GROUPING_ID SQL function


1. Usage of GROUPING_ID with ROLLUP to show total freight country and city wise.

SQL Server Query 1

            
SELECT  
c.Country,
c.City,
SUM(o.Freight) AS TotalFreight,
GROUPING(c.Country) AS GroupingCountry,
GROUPING(c.City) AS GroupingCity,
GROUPING_ID(c.Country, c.City) AS GroupingID
FROM Customers c
JOIN Orders o ON c.CustomerID = o.CustomerID
GROUP BY ROLLUP (c.Country, c.City)
ORDER BY c.Country, c.City;

Create SQL query with SqlQueryBuilder 1

            
.Select()  
.Columns("c.Country", "c.City")
.Column(new SUM(new Column("o.Freight")), "TotalFreight")
.Column(new GROUPING(new Column("c.Country")), "GroupingCountry")
.Column(new GROUPING(new Column("c.City")), "GroupingCity")
.Column(new GROUPING_ID(new Column("c.Country"), new Column("c.City")), "GroupingID")
.From("Customers", "c")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Orders", "o")
.On(new Column("c.CustomerID").Equale(new Column("o.CustomerID")))
})
.GroupBy(new GroupBy(new Column("c.Country"), new Column("c.City")).WithRollUp())
.OrderBy(new OrderBy()
.SetColumnAscending("c.Country")
.SetColumnAscending("c.City"))
.Build();

Query build by SqlQueryBuilder 1

            
SELECT c.Country,
       c.City,
       SUM(o.Freight) AS TotalFreight,
       GROUPING(c.Country) AS GroupingCountry,
       GROUPING(c.City) AS GroupingCity,
       GROUPING_ID(c.Country, c.City) AS GroupingID
FROM Customers AS c
     INNER JOIN
     Orders AS o
     ON c.CustomerID = o.CustomerID
GROUP BY ROLLUP(c.Country, c.City)
ORDER BY c.Country ASC, c.City ASC;


            
        

Parameters (If used)

Name Value

Query Results 1:

