以防你像我一样懒，这里有一个解决方案，由这个和其他关于SO的答案合并而成。

set @orig_lat=37.46; 
set @orig_long=-122.25; 
set @bounding_distance=1;

SELECT
*
,((ACOS(SIN(@orig_lat * PI() / 180) * SIN(`lat` * PI() / 180) + COS(@orig_lat * PI() / 180) * COS(`lat` * PI() / 180) * COS((@orig_long - `long`) * PI() / 180)) * 180 / PI()) * 60 * 1.1515) AS `distance` 
FROM `cities` 
WHERE
(
  `lat` BETWEEN (@orig_lat - @bounding_distance) AND (@orig_lat + @bounding_distance)
  AND `long` BETWEEN (@orig_long - @bounding_distance) AND (@orig_long + @bounding_distance)
)
ORDER BY `distance` ASC
limit 25;

这个问题一点也不难，但是如果你需要优化它，它就会变得更加复杂。

我的意思是，你的数据库中有100个地点还是1亿个?这有很大的不同。

如果位置的数量很小，只需执行->，就可以将它们从SQL中取出并放入代码中

Select * from Location

一旦你把它们转换成代码，用哈弗辛公式计算出每一个纬度/长度与原始值之间的距离，然后排序。

SELECT latitude, longitude, SQRT(
    POW(69.1 * (latitude - [startlat]), 2) +
    POW(69.1 * ([startlng] - longitude) * COS(latitude / 57.3), 2)) AS distance
FROM TableName HAVING distance < 25 ORDER BY distance;

其中[starlat]和[startlng]是开始测量距离的位置。

simpledb.execSQL("CREATE TABLE IF NOT EXISTS " + tablename + "(id INTEGER PRIMARY KEY   AUTOINCREMENT,lat double,lng double,address varchar)");
            simpledb.execSQL("insert into '" + tablename + "'(lat,lng,address)values('22.2891001','70.780154','craftbox');");
            simpledb.execSQL("insert into '" + tablename + "'(lat,lng,address)values('22.2901396','70.7782428','kotecha');");//22.2904718 //70.7783906
            simpledb.execSQL("insert into '" + tablename + "'(lat,lng,address)values('22.2863155','70.772108','kkv Hall');");
            simpledb.execSQL("insert into '" + tablename + "'(lat,lng,address)values('22.275993','70.778076','nana mava');");
            simpledb.execSQL("insert into '" + tablename + "'(lat,lng,address)values('22.2667148','70.7609386','Govani boys hostal');");


    double curentlat=22.2667258;  //22.2677258
    double curentlong=70.76096826;//70.76096826

    double curentlat1=curentlat+0.0010000;
    double curentlat2=curentlat-0.0010000;

    double curentlong1=curentlong+0.0010000;
    double curentlong2=curentlong-0.0010000;

    try{

        Cursor c=simpledb.rawQuery("select * from '"+tablename+"' where (lat BETWEEN '"+curentlat2+"' and '"+curentlat1+"') or (lng BETWEEN         '"+curentlong2+"' and '"+curentlong1+"')",null);

        Log.d("SQL ", c.toString());
        if(c.getCount()>0)
        {
            while (c.moveToNext())
            {
                double d=c.getDouble(1);
                double d1=c.getDouble(2);

            }
        }
    }
    catch (Exception e)
    {
        e.printStackTrace();
    }

谷歌的解决办法:

创建表

When you create the MySQL table, you want to pay particular attention to the lat and lng attributes. With the current zoom capabilities of Google Maps, you should only need 6 digits of precision after the decimal. To keep the storage space required for your table at a minimum, you can specify that the lat and lng attributes are floats of size (10,6). That will let the fields store 6 digits after the decimal, plus up to 4 digits before the decimal, e.g. -123.456789 degrees. Your table should also have an id attribute to serve as the primary key.

