Related
This is the function I made:
create function Route_Distance (lat1 FLOAT, lng1 FLOAT, lat2 FLOAT, lng2 FLOAT)
returns float
deterministic
begin
return 6371 * 2 * ASIN(SQRT(POWER(SIN((lat1-lat2)*pi()/180 /2), 2)
+ COS(lat1 * pi()/180) * COS(lat2 * pi()/180) * POWER(SIN((lng1 - lng2)
* pi()/180 /2), 2)));
End
This is the table I need to calculate the distance from called routes_distance:
----------------------------------------------------
lat1 | lng1 | lat2 | lng2 |
----------------------------------------------------
59.914 | -61.111 | 43.211 | 54.231
----------------------------------------------------
So the function I use is this:
select route_distance(lat1,lng1,lat2, lng1)
from routes_distance;
Why is it I get a row of zeros for my result? The table is much longer, I have only shown the first row. I want to calculate all rows using this function.
I've a database table in which there are 4 columns.
1. id
2. person_name
3. country
4. zip_code
Now I want all the zip codes with their real latitude and longitude which come in a given radius of 10 mile from a given lat long.
suppose my latitude and longitudes are (19.24947300,72.85681400) and distance is 10 mile, then what SQL query should I make to return all nearest zip codes and their lat longs.
I only have the following query
SELECT ((ACOS(SIN($lat * PI() / 180) * SIN(lat * PI() / 180) + COS($lat * PI()
/ 180) * COS(lat * PI() / 180) * COS(($lon – lon) * PI() / 180)) * 180 / PI()) * 60 *
1.1515) AS `distance` FROM `members` HAVING `distance`<=’10’ ORDER BY `distance` ASC
But it requires the lat longs of all zip codes in the table but I want them in run time.
I'm not sure I understand what you mean by
But it requires the lat longs of all zip codes in the table but I want them in run time.
Since you want a SQL query, I assume that you have a table with every zip code's latitude and longitude.
You probably shouldn't do all that math in your SQL query. I would first pull every zip code that is in a 10 mile x 10 mile square centered in your queried position and then, if you really need just those that are positively in a 10 mile radius, check in your program (I assume you are using PHP, since you have variables starting with $).
SELECT zip, latitude, longitude FROM zip_positions
WHERE latitude > 19.24947300 - DISTANCE and latitude < 19.24947300 + DISTANCE
AND longitude > 72.85681400 - DISTANCE and longitude < 72.85681400 + DISTANCE
where DISTANCE is a rough equivalent to 10 miles in latitude/longitude that you would have to calculate.
Then you would, if you need it, check in PHP (or whatever language you're using) every result to see if it is indeed less than 10 miles from the point queried. I can't help you as to how to precisely convert latitude and longitude to distance in miles.
I assume this abandoned question was resolved, but let me share my opinions here in case someone else is wrestling with this one. I present 3 options for letting closet zip from DB using lat long as the lookup:
DB LOOKUP OPTION 1 (QUICK AND DIRTY):
SET #lat = 41.675868;
SET #long = -73.864484;
SET #tol = .05;
SELECT * FROM mytable.ZipCodes
WHERE latitude >= #lat AND latitude <= #lat + #tol
AND longitude >= #long AND longitude <= #long + #tol
ORDER BY (ABS(latitude-longitude) - ABS(#lat-#long)) ASC
LIMIT 1
OPTION #2 (VARIATION ON #1)
$qry = "SELECT zipcode,cityname,stateabbr FROM dealer-site.ZipCodes WHERE (latitude >= {$lat} AND latitude <= {$lat}+1) AND (ABS(longitude) >= ABS({$long}) AND ABS(longitude) < ABS({$long})+1) ORDER BY latitude ASC LIMIT 1”;
OPTION #3 BEST METHOD CALCULATE . I WOULD TRY TO USE THIS:
SET #latitude = 41.675868;
SET #longitude = -73.864484;
SELECT
*
FROM
(SELECT
*,
(((ACOS(SIN((#latitude * PI() / 180)) *
SIN((latitude * PI() / 180)) + COS((#latitude * PI() / 180)) * COS((latitude * PI() / 180)) * COS(((#longitude - longitude) * PI() / 180)))) * 180 / PI()) * 60 * 1.1515 * 1.609344) AS distance
FROM
mytable.ZipCodes) ZipCodes
WHERE
distance <= 5
LIMIT 10
PHP MYSQL (LEGACY CALL) :
$qry = "SELECT zipcode
FROM (SELECT *,
(((ACOS(SIN(({$lat} * PI() / 180)) *
SIN((`latitude` * PI() / 180)) + COS(({$lat} * PI() / 180)) * COS((`latitude` * PI() / 180)) *
COS((({$long} - `longitude`) * PI() / 180)))) * 180 / PI()) * 60 * 1.1515 * 1.609344)
AS distance
FROM
`MyDB`.ZipCodes) ZipCodes
WHERE distance <= 5
LIMIT 1
";
I am having some issues with this SQL query. This actually comes from a PROCEDURE that is dealing with spatial calculations. The procedure finds locations within a certain radius. Really I am having a hard time understanding what is going on. I just need to rewrite it for my purposes if someone could help explain a couple of things. I will be forever grateful to whoever attempts to help. Thanks so much in advance!
