Den Abstand zwischen mehreren Punkten finden - Lat/Long

Question

Ich habe eine große Tabelle mit Pickup und Dropoff lat/long Daten. Diese Tabelle hat mehrere hunderttausend Datensätze, und ich möchte die Entfernung zwischen jedem Pickup und Dropoff finden.

Kann dies mit SQL in BigQuery getan werden?

Answer 1

unten Versuchen Sie, sollte guter Anfang für Sie

SELECT 
    orderid, 
    car_number, 
    ROUND(distance) AS distance, 
    ROUND(next_distance) AS next_distance 
FROM JS(
    (
    // input table 
    SELECT 
    orderid, 
    car_number, 
    pickup_lon, 
    pickup_lat, 
    dropoff_lon, 
    dropoff_lat, 
    LEAD(pickup_lon) OVER(PARTITION BY car_number ORDER BY orderid) AS next_pickup_lon, 
    LEAD(pickup_lat) OVER(PARTITION BY car_number ORDER BY orderid) AS next_pickup_lat 
    FROM 
    (SELECT 1 AS orderid, 1 AS car_number, -121.23200000000001 AS pickup_lon, 38.1964 AS pickup_lat, -117.48 AS dropoff_lon, 34.5894 AS dropoff_lat), 
    (SELECT 2 AS orderid, 1 AS car_number, -118.76 AS pickup_lon, 34.1445 AS pickup_lat, -122.26 AS dropoff_lon, 37.7606 AS dropoff_lat), 
    (SELECT 3 AS orderid, 2 AS car_number, -117.736 AS pickup_lon, 33.5761 AS pickup_lat, -117.19333333333333 AS dropoff_lon, 34.47484444444444 AS dropoff_lat)  
) , 
// input columns 
orderid, car_number, pickup_lon, pickup_lat, dropoff_lon, dropoff_lat, next_pickup_lon, next_pickup_lat, 
// output schema 
"[{name: 'orderid', type: 'integer'}, 
{name: 'car_number', type: 'integer'}, 
{name: 'distance', type: 'float'}, 
{name: 'next_distance', type: 'float'}]", 
// function 
"function(r, emit){ 

    emit({ 
    orderid: r.orderid, car_number: r.car_number, 
    distance: dist(r.pickup_lon, r.pickup_lat, r.dropoff_lon, r.dropoff_lat), 
    next_distance: dist(r.dropoff_lon, r.dropoff_lat, r.next_pickup_lon, r.next_pickup_lat) 
    }); 

    function deg2rad(deg) { 
    return deg * (Math.PI/180) 
    } 

    function dist(pickup_lon, pickup_lat, dropoff_lon, dropoff_lat) { 
    var R = 3959; // Radius of the earth in miles 
    var dLat = deg2rad(dropoff_lat-pickup_lat); 
    var dLon = deg2rad(dropoff_lon-pickup_lon); 
    var a = Math.sin(dLat/2) * Math.sin(dLat/2) + 
     Math.cos(deg2rad(pickup_lat)) * Math.cos(deg2rad(dropoff_lat)) * 
     Math.sin(dLon/2) * Math.sin(dLon/2); 
    var c = 2 * R * Math.atan2(Math.sqrt(a), Math.sqrt(1-a)); 
    return c; 
    } 

}" 
) 

Ergebnis ist:

orderid car_number distance next_distance  
1  1   325.0  79.0  
2  1   317.0  NaN 
3  2   69.0  NaN 

Von Kommentaren: Mein Tabellenschema ist als solche:

car_number  (string) 
pu_datetime (timestamp) 
do_datetime (timestamp) 
pu_lat   (float) 
pu_long  (float) 
do_lat   (float) 
do_long  (float) 