CREATE TABLE `markers` (
  `id` INT NOT NULL AUTO_INCREMENT PRIMARY KEY ,
  `name` VARCHAR( 60 ) NOT NULL ,
  `address` VARCHAR( 80 ) NOT NULL ,
  `lat` FLOAT( 10, 6 ) NOT NULL ,
  `lng` FLOAT( 10, 6 ) NOT NULL
) ENGINE = MYISAM ;

填充表

创建表之后，是时候用数据填充它了。下面提供的样本数据是分布在美国各地的大约180家披萨店。在phpMyAdmin中，您可以使用IMPORT选项卡导入各种文件格式，包括CSV(逗号分隔值)。Microsoft Excel和谷歌电子表格都导出为CSV格式，因此您可以通过导出/导入CSV文件轻松地将数据从电子表格传输到MySQL表。

INSERT INTO `markers` (`name`, `address`, `lat`, `lng`) VALUES ('Frankie Johnnie & Luigo Too','939 W El Camino Real, Mountain View, CA','37.386339','-122.085823');
INSERT INTO `markers` (`name`, `address`, `lat`, `lng`) VALUES ('Amici\'s East Coast Pizzeria','790 Castro St, Mountain View, CA','37.38714','-122.083235');
INSERT INTO `markers` (`name`, `address`, `lat`, `lng`) VALUES ('Kapp\'s Pizza Bar & Grill','191 Castro St, Mountain View, CA','37.393885','-122.078916');
INSERT INTO `markers` (`name`, `address`, `lat`, `lng`) VALUES ('Round Table Pizza: Mountain View','570 N Shoreline Blvd, Mountain View, CA','37.402653','-122.079354');
INSERT INTO `markers` (`name`, `address`, `lat`, `lng`) VALUES ('Tony & Alba\'s Pizza & Pasta','619 Escuela Ave, Mountain View, CA','37.394011','-122.095528');
INSERT INTO `markers` (`name`, `address`, `lat`, `lng`) VALUES ('Oregano\'s Wood-Fired Pizza','4546 El Camino Real, Los Altos, CA','37.401724','-122.114646');

使用MySQL查找位置

要在标记表中查找给定纬度/经度的某个半径距离内的位置，可以使用基于Haversine公式的SELECT语句。哈弗辛公式一般用于计算球面上两对坐标之间的大圆距离。维基百科给出了一个深入的数学解释，Movable Type的网站上有一个关于公式的很好的讨论，因为它与编程有关。

下面的SQL语句将查找距离坐标37 -122 25英里半径内最近的20个位置。它根据该行的纬度/经度和目标纬度/经度计算距离，然后只请求距离值小于25的行，根据距离对整个查询进行排序，并将结果限制为20个。要按公里而不是英里搜索，将3959替换为6371。

SELECT 
id, 
(
   3959 *
   acos(cos(radians(37)) * 
   cos(radians(lat)) * 
   cos(radians(lng) - 
   radians(-122)) + 
   sin(radians(37)) * 
   sin(radians(lat )))
) AS distance 
FROM markers 
HAVING distance < 28 
ORDER BY distance LIMIT 0, 20;

这个方法是在小于28英里的距离内找到经纬度。

另一种方法是在28到29英里的距离上找到它们:

SELECT 
id, 
(
   3959 *
   acos(cos(radians(37)) * 
   cos(radians(lat)) * 
   cos(radians(lng) - 
   radians(-122)) + 
   sin(radians(37)) * 
   sin(radians(lat )))
) AS distance 
FROM markers 
HAVING distance < 29 and distance > 28 
ORDER BY distance LIMIT 0, 20;

https://developers.google.com/maps/articles/phpsqlsearch_v3#creating-the-map

以防你像我一样懒，这里有一个解决方案，由这个和其他关于SO的答案合并而成。

set @orig_lat=37.46; 
set @orig_long=-122.25; 
set @bounding_distance=1;

SELECT
*
,((ACOS(SIN(@orig_lat * PI() / 180) * SIN(`lat` * PI() / 180) + COS(@orig_lat * PI() / 180) * COS(`lat` * PI() / 180) * COS((@orig_long - `long`) * PI() / 180)) * 180 / PI()) * 60 * 1.1515) AS `distance` 
FROM `cities` 
WHERE
(
  `lat` BETWEEN (@orig_lat - @bounding_distance) AND (@orig_lat + @bounding_distance)
  AND `long` BETWEEN (@orig_long - @bounding_distance) AND (@orig_long + @bounding_distance)
)
ORDER BY `distance` ASC
limit 25;