Link To Source: http://www.scribd.com/doc/2569355/Geo-Distance-Search-with-MySQL
Full Procedure - I Just Need Some Explanation Help On The Actual SELECT Statement - Is Here Just For Some Clarification So Whoever Is Reading Can Get A Better Understanding
CREATE PROCEDURE geodist (IN userid int, IN dist int)BEGINdeclare mylon double; declare mylat double;declare lon1 float; declare lon2 float;declare lat1 float; declare lat2 float;
-- get the original lon and lat for the userid
select longitude, latitude into mylon, mylat from users5where id=userid limit 1;
-- calculate lon and lat for the rectangle:
set lon1 = mylon-dist/abs(cos(radians(mylat))*69);set lon2 = mylon+dist/abs(cos(radians(mylat))*69);set lat1 = mylat-(dist/69); set lat2 = mylat+(dist/69);
-- run the query:
SELECT destination.*,3956 * 2 * ASIN(SQRT( POWER(SIN((orig.lat -dest.lat) * pi()/180 / 2), 2) +COS(orig.lat * pi()/180) * COS(dest.lat * pi()/180) *POWER(SIN((orig.lon -dest.lon) * pi()/180 / 2), 2) )) asdistance FROM users destination, users originWHERE origin.id=userid
and destination.longitude between lon1 and lon2 and destination.latitude between lat1 and lat2
having distance < dist ORDER BY Distance limit 10;END $$
Full Query The Part I Need a Little Clarification On:
SELECT destination.*,3956 * 2 * ASIN(SQRT( POWER(SIN((orig.lat -dest.lat) * pi()/180 / 2), 2) +COS(orig.lat * pi()/180) * COS(dest.lat * pi()/180) *POWER(SIN((orig.lon -dest.lon) * pi()/180 / 2), 2) )) as distance FROM users destination, users origin WHERE origin.id=userid
and locations.longitude between lon1 and lon2 and locations.latitude between lat1 and lat2
having distance < dist ORDER BY Distance;
First Part:
SELECT destination.*
Question: What is with the period and * after the word destination? Sure we are selecting destination but is this concatenating? Like prefixing the word destination to every column in the table?
Next Part:
3956 * 2 * ASIN(SQRT( POWER(SIN((orig.lat -dest.lat) * pi()/180 / 2), 2) +COS(orig.lat * pi()/180) * COS(dest.lat * pi()/180) *POWER(SIN((orig.lon -dest.lon) * pi()/180 / 2), 2) )) as distance
Question: Is this just performing the calculation and storing it as the keyword destination? The keyword "as" is throwing me off here. Is it searching the database for a column destination?
Third Part:
FROM users destination, users origin WHERE origin.id=userid
Question: a little confused on where the query is headed. users destination? users origin? What is this grabbing?
Last Part:
having distance < dist ORDER BY Distance;
Question: Confused about the "having" keyword and where having distance comes into play. Is it trying to grab distance from the table because this is something that is obviously calculated on the fly.
First Part
* selects all columns. You can specify all columns for a particular table using the dot notation as you would use to specify an individual column for a table. For example:
SELECT t1.* FROM t1 NATURAL JOIN t2
Will only SELECT columns from t1 even though t2 is used in the JOIN.
Next Part
This just does a mathematical calculation on some columns and aliases the result in distance (not "destination"). You can reference the result as distance in the result set. The AS keyword sets the column alias, but it is optional.
Third Part
destination and origin are aliases. They are leaving off the optional AS keyword. It would be the same to write:
FROM users AS destination, users AS origin
The users table is being renamed for the duration of the query so it can be referenced by the alias but also to avoid the collision of two of the same table name in the query which would be invalid.
Last Part
distance is an alias for the mathematical calculation above. HAVING is like WHERE, but it has to be used for aggregation (e.g. GROUP BY). I could be wrong, but I don't think it's necessary in this query.
I feel like I'm missing something here... Why doesn't the code use the 'mylon' and 'mylat' in the math part of the final query?
