按多个数字对Java字符串数组进行排序

Question

我有这样的txt文件中的数据列表

Date,Lat,Lon,Depth,Mag

20000101,34.6920,-116.3550,12.30,1.21
20000101,34.4420,-116.2280,7.32,1.01
20000101,37.4172,-121.7667,5.88,1.14
20000101,-41.1300,174.7600,27.00,1.90
20000101,37.6392,-119.0482,2.40,1.03
20000101,32.1790,-115.0730,6.00,2.44
20000101,59.7753,-152.2192,86.34,1.48
20000101,34.5230,-116.2410,11.63,1.61
20000101,59.5369,-153.1360,100.15,1.62
20000101,44.7357,-110.7932,4.96,2.20
20000101,34.6320,-116.2950,9.00,1.73
20000101,44.7370,-110.7938,5.32,1.75
20000101,35.7040,-117.6320,4.15,1.45
20000101,41.9270,20.5430,10.00,4.80

我的任务是按照每个标准对这些数据进行排序，例如）按日期，纬度和经度排序

我尝试像这样的泡沫排序

if ( Double.parseDouble(a[0].split(",")[1]) <  Double.parseDouble(a[1].split(",")[1]))

这可行，但是需要太多时间

那里有40000在txt文件数据

有没有其他方法可以对这些数据进行排序？

Answer 1

我可能会破坏一些学生的家庭作业，但是这里…

正如课题所建议的那样，Java的自然方法是创建一个表示您的数据的类。然后实现一个Comparator将传递给实用方法的方法Collections.sort。

在运行带有Java 8的Parallels虚拟机的MacBook Pro 2.3 GHz Intel Core
i7上，42,000个元素的数据集需要45-90毫秒的时间才能排序。

我更改了示例数据，使其更加有趣，引入了一些不同的日期和重复的纬度。

20000101,34.6920,-116.3550,12.30,1.21
20000101,34.4420,-116.2280,7.32,1.01
20000101,34.6920,-121.7667,5.88,1.14
20000101,-41.1300,174.7600,27.00,1.90
20000101,37.6392,-119.0482,2.40,1.03
20000101,32.1790,-115.0730,6.00,2.44
20000101,34.6920,-152.2192,86.34,1.48
20000102,34.6320,-116.2410,11.63,1.61
20000102,59.5369,-153.1360,100.15,1.62
20000102,44.7357,-110.7932,4.96,2.20
20000102,34.6320,-116.2950,9.00,1.73
20000102,34.6320,-110.7938,5.32,1.75
20000102,34.6320,-117.6320,4.15,1.45
20000102,41.9270,20.5430,10.00,4.80

我的GeoReading班代表数据。

class GeoReading
{

    LocalDate localDate = null;
    BigDecimal latitude = null;
    BigDecimal longitude = null;
    BigDecimal depth = null;
    BigDecimal magnitude = null;

    public GeoReading( String arg )
    {
        // String is comma-separated values of: Date,Lat,Lon,Depth,Mag
        List<String> items = Arrays.asList( arg.split( "\\s*,\\s*" ) ); // Regex explained here: http://stackoverflow.com/a/7488676/642706
        this.localDate = ISODateTimeFormat.basicDate().parseLocalDate( items.get( 0 ) );
        this.latitude = new BigDecimal( items.get( 1 ) );
        this.longitude = new BigDecimal( items.get( 2 ) );
        this.depth = new BigDecimal( items.get( 3 ) );
        this.magnitude = new BigDecimal( items.get( 4 ) );
    }

    @Override
    public String toString()
    {
        return "GeoReading{" + "localDate=" + localDate + ", latitude=" + latitude + ", longitude=" + longitude + ", depth=" + depth + ", magnitude=" + magnitude + '}';
    }

}

这是比较器的实现。

class GeoReadingAscendingComparator implements Comparator<GeoReading>
{

    @Override
    public int compare( GeoReading o1 , GeoReading o2 )
    {
        int localDateCompare = o1.localDate.compareTo( o2.localDate );
        if ( localDateCompare != 0 ) { // If not equal on this component, so compare on this.
            return localDateCompare;
        }

        int latitudeCompare = o1.latitude.compareTo( o2.latitude );
        if ( latitudeCompare != 0 ) { // If not equal on this component, so compare on this.
            return latitudeCompare;
        }

        return o1.longitude.compareTo( o2.longitude );

    }
}

主要代码。

Path path = Paths.get( "/Users/basil/lat-lon.txt" );  // Path for Mac OS X.
try {
    List<GeoReading> list = new ArrayList<>();
    Stream<String> lines = Files.lines( path );
    lines.forEach( line -> list.add( new GeoReading( line ) ) );
    // Take those 14 lines and multiply to simulate large text file. 14 * 3,000 = 42,000.
    int count = 3000;
    List<GeoReading> bigList = new ArrayList<>( list.size() * count ); // Initialze capacite to expected number of elements.
    for ( int i = 0 ; i < count ; i++ ) {
        bigList.addAll( list );
    }
    long start = System.nanoTime();
    Collections.sort( bigList , new GeoReadingAscendingComparator() );
    long elapsed = ( System.nanoTime() - start );
    System.out.println( "Done sorting the GeoReading list. Sorting " + bigList.size() + " took: " + TimeUnit.MILLISECONDS.convert( elapsed , TimeUnit.NANOSECONDS ) + " ms ( " + elapsed + " nanos )." );

    System.out.println( "Dump…" );
    for ( GeoReading g : bigList ) {
        System.out.println( g );
    }
} catch ( IOException ex ) {
    System.out.println( "ERROR - ex: " + ex );
}

在现实世界中，我将添加一些防御性编程代码来验证传入的数据。来自外部来源的数据 始终 是有缺陷的和/或不断变化的。