pgr_drivingDistance - Returns the driving distance from a start node.
Boost Graph Inside
Availability
Using Dijkstra algorithm, extracts all the nodes that have costs less than or equal to the value distance.
The edges extracted will conform the corresponding spanning tree.
pgr_drivingDistance(edges_sql, start_vid, distance)
pgr_drivingDistance(edges_sql, start_vid, distance, directed)
pgr_drivingDistance(edges_sql, start_vids, distance, directed, equicost)
RETURNS SET OF (seq, [start_vid,] node, edge, cost, agg_cost)
pgr_drivingDistance(edges_sql, start_vid, distance)
RETURNS SET OF (seq, node, edge, cost, agg_cost)
pgr_drivingDistance(edges_sql, start_vid, distance, directed)
RETURNS SET OF (seq, node, edge, cost, agg_cost)
pgr_drivingDistance(edges_sql, start_vids, distance, directed, equicost)
RETURNS SET OF (seq, start_vid, node, edge, cost, agg_cost)
| edges_sql: | an SQL query, which should return a set of rows with the following columns: |
|---|
| Column | Type | Default | Description |
|---|---|---|---|
| id | ANY-INTEGER |
Identifier of the edge. | |
| source | ANY-INTEGER |
Identifier of the first end point vertex of the edge. | |
| target | ANY-INTEGER |
Identifier of the second end point vertex of the edge. | |
| cost | ANY-NUMERICAL |
Weight of the edge (source, target)
|
|
| reverse_cost | ANY-NUMERICAL |
-1 | Weight of the edge (target, source),
|
Where:
| ANY-INTEGER: | SMALLINT, INTEGER, BIGINT |
|---|---|
| ANY-NUMERICAL: | SMALLINT, INTEGER, BIGINT, REAL, FLOAT |
| Column | Type | Description |
|---|---|---|
| edges_sql | TEXT |
SQL query as described above. |
| start_vid | BIGINT |
Identifier of the starting vertex. |
| start_vids | ARRAY[ANY-INTEGER] |
Array of identifiers of starting vertices. |
| distance | FLOAT |
Upper limit for the inclusion of the node in the result. |
| directed | BOOLEAN |
(optional). When false the graph is considered as Undirected. Default is true which considers the graph as Directed. |
| equicost | BOOLEAN |
(optional). When true the node will only appear in the closest start_vid list. Default is false which resembles several calls using the single starting point signatures. Tie brakes are arbitrarely. |
Returns set of (seq [, start_v], node, edge, cost, agg_cost)
| Column | Type | Description |
|---|---|---|
| seq | INTEGER |
Sequential value starting from 1. |
| start_vid | INTEGER |
Identifier of the starting vertex. |
| node | BIGINT |
Identifier of the node in the path within the limits from start_vid. |
| edge | BIGINT |
Identifier of the edge used to arrive to node. 0 when the node is the start_vid. |
| cost | FLOAT |
Cost to traverse edge. |
| agg_cost | FLOAT |
Aggregate cost from start_vid to node. |
directed with cost and reverse_cost columns¶The examples in this section use the following Graph 1: Directed, with cost and reverse cost
/*PGR-GNU*****************************************************************
Copyright (c) 2015 pgRouting developers
Mail: project@pgrouting.org
------
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it under the terms of the GNU General Public License as published by