So, this:
SELECT destination.*,
3956 * 2 * ASIN(SQRT( POWER(SIN((orig.lat -
destination.lat) * pi()/180 / 2), 2) +
COS(orig.lat * pi()/180) * COS(destination.lat * pi()/180) *
POWER(SIN((orig.lon -destination.lon) * pi()/180 / 2), 2) ))
as distance
FROM users AS destination, users AS orig
WHERE origin.id=userid
AND destination.longitude BETWEEN lon1 AND lon2
AND destination.latitude BETWEEN lat1 AND lat2
HAVING distance < dist ORDER BY Distance limit 10;
becomes this:
SELECT destination.*,
3956 * 2 * ASIN(SQRT( POWER(SIN((mylat -
dest.lat) * pi()/180 / 2), 2) +
COS(mylat * pi()/180) * COS(dest.lat * pi()/180) *
POWER(SIN((mylon -dest.lon) * pi()/180 / 2), 2) ))
as distance
FROM users AS destination
WHERE
destination.longitude BETWEEN lon1 AND lon2
AND destination.latitude BETWEEN lat1 AND lat2
HAVING distance < dist ORDER BY Distance limit 10;
edit: my best guess is that "origin.id=userid" should read "origin.id=destination.id". Am I correct in thinking that this join is done to filter out all users who are outside of the "distance box" -- in order to avoid calculating the actual geo distance?
I have latitude and longitude and I want to pull the record from the database, which has nearest latitude and longitude by the distance, if that distance gets longer than specified one, then don't retrieve it.
Table structure:
id
latitude
longitude
place name
city
country
state
zip
sealevel
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;
where [starlat] and [startlng] is the position where to start measuring the distance.
Google's solution:
Creating the Table
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 ;
Populating the Table
After creating the table, it's time to populate it with data. The sample data provided below is for about 180 pizzarias scattered across the United States. In phpMyAdmin, you can use the IMPORT tab to import various file formats, including CSV (comma-separated values). Microsoft Excel and Google Spreadsheets both export to CSV format, so you can easily transfer data from spreadsheets to MySQL tables through exporting/importing CSV files.
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');
Finding Locations with MySQL
To find locations in your markers table that are within a certain radius distance of a given latitude/longitude, you can use a SELECT statement based on the Haversine formula. The Haversine formula is used generally for computing great-circle distances between two pairs of coordinates on a sphere. An in-depth mathemetical explanation is given by Wikipedia and a good discussion of the formula as it relates to programming is on Movable Type's site.
Here's the SQL statement that will find the closest 20 locations that are within a radius of 25 miles to the 37, -122 coordinate. It calculates the distance based on the latitude/longitude of that row and the target latitude/longitude, and then asks for only rows where the distance value is less than 25, orders the whole query by distance, and limits it to 20 results. To search by kilometers instead of miles, replace 3959 with 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;
This one is to find latitudes and longitudes in a distance less than 28 miles.
Another one is to find them in a distance between 28 and 29 miles:
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
The original answers to the question are good, but newer versions of mysql (MySQL 5.7.6 on) support geo queries, so you can now use built in functionality rather than doing complex queries.
You can now do something like:
select *, ST_Distance_Sphere( point ('input_longitude', 'input_latitude'),
point(longitude, latitude)) * .000621371192
as `distance_in_miles`
from `TableName`
having `distance_in_miles` <= 'input_max_distance'
order by `distance_in_miles` asc
The results are returned in meters. So if you want in KM simply use .001 instead of .000621371192 (which is for miles).
MySql docs are here
Here is my full solution implemented in PHP.
This solution uses the Haversine formula as presented in http://www.scribd.com/doc/2569355/Geo-Distance-Search-with-MySQL.
It should be noted that the Haversine formula experiences weaknesses around the poles. This answer shows how to implement the vincenty Great Circle Distance formula to get around this, however I chose to just use Haversine because it's good enough for my purposes.
I'm storing latitude as DECIMAL(10,8) and longitude as DECIMAL(11,8). Hopefully this helps!
showClosest.php
<?PHP
/**
* Use the Haversine Formula to display the 100 closest matches to $origLat, $origLon
* Only search the MySQL table $tableName for matches within a 10 mile ($dist) radius.
*/
include("./assets/db/db.php"); // Include database connection function
$db = new database(); // Initiate a new MySQL connection
$tableName = "db.table";
$origLat = 42.1365;
$origLon = -71.7559;
$dist = 10; // This is the maximum distance (in miles) away from $origLat, $origLon in which to search
$query = "SELECT name, latitude, longitude, 3956 * 2 *
ASIN(SQRT( POWER(SIN(($origLat - latitude)*pi()/180/2),2)
+COS($origLat*pi()/180 )*COS(latitude*pi()/180)
*POWER(SIN(($origLon-longitude)*pi()/180/2),2)))
as distance FROM $tableName WHERE
longitude between ($origLon-$dist/cos(radians($origLat))*69)
and ($origLon+$dist/cos(radians($origLat))*69)
and latitude between ($origLat-($dist/69))
and ($origLat+($dist/69))
having distance < $dist ORDER BY distance limit 100";
$result = mysql_query($query) or die(mysql_error());
while($row = mysql_fetch_assoc($result)) {
echo $row['name']." > ".$row['distance']."<BR>";
}
mysql_close($db);
?>
./assets/db/db.php
<?PHP
/**
* Class to initiate a new MySQL connection based on $dbInfo settings found in dbSettings.php
*
* #example $db = new database(); // Initiate a new database connection
* #example mysql_close($db); // close the connection
*/
class database{
protected $databaseLink;
function __construct(){
include "dbSettings.php";
$this->database = $dbInfo['host'];
$this->mysql_user = $dbInfo['user'];
$this->mysql_pass = $dbInfo['pass'];
$this->openConnection();
return $this->get_link();
}
function openConnection(){
$this->databaseLink = mysql_connect($this->database, $this->mysql_user, $this->mysql_pass);
}
function get_link(){
return $this->databaseLink;
}
}
?>
./assets/db/dbSettings.php
<?php
$dbInfo = array(
'host' => "localhost",
'user' => "root",
'pass' => "password"
);
?>
It may be possible to increase performance by using a MySQL stored procedure as suggested by the "Geo-Distance-Search-with-MySQL" article posted above.
