 if_icmplt 5
16 return

As you can observe, to manipulate short data type, it is still using int data type instruction version and explicitly converting int to short when required. Now, due to this, performance gets reduced.

Now, reason cited for not giving direct support as follows:

The Java Virtual Machine provides the most direct support for data of type int. This is partly in anticipation of efficient implementations of the Java Virtual Machine's operand stacks and local variable arrays. It is also motivated by the frequency of int data in typical programs. Other integral types have less direct support. There are no byte, char, or short versions of the store, load, or add instructions, for instance.

Quoted from JVM specification present here (Page 58).

小开

I would say that accepted answer is somewhat wrong saying "it makes little difference in terms of space used". Here is the example showing that difference in some cases is very different:

Baseline usage 4.90MB, java: 11.0.12
Mem usage - bytes : +202.60 MB
Mem usage - shorts: +283.02 MB
Mem usage - ints  : +363.02 MB
Mem usage - bytes : +203.02 MB
Mem usage - shorts: +283.02 MB
Mem usage - ints  : +363.02 MB
Mem usage - bytes : +203.02 MB
Mem usage - shorts: +283.02 MB
Mem usage - ints  : +363.02 MB

The code to verify:

static class Bytes {
public byte f1;
public byte f2;
public byte f3;
public byte f4;
}


static class Shorts {
public short f1;
public short f2;
public short f3;
public short f4;
}


static class Ints {
public int f1;
public int f2;
public int f3;
public int f4;
}


@Test
public void memUsageTest() throws Exception {
int countOfItems = 10 * 1024 * 1024;
float MB = 1024*1024;
Runtime rt = Runtime.getRuntime();


System.gc();
Thread.sleep(1000);
long baseLineUsage = rt.totalMemory() - rt.freeMemory();


trace("Baseline usage %.2fMB, java: %s", (baseLineUsage / MB), System.getProperty("java.version"));


for( int j = 0; j < 3; j++ ) {
Bytes[] bytes = new Bytes[countOfItems];
for( int i = 0; i < bytes.length; i++ ) {
bytes[i] = new Bytes();
}
System.gc();
Thread.sleep(1000);
trace("Mem usage - bytes : +%.2f MB", (rt.totalMemory() - rt.freeMemory() - baseLineUsage) / MB);
bytes = null;


Shorts[] shorts = new Shorts[countOfItems];
for( int i = 0; i < shorts.length; i++ ) {
shorts[i] = new Shorts();
}
System.gc();
Thread.sleep(1000);
trace("Mem usage - shorts: +%.2f MB", (rt.totalMemory() - rt.freeMemory() - baseLineUsage) / MB);
shorts = null;


Ints[] ints = new Ints[countOfItems];
for( int i = 0; i < ints.length; i++ ) {
ints[i] = new Ints();
}
System.gc();
Thread.sleep(1000);
trace("Mem usage - ints  : +%.2f MB", (rt.totalMemory() - rt.freeMemory() - baseLineUsage) / MB);
ints = null;
}
}


private static void trace(String message, Object... args) {
String line = String.format(US, message, args);
System.out.println(line);
}

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