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but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
********************************************************************PGR-GNU*/
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
2, 3
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 2 | -1 | 0 | 0
2 | 1 | 1 | 1 | 1
3 | 5 | 4 | 1 | 1
4 | 6 | 8 | 1 | 2
5 | 8 | 7 | 1 | 2
6 | 10 | 10 | 1 | 2
7 | 7 | 6 | 1 | 3
8 | 9 | 9 | 1 | 3
9 | 11 | 12 | 1 | 3
10 | 13 | 14 | 1 | 3
(10 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
13, 3
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 13 | -1 | 0 | 0
2 | 10 | 14 | 1 | 1
3 | 5 | 10 | 1 | 2
4 | 11 | 12 | 1 | 2
5 | 2 | 4 | 1 | 3
6 | 6 | 8 | 1 | 3
7 | 8 | 7 | 1 | 3
8 | 12 | 13 | 1 | 3
(8 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
array[2,13], 3
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 1 | 1 | 1 | 1
3 | 2 | 5 | 4 | 1 | 1
4 | 2 | 6 | 8 | 1 | 2
5 | 2 | 8 | 7 | 1 | 2
6 | 2 | 10 | 10 | 1 | 2
7 | 2 | 7 | 6 | 1 | 3
8 | 2 | 9 | 9 | 1 | 3
9 | 2 | 11 | 12 | 1 | 3
10 | 2 | 13 | 14 | 1 | 3
11 | 13 | 13 | -1 | 0 | 0
12 | 13 | 10 | 14 | 1 | 1
13 | 13 | 5 | 10 | 1 | 2
14 | 13 | 11 | 12 | 1 | 2
15 | 13 | 2 | 4 | 1 | 3
16 | 13 | 6 | 8 | 1 | 3
17 | 13 | 8 | 7 | 1 | 3
18 | 13 | 12 | 13 | 1 | 3
(18 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
array[2,13], 3, equicost:=true
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 1 | 1 | 1 | 1
3 | 2 | 5 | 4 | 1 | 1
4 | 2 | 6 | 8 | 1 | 2
5 | 2 | 8 | 7 | 1 | 2
6 | 2 | 7 | 6 | 1 | 3
7 | 2 | 9 | 9 | 1 | 3
8 | 13 | 13 | -1 | 0 | 0
9 | 13 | 10 | 14 | 1 | 1
10 | 13 | 11 | 12 | 1 | 2
11 | 13 | 12 | 13 | 1 | 3
(11 rows)
undirected with cost and reverse_cost columns¶The examples in this section use the following Graph 2: Undirected, with cost and reverse cost
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
2, 3, false
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 2 | -1 | 0 | 0
2 | 1 | 1 | 1 | 1
3 | 3 | 2 | 1 | 1
4 | 5 | 4 | 1 | 1
5 | 4 | 3 | 1 | 2
6 | 6 | 8 | 1 | 2
7 | 8 | 7 | 1 | 2
8 | 10 | 10 | 1 | 2
9 | 7 | 6 | 1 | 3
10 | 9 | 16 | 1 | 3
11 | 11 | 12 | 1 | 3
12 | 13 | 14 | 1 | 3
(12 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
13, 3, false
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 13 | -1 | 0 | 0
2 | 10 | 14 | 1 | 1
3 | 5 | 10 | 1 | 2
4 | 11 | 12 | 1 | 2
5 | 2 | 4 | 1 | 3
6 | 6 | 8 | 1 | 3
7 | 8 | 7 | 1 | 3
8 | 12 | 13 | 1 | 3
(8 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
array[2,13], 3, false
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 1 | 1 | 1 | 1
3 | 2 | 3 | 2 | 1 | 1
4 | 2 | 5 | 4 | 1 | 1
5 | 2 | 4 | 3 | 1 | 2
6 | 2 | 6 | 8 | 1 | 2
7 | 2 | 8 | 7 | 1 | 2
8 | 2 | 10 | 10 | 1 | 2
9 | 2 | 7 | 6 | 1 | 3
10 | 2 | 9 | 16 | 1 | 3
11 | 2 | 11 | 12 | 1 | 3
12 | 2 | 13 | 14 | 1 | 3
13 | 13 | 13 | -1 | 0 | 0
14 | 13 | 10 | 14 | 1 | 1
15 | 13 | 5 | 10 | 1 | 2
16 | 13 | 11 | 12 | 1 | 2
17 | 13 | 2 | 4 | 1 | 3
18 | 13 | 6 | 8 | 1 | 3
19 | 13 | 8 | 7 | 1 | 3
20 | 13 | 12 | 13 | 1 | 3
(20 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost, reverse_cost FROM edge_table',
array[2,13], 3, false, equicost:=true
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 1 | 1 | 1 | 1