I have a database of ~17,000 places and the query execution time is 0.054 seconds.
Just in case you are lazy like me, here's a solution amalgamated from this and other answers on SO.
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;
Easy one ;)
SELECT * FROM `WAYPOINTS` W ORDER BY
ABS(ABS(W.`LATITUDE`-53.63) +
ABS(W.`LONGITUDE`-9.9)) ASC LIMIT 30;
Just replace the coordinates with your required ones. The values have to be stored as double. This ist a working MySQL 5.x example.
Cheers
Try this, it show the nearest points to provided coordinates (within 50 km). It works perfectly:
SELECT m.name,
m.lat, m.lon,
p.distance_unit
* DEGREES(ACOS(COS(RADIANS(p.latpoint))
* COS(RADIANS(m.lat))
* COS(RADIANS(p.longpoint) - RADIANS(m.lon))
+ SIN(RADIANS(p.latpoint))
* SIN(RADIANS(m.lat)))) AS distance_in_km
FROM <table_name> AS m
JOIN (
SELECT <userLat> AS latpoint, <userLon> AS longpoint,
50.0 AS radius, 111.045 AS distance_unit
) AS p ON 1=1
WHERE m.lat
BETWEEN p.latpoint - (p.radius / p.distance_unit)
AND p.latpoint + (p.radius / p.distance_unit)
AND m.lon BETWEEN p.longpoint - (p.radius / (p.distance_unit * COS(RADIANS(p.latpoint))))
AND p.longpoint + (p.radius / (p.distance_unit * COS(RADIANS(p.latpoint))))
ORDER BY distance_in_km
Just change <table_name>. <userLat> and <userLon>
You can read more about this solution here: http://www.plumislandmedia.net/mysql/haversine-mysql-nearest-loc/
You're looking for things like the haversine formula. See here as well.
There's other ones but this is the most commonly cited.
If you're looking for something even more robust, you might want to look at your databases GIS capabilities. They're capable of some cool things like telling you whether a point (City) appears within a given polygon (Region, Country, Continent).
Check this code based on the article Geo-Distance-Search-with-MySQL:
Example: find the 10 nearest hotels to my current location in a 10 miles radius:
#Please notice that (lat,lng) values mustn't be negatives to perform all calculations
set #my_lat=34.6087674878572;
set #my_lng=58.3783670308302;
set #dist=10; #10 miles radius
SELECT dest.id, dest.lat, dest.lng, 3956 * 2 * ASIN(SQRT(POWER(SIN((#my_lat -abs(dest.lat)) * pi()/180 / 2),2) + COS(#my_lat * pi()/180 ) * COS(abs(dest.lat) * pi()/180) * POWER(SIN((#my_lng - abs(dest.lng)) * pi()/180 / 2), 2))
) as distance
FROM hotel as dest
having distance < #dist
ORDER BY distance limit 10;
#Also notice that distance are expressed in terms of radius.
Find nearest Users to my:
Distance in meters
Based in Vincenty's formula
i have User table:
+----+-----------------------+---------+--------------+---------------+
| id | email | name | location_lat | location_long |
+----+-----------------------+---------+--------------+---------------+
| 13 | xxxxxx#xxxxxxxxxx.com | Isaac | 17.2675625 | -97.6802361 |
| 14 | xxxx#xxxxxxx.com.mx | Monse | 19.392702 | -99.172596 |
+----+-----------------------+---------+--------------+---------------+
sql:
-- my location: lat 19.391124 -99.165660
SELECT
(ATAN(
SQRT(
POW(COS(RADIANS(users.location_lat)) * SIN(RADIANS(users.location_long) - RADIANS(-99.165660)), 2) +
POW(COS(RADIANS(19.391124)) * SIN(RADIANS(users.location_lat)) -
SIN(RADIANS(19.391124)) * cos(RADIANS(users.location_lat)) * cos(RADIANS(users.location_long) - RADIANS(-99.165660)), 2)
)
,
SIN(RADIANS(19.391124)) *
SIN(RADIANS(users.location_lat)) +
COS(RADIANS(19.391124)) *
COS(RADIANS(users.location_lat)) *
COS(RADIANS(users.location_long) - RADIANS(-99.165660))
) * 6371000) as distance,
users.id
FROM users
ORDER BY distance ASC
radius of the earth : 6371000 ( in meters)
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();
}
It sounds like you want to do a nearest neighbour search with some bound on the distance. SQL does not support anything like this as far as I am aware and you would need to use an alternative data structure such as an R-tree or kd-tree.