  Country City TotalFreight GroupingCountry GroupingCity GroupingID
1 64942.6900 1 1 3
2 Argentina 598.5800 0 1 1
3 Argentina Buenos Aires 598.5800 0 0 0
4 Austria 7391.5000 0 1 1
5 Austria Graz 6205.3900 0 0 0
6 Austria Salzburg 1186.1100 0 0 0
7 Belgium 1280.1400 0 1 1
8 Belgium Bruxelles 458.9100 0 0 0
9 Belgium Charleroi 821.2300 0 0 0
10 Brazil 4880.1900 0 1 1
11 Brazil Campinas 322.3800 0 0 0
12 Brazil Resende 194.7100 0 0 0
13 Brazil Rio de Janeiro 1685.2700 0 0 0
14 Brazil Sao Paulo 2677.8300 0 0 0
15 Canada 2198.0900 0 1 1
16 Canada Montréal 1394.2200 0 0 0
17 Canada Tsawassen 793.9500 0 0 0
18 Canada Vancouver 9.9200 0 0 0
19 Denmark 1396.1900 0 1 1
20 Denmark Århus 947.3400 0 0 0
21 Denmark Kobenhavn 448.8500 0 0 0
22 Finland 910.8900 0 1 1
23 Finland Helsinki 88.4100 0 0 0
24 Finland Oulu 822.4800 0 0 0
25 France 4237.8400 0 1 1
26 France Lille 637.9400 0 0 0
27 France Lyon 493.2500 0 0 0
28 France Marseille 1357.8700 0 0 0
29 France Nantes 235.1200 0 0 0
30 France Paris 108.2800 0 0 0
31 France Reims 58.4100 0 0 0
32 France Strasbourg 623.6600 0 0 0
33 France Toulouse 635.8200 0 0 0
34 France Versailles 87.4900 0 0 0
35 Germany 11283.2800 0 1 1
36 Germany Aachen 306.0400 0 0 0
37 Germany Berlin 225.5800 0 0 0
38 Germany Brandenburg 813.6800 0 0 0
39 Germany Cunewalde 5605.6300 0 0 0
40 Germany Frankfurt a.M. 1017.0300 0 0 0
41 Germany Köln 862.7400 0 0 0
42 Germany Leipzig 322.0400 0 0 0
43 Germany Mannheim 168.2600 0 0 0
44 Germany München 1403.4400 0 0 0
45 Germany Münster 125.9700 0 0 0
46 Germany Stuttgart 432.8700 0 0 0
47 Ireland 2755.2400 0 1 1
48 Ireland Cork 2755.2400 0 0 0
49 Italy 864.4400 0 1 1
50 Italy Bergamo 469.7500 0 0 0
51 Italy Reggio Emilia 319.5600 0 0 0
52 Italy Torino 75.1300 0 0 0
53 Mexico 1122.7800 0 1 1
54 Mexico México D.F. 1122.7800 0 0 0
55 Norway 275.5000 0 1 1
56 Norway Stavern 275.5000 0 0 0
57 Poland 175.7400 0 1 1
58 Poland Warszawa 175.7400 0 0 0
59 Portugal 643.5300 0 1 1
60 Portugal Lisboa 643.5300 0 0 0
61 Spain 861.8900 0 1 1
62 Spain Barcelona 37.9800 0 0 0
63 Spain Madrid 255.6400 0 0 0
64 Spain Sevilla 568.2700 0 0 0
65 Sweden 3237.6000 0 1 1
66 Sweden Bräcke 1678.0800 0 0 0
67 Sweden Luleå 1559.5200 0 0 0
68 Switzerland 1368.5300 0 1 1
69 Switzerland Bern 367.2400 0 0 0
70 Switzerland Genève 1001.2900 0 0 0
71 UK 2954.2700 0 1 1
72 UK Cowes 363.6500 0 0 0
73 UK London 2590.6200 0 0 0
74 USA 13771.2900 0 1 1
75 USA Albuquerque 2134.2100 0 0 0
76 USA Anchorage 983.5300 0 0 0
77 USA Boise 6683.7000 0 0 0
78 USA Butte 129.9600 0 0 0
79 USA Elgin 207.0800 0 0 0
80 USA Eugene 1087.6100 0 0 0
81 USA Kirkland 70.0100 0 0 0
82 USA Lander 558.6700 0 0 0
83 USA Portland 341.9500 0 0 0
84 USA San Francisco 202.1100 0 0 0
85 USA Seattle 1353.0600 0 0 0
86 USA Walla Walla 19.4000 0 0 0
87 Venezuela 2735.1800 0 1 1
88 Venezuela Barquisimeto 734.4100 0 0 0
89 Venezuela Caracas 67.8000 0 0 0
90 Venezuela I. de Margarita 673.8100 0 0 0
91 Venezuela San Cristóbal 1259.1600 0 0 0


2. Usage of GROUPING_ID with GROUPING SETS

SQL Server Query 2

            
SELECT  
c.Country,
c.City,
s.CompanyName AS Shipper,
SUM(o.Freight) AS TotalFreight,
GROUPING(c.Country) AS GroupingCountry,
GROUPING(c.City) AS GroupingCity,
GROUPING(s.CompanyName) AS GroupingShipper,
GROUPING_ID(c.Country, c.City, s.CompanyName) AS GroupingID
FROM Customers c
JOIN Orders o ON c.CustomerID = o.CustomerID
JOIN Shippers s ON o.ShipVia = s.ShipperID
GROUP BY GROUPING SETS (
(c.Country, c.City),
(c.Country, s.CompanyName),
(s.CompanyName),
() -- Grand total
)
ORDER BY c.Country, c.City, s.CompanyName;