3 | 2 | 3 | 2 | 1 | 1
4 | 2 | 5 | 4 | 1 | 1
5 | 2 | 4 | 3 | 1 | 2
6 | 2 | 6 | 8 | 1 | 2
7 | 2 | 8 | 7 | 1 | 2
8 | 2 | 7 | 6 | 1 | 3
9 | 2 | 9 | 16 | 1 | 3
10 | 13 | 13 | -1 | 0 | 0
11 | 13 | 10 | 14 | 1 | 1
12 | 13 | 11 | 12 | 1 | 2
13 | 13 | 12 | 13 | 1 | 3
(13 rows)
directed with cost column¶The examples in this section use the following Graph 3: Directed, with cost
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
2, 3
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 2 | -1 | 0 | 0
2 | 5 | 4 | 1 | 1
3 | 6 | 8 | 1 | 2
4 | 10 | 10 | 1 | 2
5 | 9 | 9 | 1 | 3
6 | 11 | 11 | 1 | 3
7 | 13 | 14 | 1 | 3
(7 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
13, 3
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 13 | -1 | 0 | 0
(1 row)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
array[2,13], 3
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 5 | 4 | 1 | 1
3 | 2 | 6 | 8 | 1 | 2
4 | 2 | 10 | 10 | 1 | 2
5 | 2 | 9 | 9 | 1 | 3
6 | 2 | 11 | 11 | 1 | 3
7 | 2 | 13 | 14 | 1 | 3
8 | 13 | 13 | -1 | 0 | 0
(8 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
array[2,13], 3, equicost:=true
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 5 | 4 | 1 | 1
3 | 2 | 6 | 8 | 1 | 2
4 | 2 | 10 | 10 | 1 | 2
5 | 2 | 9 | 9 | 1 | 3
6 | 2 | 11 | 11 | 1 | 3
7 | 13 | 13 | -1 | 0 | 0
(7 rows)
undirected with cost column¶The examples in this section use the following Graph 4: Undirected, with cost
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
2, 3, false
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 2 | -1 | 0 | 0
2 | 1 | 1 | 1 | 1
3 | 5 | 4 | 1 | 1
4 | 6 | 8 | 1 | 2
5 | 8 | 7 | 1 | 2
6 | 10 | 10 | 1 | 2
7 | 3 | 5 | 1 | 3
8 | 7 | 6 | 1 | 3
9 | 9 | 9 | 1 | 3
10 | 11 | 12 | 1 | 3
11 | 13 | 14 | 1 | 3
(11 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
13, 3, false
);
seq | node | edge | cost | agg_cost
-----+------+------+------+----------
1 | 13 | -1 | 0 | 0
2 | 10 | 14 | 1 | 1
3 | 5 | 10 | 1 | 2
4 | 11 | 12 | 1 | 2
5 | 2 | 4 | 1 | 3
6 | 6 | 8 | 1 | 3
7 | 8 | 7 | 1 | 3
8 | 12 | 13 | 1 | 3
(8 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
array[2,13], 3, false
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 1 | 1 | 1 | 1
3 | 2 | 5 | 4 | 1 | 1
4 | 2 | 6 | 8 | 1 | 2
5 | 2 | 8 | 7 | 1 | 2
6 | 2 | 10 | 10 | 1 | 2
7 | 2 | 3 | 5 | 1 | 3
8 | 2 | 7 | 6 | 1 | 3
9 | 2 | 9 | 9 | 1 | 3
10 | 2 | 11 | 12 | 1 | 3
11 | 2 | 13 | 14 | 1 | 3
12 | 13 | 13 | -1 | 0 | 0
13 | 13 | 10 | 14 | 1 | 1
14 | 13 | 5 | 10 | 1 | 2
15 | 13 | 11 | 12 | 1 | 2
16 | 13 | 2 | 4 | 1 | 3
17 | 13 | 6 | 8 | 1 | 3
18 | 13 | 8 | 7 | 1 | 3
19 | 13 | 12 | 13 | 1 | 3
(19 rows)
SELECT * FROM pgr_drivingDistance(
'SELECT id, source, target, cost FROM edge_table',
array[2,13], 3, false, equicost:=true
);
seq | from_v | node | edge | cost | agg_cost
-----+--------+------+------+------+----------
1 | 2 | 2 | -1 | 0 | 0
2 | 2 | 1 | 1 | 1 | 1
3 | 2 | 5 | 4 | 1 | 1
4 | 2 | 6 | 8 | 1 | 2
5 | 2 | 8 | 7 | 1 | 2
6 | 2 | 3 | 5 | 1 | 3
7 | 2 | 7 | 6 | 1 | 3
8 | 2 | 9 | 9 | 1 | 3
9 | 13 | 13 | -1 | 0 | 0
10 | 13 | 10 | 14 | 1 | 1
11 | 13 | 11 | 12 | 1 | 2
12 | 13 | 12 | 13 | 1 | 3
(12 rows)
Indices and tables