MS SQL Edition here:
DECLARE #SLAT AS FLOAT
DECLARE #SLON AS FLOAT
SET #SLAT = 38.150785
SET #SLON = 27.360249
SELECT TOP 10 [LATITUDE], [LONGITUDE], SQRT(
POWER(69.1 * ([LATITUDE] - #SLAT), 2) +
POWER(69.1 * (#SLON - [LONGITUDE]) * COS([LATITUDE] / 57.3), 2)) AS distance
FROM [TABLE] ORDER BY 3
Sounds like you should just use PostGIS, SpatialLite, SQLServer2008, or Oracle Spatial. They can all answer this question for you with spatial SQL.
+----+-----------------------+---------+--------------+---------------+
| id | email | name | location_lat | location_long |
+----+-----------------------+---------+--------------+---------------+
| 7 | test#gmail.com | rembo | 23.0249256 | 72.5269697 |
| 25 | test1#gmail.com. | Rajnis | 23.0233221 | 72.5342112 |
+----+-----------------------+---------+--------------+---------------+
$lat = 23.02350629;
$long = 72.53230239;
DB::
SELECT
("
SELECT
*
FROM
(
SELECT
,
(
( ( acos( sin(( ". $ lat ." * pi() / 180)) * sin(( lat * pi() / 180)) + cos(( ". $ lat ." pi() / 180 )) * cos(( lat * pi() / 180)) * cos((( ". $ long ." - LONG) * pi() / 180))) ) * 180 / pi() ) * 60 * 1.1515 * 1.609344
)
as distance
FROM
users
)
users
WHERE
distance <= 2");
In extreme cases this approach fails, but for performance, I've skipped the trigonometry and simply calculated the diagonal squared.
Mysql query for search coordinates with distance limit and where condition
SELECT id, ( 3959 * acos( cos( radians('28.5850154') ) * cos( radians(latitude) ) * cos( radians( longitude ) - radians('77.07207489999999') ) + sin( radians('28.5850154') ) * sin( radians( latitude ) ) ) ) AS distance FROM `vendors` HAVING distance < 5;
This problem is not very hard at all, but it gets more complicated if you need to optimize it.
What I mean is, do you have 100 locations in your database or 100 million? It makes a big difference.
If the number of locations is small, get them out of SQL and into code by just doing ->
Select * from Location
Once you get them into code, calculate the distance between each lat/lon and your original with the Haversine formula and sort it.
I currently have just under a million locations in a mysql database all with longitude and latitude information.
I am trying to find the distance between one point and many other points via a query. It's not as fast as I want it to be especially with 100+ hits a second.
Is there a faster query or possibly a faster system other than mysql for this? I'm using this query:
SELECT
name,
( 3959 * acos( cos( radians(42.290763) ) * cos( radians( locations.lat ) )
* cos( radians(locations.lng) - radians(-71.35368)) + sin(radians(42.290763))
* sin( radians(locations.lat)))) AS distance
FROM locations
WHERE active = 1
HAVING distance < 10
ORDER BY distance;
Note: The provided distance is in Miles. If you need Kilometers, use 6371 instead of 3959.
Create your points using Point values of Geometry data types in MyISAM table. As of Mysql 5.7.5, InnoDB tables now also support SPATIAL indices.
Create a SPATIAL index on these points
Use MBRContains() to find the values:
SELECT *
FROM table
WHERE MBRContains(LineFromText(CONCAT(
'('
, #lon + 10 / ( 111.1 / cos(RADIANS(#lat)))
, ' '
, #lat + 10 / 111.1
, ','
, #lon - 10 / ( 111.1 / cos(RADIANS(#lat)))
, ' '
, #lat - 10 / 111.1
, ')' )
,mypoint)
, or, in MySQL 5.1 and above:
SELECT *
FROM table
WHERE MBRContains
(
LineString
(
Point (
#lon + 10 / ( 111.1 / COS(RADIANS(#lat))),
#lat + 10 / 111.1
),
Point (
#lon - 10 / ( 111.1 / COS(RADIANS(#lat))),
#lat - 10 / 111.1
)
),
mypoint
)
This will select all points approximately within the box (#lat +/- 10 km, #lon +/- 10km).
This actually is not a box, but a spherical rectangle: latitude and longitude bound segment of the sphere. This may differ from a plain rectangle on the Franz Joseph Land, but quite close to it on most inhabited places.