hinzugefügt Ihr Tabellenschema aus einem einzigen Basispunkt

SELECT 
    pu_datetime, 
    car_number, 
    ROUND(distance) AS distance, 
    ROUND(next_distance) AS next_distance 
FROM JS(
    (
    // input table 
    SELECT 
    pu_datetime, 
    car_number, 
    pu_lon, 
    pu_lat, 
    do_lon, 
    do_lat, 
    LEAD(pu_lon) OVER(PARTITION BY car_number ORDER BY pu_datetime) AS next_pu_lon, 
    LEAD(pu_lat) OVER(PARTITION BY car_number ORDER BY pu_datetime) AS next_pu_lat 
    FROM 
    (SELECT timestamp('2016-07-01 13:00:00') AS pu_datetime, '1' AS car_number, -121.23200000000001 AS pu_lon, 38.1964 AS pu_lat, -117.48 AS do_lon, 34.5894 AS do_lat), 
    (SELECT timestamp('2016-07-02 10:00:00') AS pu_datetime, '1' AS car_number, -118.76 AS pu_lon, 34.1445 AS pu_lat, -122.26 AS do_lon, 37.7606 AS do_lat), 
    (SELECT timestamp('2016-07-03 11:00:00') AS pu_datetime, '2' AS car_number, -117.736 AS pu_lon, 33.5761 AS pu_lat, -117.19333333333333 AS do_lon, 34.47484444444444 AS do_lat)  
) , 
// input columns 
pu_datetime, car_number, pu_lon, pu_lat, do_lon, do_lat, next_pu_lon, next_pu_lat, 
// output schema 
"[{name: 'pu_datetime', type: 'timestamp'}, 
{name: 'car_number', type: 'string'}, 
{name: 'distance', type: 'float'}, 
{name: 'next_distance', type: 'float'}]", 
// function 
"function(r, emit){ 

    emit({ 
    pu_datetime: r.pu_datetime, car_number: r.car_number, 
    distance: dist(r.pu_lon, r.pu_lat, r.do_lon, r.do_lat), 
    next_distance: dist(r.do_lon, r.do_lat, r.next_pu_lon, r.next_pu_lat) 
    }); 

    function deg2rad(deg) { 
    return deg * (Math.PI/180) 
    } 

    function dist(pu_lon, pu_lat, do_lon, do_lat) { 
    var R = 3959; // Radius of the earth in miles 
    var dLat = deg2rad(do_lat-pu_lat); 
    var dLon = deg2rad(do_lon-pu_lon); 
    var a = Math.sin(dLat/2) * Math.sin(dLat/2) + 
     Math.cos(deg2rad(pu_lat)) * Math.cos(deg2rad(do_lat)) * 
     Math.sin(dLon/2) * Math.sin(dLon/2); 
    var c = 2 * R * Math.atan2(Math.sqrt(a), Math.sqrt(1-a)); 
    return c; 
    } 

}" 
) 

Answer 2

Diese Funktion berechnet Meilen zwischen zwei Punkten. Das ist keine FAHRTENSTRECKE. Sie müssten dafür das Google API verwenden, und ich glaube, es gibt ein Limit von 2500 Treffern pro Tag.

SET ANSI_NULLS ON 
GO 
SET QUOTED_IDENTIFIER ON 
GO 
CREATE Function [dbo].[udf-Geo-CalcMiles] (@Long1 float,@Lat1 float,@Long2 float,@Lat2 Float) 
Returns Float as 
Begin 
    Declare @Miles Float 
    Set @Miles = 0 
    Set @Miles = (Sin(Radians(@Lat1)) * Sin(Radians(@Lat2))) + (Cos(Radians(@Lat1)) * Cos(Radians(@Lat2)) * Cos(Radians(@Long2) - Radians(@Long1))) 
    Return Case When @Miles =0 then 0 else abs((3958.75 * Atan(Sqrt(1 - power(@Miles, 2))/@Miles))) end 
End 

So zum Beispiel

;with cteBase as (
    Select Top 10 
      Box_Nr 
     ,From_Lat=Box_Lat 
     ,From_Lng=Box_Lng 
     ,To_Lat = Lead(Box_Lat,1) over (Order By Box_Nr) 
     ,To_Lng = Lead(Box_Lng,1) over (Order By Box_Nr) 
    from [dbo].[USPS-Collection-Point] Order by Box_Nr 
) 
Select * 
     ,Distance = [dbo].[udf-Geo-CalcMiles] (From_Lng,From_Lat,To_Lng,To_Lat) 
From cteBase 

Returns

Box_Nr From_Lat From_Lng To_Lat  To_Lng  Distance 
1  41.6947535 -71.1394048 41.6980289 -71.1341529 0.353027299635122 
2  41.6980289 -71.1341529 41.682761 -71.124812 1.15978643547294 
3  41.682761 -71.124812 41.7051854 -71.1477813 1.95061187457874 
4  41.7051854 -71.1477813 41.7080851 -71.1441519 0.274205428604983 
5  41.7080851 -71.1441519 41.702242 -71.1282279 0.915266219941071 
6  41.702242 -71.1282279 41.711085 -71.142123 0.941821767229312 
7  41.711085 -71.142123 41.7055301 -71.1516977 0.625473329587972 
8  41.7055301 -71.1516977 41.7071749 -71.1513423 0.115113681673717 
9  41.7071749 -71.1513423 41.7079604 -71.1543306 0.163416766676813 
10  41.7079604 -71.1543306 41.667808 -71.154372 2.77425950023261