[Java] Type conversion speed comparison

Everyone also saw the code ``` double hoge = 1;`` and said, "Is it okay if I don't set"double hoge = 1.0d;` ``? "" Does the execution speed slow down? " I think you may have been worried. So I actually measured it.

result

The unit is nanoseconds, but the speed varies depending on the environment, so it is just a guide. Think of it as ** relatively ** faster ** as the number is ** smaller. Bold is the conversion to the same type.

Impressions

After all it seems that it is basically faster to align the molds. However, there are some combinations where type conversion is faster, so it may be considered as a category of error.

double hoge = 1;And double hoge= 1.0d;As for, I found that it didn't change much, so I can finally sleep with my pillow raised from today.

### Caution
 Based on this result ** Please do not try to speed up the program carelessly **.
 Readability and algorithm speedup are more important than forcibly changing the program and making slight speedups such as errors.

# Execution content
 The processing content actually entered is as follows.

static int    srcI = 1;
static long   srcL = 1l;
static float  srcF = 1.0f;
static double srcD = 1.0d;
static int    dstI;
static long   dstL;
static float  dstF;
static double dstD;

    TimeMeasure.Sample sampleI[] = {
        //Substitute as it is
        ()->{ dstI = srcI; }

// , ()->{ dstI = srcL; } //Impossible // , ()->{ dstI = srcF; } //Impossible // , ()->{ dstI = srcD; } //Impossible //Cast and assign , ()->{ dstI = (int)srcI; } , ()->{ dstI = (int)srcL; } , ()->{ dstI = (int)srcF; } , ()->{ dstI = (int)srcD; } //Substitute a number , ()->{ dstI = 1 ; } // , ()->{ dstI = 1l ; } //Impossible // , ()->{ dstI = 1.0f; } //Impossible // , ()->{ dstI = 1.0d; } //Impossible };

    TimeMeasure.Sample sampleL[] = {
        //Substitute as it is
        ()->{ dstL = srcI; }
    ,   ()->{ dstL = srcL; }

// , ()->{ dstL = srcF; } //Impossible // , ()->{ dstL = srcD; } //Impossible //Cast and assign , ()->{ dstL = (long)srcI; } , ()->{ dstL = (long)srcL; } , ()->{ dstL = (long)srcF; } , ()->{ dstL = (long)srcD; } //Substitute a number , ()->{ dstL = 1 ; } , ()->{ dstL = 1l ; } // , ()->{ dstL = 1.0f; } //Impossible // , ()->{ dstL = 1.0d; } //Impossible };

    TimeMeasure.Sample sampleF[] = {
        //Substitute as it is
        ()->{ dstF = srcI; }
    ,   ()->{ dstF = srcL; }
    ,   ()->{ dstF = srcF; }

// , ()->{ dstF = srcD; } //Impossible //Cast and assign , ()->{ dstF = (float)srcI; } , ()->{ dstF = (float)srcL; } , ()->{ dstF = (float)srcF; } , ()->{ dstF = (float)srcD; } //Substitute a number , ()->{ dstF = 1 ; } , ()->{ dstF = 1l ; } , ()->{ dstF = 1.0f; } // , ()->{ dstF = 1.0d; } //Impossible };

    TimeMeasure.Sample sampleD[] = {
        //Substitute as it is
        ()->{ dstD = srcI; }
    ,   ()->{ dstD = srcL; }
    ,   ()->{ dstD = srcF; }
    ,   ()->{ dstD = srcD; }
        //Cast and assign
    ,   ()->{ dstD = (double)srcI; }
    ,   ()->{ dstD = (double)srcL; }
    ,   ()->{ dstD = (double)srcF; }
    ,   ()->{ dstD = (double)srcD; }
        //Substitute a number
    ,   ()->{ dstD = 1   ; }
    ,   ()->{ dstD = 1l  ; }
    ,   ()->{ dstD = 1.0f; }
    ,   ()->{ dstD = 1.0d; }
    };

### Calculation method
 1. Execute the process to be measured 1 million times and find the average execution time for each time.
 2. Execute 1 100 times and calculate the average value of the results.

 * The program for the calculation part is undecided because it is built into the homemade library. If you are distrustful of the result, try measuring it yourself.

<details>
 <summary> Raw execution result </ summary>
<div>

Substitution to int sample( 1 / 6 ) set times : 1000000 x 100 set avelage : 19.416518 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 2 / 6 ) set times : 1000000 x 100 set avelage : 19.949821 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 3 / 6 ) set times : 1000000 x 100 set avelage : 20.694315 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 4 / 6 ) set times : 1000000 x 100 set avelage : 21.191030 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 5 / 6 ) set times : 1000000 x 100 set avelage : 20.969548 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 6 / 6 ) set times : 1000000 x 100 set avelage : 20.723962 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| Substitution to long sample( 1 / 8 ) set times : 1000000 x 100 set avelage : 20.926685 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 2 / 8 ) set times : 1000000 x 100 set avelage : 20.923104 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 3 / 8 ) set times : 1000000 x 100 set avelage : 20.933459 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 4 / 8 ) set times : 1000000 x 100 set avelage : 21.099284 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 5 / 8 ) set times : 1000000 x 100 set avelage : 21.107446 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 6 / 8 ) set times : 1000000 x 100 set avelage : 21.144695 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 7 / 8 ) set times : 1000000 x 100 set avelage : 20.855954 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 8 / 8 ) set times : 1000000 x 100 set avelage : 20.842132 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| Assignment to float sample( 1 / 10 ) set times : 1000000 x 100 set avelage : 20.799797 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 2 / 10 ) set times : 1000000 x 100 set avelage : 20.841888 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 3 / 10 ) set times : 1000000 x 100 set avelage : 21.097959 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 4 / 10 ) set times : 1000000 x 100 set avelage : 20.814193 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 5 / 10 ) set times : 1000000 x 100 set avelage : 20.959374 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 6 / 10 ) set times : 1000000 x 100 set avelage : 20.883601 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 7 / 10 ) set times : 1000000 x 100 set avelage : 20.948977 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 8 / 10 ) set times : 1000000 x 100 set avelage : 20.824086 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 9 / 10 ) set times : 1000000 x 100 set avelage : 20.750565 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 10 / 10 ) set times : 1000000 x 100 set avelage : 20.721974 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| Substitution to double sample( 1 / 12 ) set times : 1000000 x 100 set avelage : 20.958085 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 2 / 12 ) set times : 1000000 x 100 set avelage : 20.943837 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 3 / 12 ) set times : 1000000 x 100 set avelage : 20.839026 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 4 / 12 ) set times : 1000000 x 100 set avelage : 20.972230 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 5 / 12 ) set times : 1000000 x 100 set avelage : 20.951048 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 6 / 12 ) set times : 1000000 x 100 set avelage : 20.900803 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 7 / 12 ) set times : 1000000 x 100 set avelage : 21.196955 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 8 / 12 ) set times : 1000000 x 100 set avelage : 20.954024 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 9 / 12 ) set times : 1000000 x 100 set avelage : 21.002265 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 10 / 12 ) set times : 1000000 x 100 set avelage : 20.991709 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 11 / 12 ) set times : 1000000 x 100 set avelage : 21.072246 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=| sample( 12 / 12 ) set times : 1000000 x 100 set avelage : 20.941363 ns |=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|=|

</div></details>

### environment
Java : 1.8.0_31
OS : Windows 10 64bit
RAM : 32.0GB
CPU : Intel Core i7-4790K 4.00GHz