Apply additional filtering to select everything inside the circle (not the square)
Possibly apply additional fine filtering to account for the big circle distance (for large distances)
Not a MySql specific answer, but it'll improve the performance of your sql statement.
What you're effectively doing is calculating the distance to every point in the table, to see if it's within 10 units of a given point.
What you can do before you run this sql, is create four points that draw a box 20 units on a side, with your point in the center i.e.. (x1,y1 ) . . . (x4, y4), where (x1,y1) is (givenlong + 10 units, givenLat + 10units) . . . (givenLong - 10units, givenLat -10 units).
Actually, you only need two points, top left and bottom right call them (X1, Y1) and (X2, Y2)
Now your SQL statement use these points to exclude rows that definitely are more than 10u from your given point, it can use indexes on the latitudes & longitudes, so will be orders of magnitude faster than what you currently have.
e.g.
select . . .
where locations.lat between X1 and X2
and locations.Long between y1 and y2;
The box approach can return false positives (you can pick up points in the corners of the box that are > 10u from the given point), so you still need to calculate the distance of each point. However this again will be much faster because you have drastically limited the number of points to test to the points within the box.
I call this technique "Thinking inside the box" :)
EDIT: Can this be put into one SQL statement?
I have no idea what mySql or Php is capable of, sorry.
I don't know where the best place is to build the four points, or how they could be passed to a mySql query in Php. However, once you have the four points, there's nothing stopping you combining your own SQL statement with mine.
select name,
( 3959 * acos( cos( radians(42.290763) )
* cos( radians( locations.lat ) )
* cos( radians( locations.lng ) - radians(-71.35368) )
+ sin( radians(42.290763) )
* sin( radians( locations.lat ) ) ) ) AS distance
from locations
where active = 1
and locations.lat between X1 and X2
and locations.Long between y1 and y2
having distance < 10 ORDER BY distance;
I know with MS SQL I can build a SQL statement that declares four floats (X1, Y1, X2, Y2) and calculates them before the "main" select statement, like I said, I've no idea if this can be done with MySql. However I'd still be inclined to build the four points in C# and pass them as parameters to the SQL query.
Sorry I can't be more help, if anyone can answer the MySQL & Php specific portions of this, feel free to edit this answer to do so.
I needed to solve similar problem (filtering rows by distance from single point) and by combining original question with answers and comments, I came up with solution which perfectly works for me on both MySQL 5.6 and 5.7.
SELECT
*,
(6371 * ACOS(COS(RADIANS(56.946285)) * COS(RADIANS(Y(coordinates)))
* COS(RADIANS(X(coordinates)) - RADIANS(24.105078)) + SIN(RADIANS(56.946285))
* SIN(RADIANS(Y(coordinates))))) AS distance
FROM places
WHERE MBRContains
(
LineString
(
Point (
24.105078 + 15 / (111.320 * COS(RADIANS(56.946285))),
56.946285 + 15 / 111.133
),
Point (
24.105078 - 15 / (111.320 * COS(RADIANS(56.946285))),
56.946285 - 15 / 111.133
)
),
coordinates
)
HAVING distance < 15
ORDER By distance
coordinates is field with type POINT and has SPATIAL index
6371 is for calculating distance in kilometres
56.946285 is latitude for central point
24.105078 is longitude for central point
15 is maximum distance in kilometers
In my tests, MySQL uses SPATIAL index on coordinates field to quickly select all rows which are within rectangle and then calculates actual distance for all filtered places to exclude places from rectangles corners and leave only places inside circle.
This is visualisation of my result:
Gray stars visualise all points on map, yellow stars are ones returned by MySQL query. Gray stars inside corners of rectangle (but outside circle) were selected by MBRContains() and then deselected by HAVING clause.
The following MySQL function was posted on this blog post. I haven't tested it much, but from what I gathered from the post, if your latitude and longitude fields are indexed, this may work well for you:
DELIMITER $$
DROP FUNCTION IF EXISTS `get_distance_in_miles_between_geo_locations` $$
CREATE FUNCTION get_distance_in_miles_between_geo_locations(
geo1_latitude decimal(10,6), geo1_longitude decimal(10,6),
geo2_latitude decimal(10,6), geo2_longitude decimal(10,6))
returns decimal(10,3) DETERMINISTIC
BEGIN
return ((ACOS(SIN(geo1_latitude * PI() / 180) * SIN(geo2_latitude * PI() / 180)
+ COS(geo1_latitude * PI() / 180) * COS(geo2_latitude * PI() / 180)
* COS((geo1_longitude - geo2_longitude) * PI() / 180)) * 180 / PI())
* 60 * 1.1515);
END $$
DELIMITER ;
Sample usage:
Assuming a table called places with fields latitude & longitude:
SELECT get_distance_in_miles_between_geo_locations(-34.017330, 22.809500,
latitude, longitude) AS distance_from_input FROM places;
if you are using MySQL 5.7.*, then you can use st_distance_sphere(POINT, POINT).