Create SQL query with SqlQueryBuilder 2

            
var (sql2, parameters2) = new SqlQueryBuilder()  
.Select()
.Columns("c.Country", "c.City")
.Column("s.CompanyName","Shipper")
.Column(new SUM(new Column("o.Freight")), "TotalFreight")
.Column(new GROUPING(new Column("c.Country")), "CountryGrouping")
.Column(new GROUPING(new Column("c.City")), "CustomerGrouping")
.Column(new GROUPING(new Column("s.CompanyName")), "GroupingShipper")
.Column(new GROUPING_ID(new Column("c.Country"), new Column("c.City"), new Column("s.CompanyName")), "GroupingID")
.From("Customers", "c")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Orders", "o")
.On(new Column("c.CustomerID").Equale(new Column("o.CustomerID"))),
new INNERJOIN().TableName("Shippers", "s")
.On(new Column("o.ShipVia").Equale(new Column("s.ShipperID")))
})
.GroupBy(new GroupBy().WithGroupingSets(new List<List<string>>()
{
new List<string> { "c.Country", "c.City" },
new List<string> { "c.Country", "s.CompanyName" },
new List<string> { "s.CompanyName" },
new List<string>()
}))
.OrderBy(new OrderBy()
.SetColumnAscending("c.Country")
.SetColumnAscending("c.City")
.SetColumnAscending("s.CompanyName"))
.Build();

Query build by SqlQueryBuilder 2

            
SELECT c.Country,
       c.City,
       s.CompanyName AS Shipper,
       SUM(o.Freight) AS TotalFreight,
       GROUPING(c.Country) AS CountryGrouping,
       GROUPING(c.City) AS CustomerGrouping,
       GROUPING(s.CompanyName) AS GroupingShipper,
       GROUPING_ID(c.Country, c.City, s.CompanyName) AS GroupingID
FROM Customers AS c
     INNER JOIN
     Orders AS o
     ON c.CustomerID = o.CustomerID
     INNER JOIN
     Shippers AS s
     ON o.ShipVia = s.ShipperID
GROUP BY GROUPING SETS((c.Country, c.City), (c.Country, s.CompanyName), (s.CompanyName), ())
ORDER BY c.Country ASC, c.City ASC, s.CompanyName ASC;


            
        

Parameters (If used)

Name Value

Query Results 2:

  Country City Shipper TotalFreight GroupingCountry GroupingCity GroupingID GroupingShipper
1 64942.6900 0 0 7 1
2 Federal Shipping 20512.5100 0 0 6 0
3 Speedy Express 16185.3300 0 0 6 0
4 United Package 28244.8500 0 0 6 0
5 Argentina Federal Shipping 55.5400 0 0 2 0
6 Argentina Speedy Express 131.9700 0 0 2 0
7 Argentina United Package 411.0700 0 0 2 0
8 Argentina Buenos Aires 598.5800 0 0 1 1
9 Austria Federal Shipping 2107.1000 0 0 2 0
10 Austria Speedy Express 2218.5700 0 0 2 0
11 Austria United Package 3065.8300 0 0 2 0
12 Austria Graz 6205.3900 0 0 1 1
13 Austria Salzburg 1186.1100 0 0 1 1
14 Belgium Federal Shipping 279.7300 0 0 2 0
15 Belgium Speedy Express 269.0000 0 0 2 0
16 Belgium United Package 731.4100 0 0 2 0
17 Belgium Bruxelles 458.9100 0 0 1 1
18 Belgium Charleroi 821.2300 0 0 1 1
19 Brazil Federal Shipping 823.8400 0 0 2 0
20 Brazil Speedy Express 1542.9200 0 0 2 0
21 Brazil United Package 2513.4300 0 0 2 0
22 Brazil Campinas 322.3800 0 0 1 1
23 Brazil Resende 194.7100 0 0 1 1
24 Brazil Rio de Janeiro 1685.2700 0 0 1 1
25 Brazil Sao Paulo 2677.8300 0 0 1 1
26 Canada Federal Shipping 848.2900 0 0 2 0
27 Canada Speedy Express 284.1000 0 0 2 0
28 Canada United Package 1065.7000 0 0 2 0
29 Canada Montréal 1394.2200 0 0 1 1
30 Canada Tsawassen 793.9500 0 0 1 1
31 Canada Vancouver 9.9200 0 0 1 1
32 Denmark Federal Shipping 390.4400 0 0 2 0
33 Denmark Speedy Express 400.8400 0 0 2 0
34 Denmark United Package 604.9100 0 0 2 0
35 Denmark Århus 947.3400 0 0 1 1
36 Denmark Kobenhavn 448.8500 0 0 1 1
37 Finland Federal Shipping 233.3000 0 0 2 0
38 Finland Speedy Express 278.0100 0 0 2 0
39 Finland United Package 399.5800 0 0 2 0
40 Finland Helsinki 88.4100 0 0 1 1
41 Finland Oulu 822.4800 0 0 1 1
42 France Federal Shipping 1823.3700 0 0 2 0
43 France Speedy Express 1149.9800 0 0 2 0
44 France United Package 1264.4900 0 0 2 0
45 France Lille 637.9400 0 0 1 1
46 France Lyon 493.2500 0 0 1 1
47 France Marseille 1357.8700 0 0 1 1
48 France Nantes 235.1200 0 0 1 1
49 France Paris 108.2800 0 0 1 1
50 France Reims 58.4100 0 0 1 1
51 France Strasbourg 623.6600 0 0 1 1
52 France Toulouse 635.8200 0 0 1 1
53 France Versailles 87.4900 0 0 1 1
54 Germany Federal Shipping 3646.9900 0 0 2 0
55 Germany Speedy Express 3671.9600 0 0 2 0
56 Germany United Package 3964.3300 0 0 2 0
57 Germany Aachen 306.0400 0 0 1 1
58 Germany Berlin 225.5800 0 0 1 1
59 Germany Brandenburg 813.6800 0 0 1 1
60 Germany Cunewalde 5605.6300 0 0 1 1
61 Germany Frankfurt a.M. 1017.0300 0 0 1 1
62 Germany Köln 862.7400 0 0 1 1
63 Germany Leipzig 322.0400 0 0 1 1
64 Germany Mannheim 168.2600 0 0 1 1
65 Germany München 1403.4400 0 0 1 1
66 Germany Münster 125.9700 0 0 1 1
67 Germany Stuttgart 432.8700 0 0 1 1
68 Ireland Federal Shipping 602.1200 0 0 2 0
69 Ireland Speedy Express 262.7100 0 0 2 0
70 Ireland United Package 1890.4100 0 0 2 0
71 Ireland Cork 2755.2400 0 0 1 1
72 Italy Federal Shipping 203.3600 0 0 2 0
73 Italy Speedy Express 452.6500 0 0 2 0
74 Italy United Package 208.4300 0 0 2 0
75 Italy Bergamo 469.7500 0 0 1 1
76 Italy Reggio Emilia 319.5600 0 0 1 1
77 Italy Torino 75.1300 0 0 1 1
78 Mexico Federal Shipping 418.3400 0 0 2 0
79 Mexico Speedy Express 176.3100 0 0 2 0
80 Mexico United Package 528.1300 0 0 2 0
81 Mexico México D.F. 1122.7800 0 0 1 1
82 Norway Federal Shipping 38.6400 0 0 2 0
83 Norway Speedy Express 13.3700 0 0 2 0
84 Norway United Package 223.4900 0 0 2 0
85 Norway Stavern 275.5000 0 0 1 1
86 Poland Federal Shipping 66.0600 0 0 2 0
87 Poland Speedy Express 8.7200 0 0 2 0
88 Poland United Package 100.9600 0 0 2 0
89 Poland Warszawa 175.7400 0 0 1 1
90 Portugal Federal Shipping 256.0400 0 0 2 0
91 Portugal Speedy Express 67.7200 0 0 2 0
92 Portugal United Package 319.7700 0 0 2 0
93 Portugal Lisboa 643.5300 0 0 1 1
94 Spain Federal Shipping 128.5200 0 0 2 0
95 Spain Speedy Express 185.3300 0 0 2 0
96 Spain United Package 548.0400 0 0 2 0
97 Spain Barcelona 37.9800 0 0 1 1
98 Spain Madrid 255.6400 0 0 1 1
99 Spain Sevilla 568.2700 0 0 1 1
100 Sweden Federal Shipping 521.9900 0 0 2 0
101 Sweden Speedy Express 968.7000 0 0 2 0
102 Sweden United Package 1746.9100 0 0 2 0
103 Sweden Bräcke 1678.0800 0 0 1 1
104 Sweden Luleå 1559.5200 0 0 1 1
105 Switzerland Federal Shipping 625.2200 0 0 2 0
106 Switzerland Speedy Express 250.5300 0 0 2 0
107 Switzerland United Package 492.7800 0 0 2 0
108 Switzerland Bern 367.2400 0 0 1 1
109 Switzerland Genève 1001.2900 0 0 1 1
110 UK Federal Shipping 984.7100 0 0 2 0
111 UK Speedy Express 735.8800 0 0 2 0
112 UK United Package 1233.6800 0 0 2 0
113 UK Cowes 363.6500 0 0 1 1
114 UK London 2590.6200 0 0 1 1
115 USA Federal Shipping 5697.9900 0 0 2 0
116 USA Speedy Express 2294.7200 0 0 2 0
117 USA United Package 5778.5800 0 0 2 0
118 USA Albuquerque 2134.2100 0 0 1 1
119 USA Anchorage 983.5300 0 0 1 1
120 USA Boise 6683.7000 0 0 1 1
121 USA Butte 129.9600 0 0 1 1
122 USA Elgin 207.0800 0 0 1 1
123 USA Eugene 1087.6100 0 0 1 1
124 USA Kirkland 70.0100 0 0 1 1
125 USA Lander 558.6700 0 0 1 1
126 USA Portland 341.9500 0 0 1 1
127 USA San Francisco 202.1100 0 0 1 1
128 USA Seattle 1353.0600 0 0 1 1
129 USA Walla Walla 19.4000 0 0 1 1
130 Venezuela Federal Shipping 760.9200 0 0 2 0
131 Venezuela Speedy Express 821.3400 0 0 2 0
132 Venezuela United Package 1152.9200 0 0 2 0
133 Venezuela Barquisimeto 734.4100 0 0 1 1
134 Venezuela Caracas 67.8000 0 0 1 1
135 Venezuela I. de Margarita 673.8100 0 0 1 1
136 Venezuela San Cristóbal 1259.1600 0 0 1 1