Select st_distance_sphere(POINT(-2.997065, 53.404146 ), POINT(58.615349, 23.56676 ))/1000 as distcance
SELECT * FROM (SELECT *,(((acos(sin((43.6980168*pi()/180)) *
sin((latitude*pi()/180))+cos((43.6980168*pi()/180)) *
cos((latitude*pi()/180)) * cos(((7.266903899999988- longitude)*
pi()/180))))*180/pi())*60*1.1515 ) as distance
FROM wp_users WHERE 1 GROUP BY ID limit 0,10) as X
ORDER BY ID DESC
This is the distance calculation query between to points in MySQL, I have used it in a long database, it it working perfect! Note: do the changes (database name, table name, column etc) as per your requirements.
set #latitude=53.754842;
set #longitude=-2.708077;
set #radius=20;
set #lng_min = #longitude - #radius/abs(cos(radians(#latitude))*69);
set #lng_max = #longitude + #radius/abs(cos(radians(#latitude))*69);
set #lat_min = #latitude - (#radius/69);
set #lat_max = #latitude + (#radius/69);
SELECT * FROM postcode
WHERE (longitude BETWEEN #lng_min AND #lng_max)
AND (latitude BETWEEN #lat_min and #lat_max);
source
select
(((acos(sin(('$latitude'*pi()/180)) * sin((`lat`*pi()/180))+cos(('$latitude'*pi()/180))
* cos((`lat`*pi()/180)) * cos((('$longitude'- `lng`)*pi()/180))))*180/pi())*60*1.1515)
AS distance
from table having distance<22;
A MySQL function which returns the number of metres between the two coordinates:
CREATE FUNCTION DISTANCE_BETWEEN (lat1 DOUBLE, lon1 DOUBLE, lat2 DOUBLE, lon2 DOUBLE)
RETURNS DOUBLE DETERMINISTIC
RETURN ACOS( SIN(lat1*PI()/180)*SIN(lat2*PI()/180) + COS(lat1*PI()/180)*COS(lat2*PI()/180)*COS(lon2*PI()/180-lon1*PI()/180) ) * 6371000
To return the value in a different format, replace the 6371000 in the function with the radius of Earth in your choice of unit. For example, kilometres would be 6371 and miles would be 3959.
To use the function, just call it as you would any other function in MySQL. For example, if you had a table city, you could find the distance between every city to every other city:
SELECT
`city1`.`name`,
`city2`.`name`,
ROUND(DISTANCE_BETWEEN(`city1`.`latitude`, `city1`.`longitude`, `city2`.`latitude`, `city2`.`longitude`)) AS `distance`
FROM
`city` AS `city1`
JOIN
`city` AS `city2`
The full code with details about how to install as MySQL plugin are here: https://github.com/lucasepe/lib_mysqludf_haversine
I posted this last year as comment. Since kindly #TylerCollier suggested me to post as answer, here it is.
Another way is to write a custom UDF function that returns the haversine distance from two points. This function can take in input:
lat1 (real), lng1 (real), lat2 (real), lng2 (real), type (string - optinal - 'km', 'ft', 'mi')
So we can write something like this:
SELECT id, name FROM MY_PLACES WHERE haversine_distance(lat1, lng1, lat2, lng2) < 40;
to fetch all records with a distance less then 40 kilometers. Or:
SELECT id, name FROM MY_PLACES WHERE haversine_distance(lat1, lng1, lat2, lng2, 'ft') < 25;
to fetch all records with a distance less then 25 feet.
The core function is:
double
haversine_distance( UDF_INIT* initid, UDF_ARGS* args, char* is_null, char *error ) {
double result = *(double*) initid->ptr;
/*Earth Radius in Kilometers.*/
double R = 6372.797560856;
double DEG_TO_RAD = M_PI/180.0;
double RAD_TO_DEG = 180.0/M_PI;
double lat1 = *(double*) args->args[0];
double lon1 = *(double*) args->args[1];
double lat2 = *(double*) args->args[2];
double lon2 = *(double*) args->args[3];
double dlon = (lon2 - lon1) * DEG_TO_RAD;
double dlat = (lat2 - lat1) * DEG_TO_RAD;
double a = pow(sin(dlat * 0.5),2) +
cos(lat1*DEG_TO_RAD) * cos(lat2*DEG_TO_RAD) * pow(sin(dlon * 0.5),2);
double c = 2.0 * atan2(sqrt(a), sqrt(1-a));
result = ( R * c );
/*
* If we have a 5th distance type argument...
*/
if (args->arg_count == 5) {
str_to_lowercase(args->args[4]);
if (strcmp(args->args[4], "ft") == 0) result *= 3280.8399;
if (strcmp(args->args[4], "mi") == 0) result *= 0.621371192;
}
return result;
}
A fast, simple and accurate (for smaller distances) approximation can be done with a spherical projection. At least in my routing algorithm I get a 20% boost compared to the correct calculation. In Java code it looks like:
public double approxDistKm(double fromLat, double fromLon, double toLat, double toLon) {
double dLat = Math.toRadians(toLat - fromLat);
double dLon = Math.toRadians(toLon - fromLon);
double tmp = Math.cos(Math.toRadians((fromLat + toLat) / 2)) * dLon;
double d = dLat * dLat + tmp * tmp;
return R * Math.sqrt(d);
}
Not sure about MySQL (sorry!).
Be sure you know about the limitation (the third param of assertEquals means the accuracy in kilometers):
float lat = 24.235f;
float lon = 47.234f;
CalcDistance dist = new CalcDistance();
double res = 15.051;
assertEquals(res, dist.calcDistKm(lat, lon, lat - 0.1, lon + 0.1), 1e-3);
assertEquals(res, dist.approxDistKm(lat, lon, lat - 0.1, lon + 0.1), 1e-3);
res = 150.748;
assertEquals(res, dist.calcDistKm(lat, lon, lat - 1, lon + 1), 1e-3);
assertEquals(res, dist.approxDistKm(lat, lon, lat - 1, lon + 1), 1e-2);
res = 1527.919;
assertEquals(res, dist.calcDistKm(lat, lon, lat - 10, lon + 10), 1e-3);
assertEquals(res, dist.approxDistKm(lat, lon, lat - 10, lon + 10), 10);
Here is a very detailed description of Geo Distance Search with MySQL a solution based on implementation of Haversine Formula to mysql. The complete solution description with theory, implementation and further performance optimization. Although the spatial optimization part didn't work correct in my case.
http://www.scribd.com/doc/2569355/Geo-Distance-Search-with-MySQL
Have a read of Geo Distance Search with MySQL, a solution
based on implementation of Haversine Formula to MySQL. This is a complete solution
description with theory, implementation and further performance optimization.
Although the spatial optimization part didn't work correctly in my case.
I noticed two mistakes in this:
the use of abs in the select statement on p8. I just omitted abs and it worked.
the spatial search distance function on p27 does not convert to radians or multiply longitude by cos(latitude), unless his spatial data is loaded with this in consideration (cannot tell from context of article), but his example on p26 indicates that his spatial data POINT is not loaded with radians or degrees.
$objectQuery = "SELECT table_master.*, ((acos(sin((" . $latitude . "*pi()/180)) * sin((`latitude`*pi()/180))+cos((" . $latitude . "*pi()/180)) * cos((`latitude`*pi()/180)) * cos(((" . $longitude . "- `longtude`)* pi()/180))))*180/pi())*60*1.1515 as distance FROM `table_post_broadcasts` JOIN table_master ON table_post_broadcasts.master_id = table_master.id WHERE table_master.type_of_post ='type' HAVING distance <='" . $Radius . "' ORDER BY distance asc";
Using mysql
SET #orig_lon = 1.027125;
SET #dest_lon = 1.027125;
SET #orig_lat = 2.398441;
SET #dest_lat = 2.398441;
SET #kmormiles = 6371;-- for distance in miles set to : 3956
SELECT #kmormiles * ACOS(LEAST(COS(RADIANS(#orig_lat)) *
COS(RADIANS(#dest_lat)) * COS(RADIANS(#orig_lon - #dest_lon)) +
SIN(RADIANS(#orig_lat)) * SIN(RADIANS(#dest_lat)),1.0)) as distance;
See: https://andrew.hedges.name/experiments/haversine/
See: https://stackoverflow.com/a/24372831/5155484
See: http://www.plumislandmedia.net/mysql/haversine-mysql-nearest-loc/
NOTE: LEAST is used to avoid null values as a comment suggested on https://stackoverflow.com/a/24372831/5155484
I really liked #Māris Kiseļovs solution, but I like many others may have the Lat and lng's POINTS reversed from his example. In generalising it I though I would share it. In my case I need to find all the start_points that are within a certain radius of an end_point.
I hope this helps someone.
SELECT #LAT := ST_X(end_point), #LNG := ST_Y(end_point) FROM routes WHERE route_ID = 280;
SELECT
*,
(6371e3 * ACOS(COS(RADIANS(#LAT)) * COS(RADIANS(ST_X(start_point)))
* COS(RADIANS(ST_Y(start_point)) - RADIANS(#LNG)) + SIN(RADIANS(#LAT))
* SIN(RADIANS(ST_X(start_point))))) AS distance
FROM routes
WHERE MBRContains
(
LineString
(
Point (
#LNG + 15 / (111.320 * COS(RADIANS(#LAT))),
#LAT + 15 / 111.133
),
Point (
#LNG - 15 / (111.320 * COS(RADIANS(#LAT))),
#LAT - 15 / 111.133
)
),
POINT(ST_Y(end_point),ST_X(end_point))
)
HAVING distance < 100
ORDER By distance;