3. Usage of GROUPING_ID to Filter Aggregation Levels

SQL Server Query 3

            
SELECT  
c.Country,
c.City,
SUM(o.Freight) AS TotalFreight
FROM Customers c
JOIN Orders o ON c.CustomerID = o.CustomerID
GROUP BY ROLLUP (c.Country, c.City)
HAVING GROUPING_ID(c.Country, c.City) = 1 -- Filter for subtotals by Country
ORDER BY c.Country;

Create SQL query with SqlQueryBuilder 3

            
.Select()  
.Columns("c.Country", "c.City")
.Column(new SUM(new Column("o.Freight")), "TotalFreight")
.From("Customers", "c")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Orders", "o")
.On(new Column("c.CustomerID").Equale(new Column("o.CustomerID")))
})
.GroupBy(new GroupBy("c.Country", "c.City").WithRollUp())
.Having(new Having(new GROUPING_ID(new Column("c.Country"), new Column("c.City")).Equale(1)))
.OrderBy(new OrderBy().SetColumnAscending("c.Country"))
.Build();

Query build by SqlQueryBuilder 3

            
SELECT c.Country,
       c.City,
       SUM(o.Freight) AS TotalFreight
FROM Customers AS c
     INNER JOIN
     Orders AS o
     ON c.CustomerID = o.CustomerID
GROUP BY ROLLUP(c.Country, c.City)
HAVING GROUPING_ID(c.Country, c.City) = @pMAIN_2507200130335603160
ORDER BY c.Country ASC;


            
        

Parameters (If used)

Name Value
@pMAIN_2507200130335603160 1

Query Results 3:

  Country City TotalFreight
1 Argentina 598.5800
2 Austria 7391.5000
3 Belgium 1280.1400
4 Brazil 4880.1900
5 Canada 2198.0900
6 Denmark 1396.1900
7 Finland 910.8900
8 France 4237.8400
9 Germany 11283.2800
10 Ireland 2755.2400
11 Italy 864.4400
12 Mexico 1122.7800
13 Norway 275.5000
14 Poland 175.7400
15 Portugal 643.5300
16 Spain 861.8900
17 Sweden 3237.6000
18 Switzerland 1368.5300
19 UK 2954.2700
20 USA 13771.2900
21 Venezuela 2735.1800


4. Usage of GROUPING_ID with CASE Statements for Clarity

SQL Server Query 4

            
SELECT  
CASE GROUPING_ID(c.Country, c.City)
WHEN 0 THEN 'Total for City'
WHEN 1 THEN 'Subtotal for Country'
WHEN 3 THEN 'Grand Total'
ELSE 'Unknown'
END AS AggregationLevel,
c.Country,
c.City,
SUM(o.Freight) AS TotalFreight
FROM Customers c
JOIN Orders o ON c.CustomerID = o.CustomerID
GROUP BY ROLLUP (c.Country, c.City)
ORDER BY GROUPING_ID(c.Country, c.City), c.Country, c.City;

Create SQL query with SqlQueryBuilder 4

            
var (sql4, parameters4) = new SqlQueryBuilder()  
.Select()
.Column(new CASE(new GROUPING_ID(new Column("c.Country"), new Column("c.City")))
.When(0).Then("Total for City")
.When(1).Then("Subtotal for Country")
.When(3).Then("Grand Total")
.Else("Unknown")
, "AggregationLevel")
.Columns("c.Country", "c.City")
.Column(new SUM(new Column("o.Freight")), "TotalFreight")
.From("Customers", "c")
.Join(new List<IJoin>()
{
new INNERJOIN().TableName("Orders", "o")
.On(new Column("c.CustomerID").Equale(new Column("o.CustomerID")))
})
.GroupBy(new GroupBy("c.Country", "c.City").WithRollUp())
.OrderBy(new OrderBy().Set(new GROUPING_ID(new Column("c.Country"), new Column("c.City")))
.SetColumnAscending("c.Country")
.SetColumnAscending("c.City"))
.Build();

Query build by SqlQueryBuilder 4

            
SELECT CASE GROUPING_ID(c.Country, c.City) WHEN @pMAIN_2507200130335731180 THEN @pMAIN_2507200130335731181 WHEN @pMAIN_2507200130335731182 THEN @pMAIN_2507200130335731183 WHEN @pMAIN_2507200130335731184 THEN @pMAIN_2507200130335731185 ELSE @pMAIN_2507200130335731186 END AS AggregationLevel,
       c.Country,
       c.City,
       SUM(o.Freight) AS TotalFreight
FROM Customers AS c
     INNER JOIN
     Orders AS o
     ON c.CustomerID = o.CustomerID
GROUP BY ROLLUP(c.Country, c.City)
ORDER BY GROUPING_ID(c.Country, c.City) ASC, c.Country ASC, c.City ASC;


            
        

Parameters (If used)

Name Value
@pMAIN_2507200130335731180 0
@pMAIN_2507200130335731181 Total for City
@pMAIN_2507200130335731182 1
@pMAIN_2507200130335731183 Subtotal for Country
@pMAIN_2507200130335731184 3
@pMAIN_2507200130335731185 Grand Total
@pMAIN_2507200130335731186 Unknown

Query Results 4:

  AggregationLevel Country City TotalFreight
1 Total for City Argentina Buenos Aires 598.5800
2 Total for City Austria Graz 6205.3900
3 Total for City Austria Salzburg 1186.1100
4 Total for City Belgium Bruxelles 458.9100
5 Total for City Belgium Charleroi 821.2300
6 Total for City Brazil Campinas 322.3800
7 Total for City Brazil Resende 194.7100
8 Total for City Brazil Rio de Janeiro 1685.2700
9 Total for City Brazil Sao Paulo 2677.8300
10 Total for City Canada Montréal 1394.2200
11 Total for City Canada Tsawassen 793.9500
12 Total for City Canada Vancouver 9.9200
13 Total for City Denmark Århus 947.3400
14 Total for City Denmark Kobenhavn 448.8500
15 Total for City Finland Helsinki 88.4100
16 Total for City Finland Oulu 822.4800
17 Total for City France Lille 637.9400
18 Total for City France Lyon 493.2500
19 Total for City France Marseille 1357.8700
20 Total for City France Nantes 235.1200
21 Total for City France Paris 108.2800
22 Total for City France Reims 58.4100
23 Total for City France Strasbourg 623.6600
24 Total for City France Toulouse 635.8200
25 Total for City France Versailles 87.4900
26 Total for City Germany Aachen 306.0400
27 Total for City Germany Berlin 225.5800
28 Total for City Germany Brandenburg 813.6800
29 Total for City Germany Cunewalde 5605.6300
30 Total for City Germany Frankfurt a.M. 1017.0300
31 Total for City Germany Köln 862.7400
32 Total for City Germany Leipzig 322.0400
33 Total for City Germany Mannheim 168.2600
34 Total for City Germany München 1403.4400
35 Total for City Germany Münster 125.9700
36 Total for City Germany Stuttgart 432.8700
37 Total for City Ireland Cork 2755.2400
38 Total for City Italy Bergamo 469.7500
39 Total for City Italy Reggio Emilia 319.5600
40 Total for City Italy Torino 75.1300
41 Total for City Mexico México D.F. 1122.7800
42 Total for City Norway Stavern 275.5000
43 Total for City Poland Warszawa 175.7400
44 Total for City Portugal Lisboa 643.5300
45 Total for City Spain Barcelona 37.9800
46 Total for City Spain Madrid 255.6400
47 Total for City Spain Sevilla 568.2700
48 Total for City Sweden Bräcke 1678.0800
49 Total for City Sweden Luleå 1559.5200
50 Total for City Switzerland Bern 367.2400
51 Total for City Switzerland Genève 1001.2900
52 Total for City UK Cowes 363.6500
53 Total for City UK London 2590.6200
54 Total for City USA Albuquerque 2134.2100
55 Total for City USA Anchorage 983.5300
56 Total for City USA Boise 6683.7000
57 Total for City USA Butte 129.9600
58 Total for City USA Elgin 207.0800
59 Total for City USA Eugene 1087.6100
60 Total for City USA Kirkland 70.0100
61 Total for City USA Lander 558.6700
62 Total for City USA Portland 341.9500
63 Total for City USA San Francisco 202.1100
64 Total for City USA Seattle 1353.0600
65 Total for City USA Walla Walla 19.4000
66 Total for City Venezuela Barquisimeto 734.4100
67 Total for City Venezuela Caracas 67.8000
68 Total for City Venezuela I. de Margarita 673.8100
69 Total for City Venezuela San Cristóbal 1259.1600
70 Subtotal for Country Argentina 598.5800
71 Subtotal for Country Austria 7391.5000
72 Subtotal for Country Belgium 1280.1400
73 Subtotal for Country Brazil 4880.1900
74 Subtotal for Country Canada 2198.0900
75 Subtotal for Country Denmark 1396.1900
76 Subtotal for Country Finland 910.8900
77 Subtotal for Country France 4237.8400
78 Subtotal for Country Germany 11283.2800
79 Subtotal for Country Ireland 2755.2400
80 Subtotal for Country Italy 864.4400
81 Subtotal for Country Mexico 1122.7800
82 Subtotal for Country Norway 275.5000
83 Subtotal for Country Poland 175.7400
84 Subtotal for Country Portugal 643.5300
85 Subtotal for Country Spain 861.8900
86 Subtotal for Country Sweden 3237.6000
87 Subtotal for Country Switzerland 1368.5300
88 Subtotal for Country UK 2954.2700
89 Subtotal for Country USA 13771.2900
90 Subtotal for Country Venezuela 2735.1800
91 Grand Total 64942.6900