pgr_binaryBreadthFirstSearch — Returns the shortest path(s) in a binary graph.

Any graph whose edge-weights belongs to the set {0,X}, where ‘X’ is any non-negative integer, is termed as a ‘binary graph’.

Warning

Possible server crash

• These functions might create a server crash

Warning

Experimental functions

• They are not officially of the current release.

• They likely will not be officially be part of the next release:

• The functions might not make use of ANY-INTEGER and ANY-NUMERICAL

• Name might change.

• Signature might change.

• Functionality might change.

• pgTap tests might be missing.

• Might need c/c++ coding.

• May lack documentation.

• Documentation if any might need to be rewritten.

• Documentation examples might need to be automatically generated.

• Might need a lot of feedback from the comunity.

• Might depend on a proposed function of pgRouting

• Might depend on a deprecated function of pgRouting

Availability

• Version 3.2.0

• New experimental signature:

• Version 3.0.0

## Description¶

It is well-known that the shortest paths between a single source and all other vertices can be found using Breadth First Search in $$O(|E|)$$ in an unweighted graph, i.e. the distance is the minimal number of edges that you need to traverse from the source to another vertex. We can interpret such a graph also as a weighted graph, where every edge has the weight $$1$$. If not alledges in graph have the same weight, that we need a more general algorithm, like Dijkstra’s Algorithm which runs in $$O(|E|log|V|)$$ time.

However if the weights are more constrained, we can use a faster algorithm. This algorithm, termed as ‘Binary Breadth First Search’ as well as ‘0-1 BFS’, is a variation of the standard Breadth First Search problem to solve the SSSP (single-source shortest path) problem in $$O(|E|)$$, if the weights of each edge belongs to the set {0,X}, where ‘X’ is any non-negative real integer.

The main Characteristics are:

• Process is done only on ‘binary graphs’. (‘Binary Graph’: Any graph whose edge-weights belongs to the set {0,X}, where ‘X’ is any non-negative real integer.)

• For optimization purposes, any duplicated value in the start_vids or end_vids are ignored.

• The returned values are ordered:

• start_vid ascending

• end_vid ascending

• Running time: $$O(| start\_vids | * |E|)$$

## Signatures¶

Summary

pgr_binaryBreadthFirstSearch(Edges SQL, start vid, end vid, [directed])
pgr_binaryBreadthFirstSearch(Edges SQL, start vid, end vids, [directed])
pgr_binaryBreadthFirstSearch(Edges SQL, start vids, end vid, [directed])
pgr_binaryBreadthFirstSearch(Edges SQL, start vids, end vids, [directed])
RETURNS SET OF (seq, path_seq, [start_vid], [end_vid], node, edge, cost, agg_cost)
OR EMPTY SET

Note: Using the Sample Data Network as all weights are same (i.e $$1`$$)

### One to One¶

pgr_binaryBreadthFirstSearch(Edges SQL, start vid, end vid, [directed])
RETURNS SET OF (seq, path_seq, node, edge, cost, agg_cost)
OR EMPTY SET
Example:

From vertex $$6$$ to vertex $$10$$ on a directed graph

'SELECT id, source, target, cost, reverse_cost from edges',
6, 10, true);
seq | path_seq | node | edge | cost | agg_cost
-----+----------+------+------+------+----------
1 |        1 |    6 |    4 |    1 |        0
2 |        2 |    7 |    8 |    1 |        1
3 |        3 |   11 |    9 |    1 |        2
4 |        4 |   16 |   16 |    1 |        3
5 |        5 |   15 |    3 |    1 |        4
6 |        6 |   10 |   -1 |    0 |        5
(6 rows)

### One to Many¶

pgr_binaryBreadthFirstSearch(Edges SQL, start vid, end vids, [directed])
RETURNS SET OF (seq, path_seq, end_vid, node, edge, cost, agg_cost)
OR EMPTY SET
Example:

From vertex $$6$$ to vertices $$\{10, 17\}$$ on a directed graph

'SELECT id, source, target, cost, reverse_cost from edges',
6, ARRAY[10, 17]);
seq | path_seq | end_vid | node | edge | cost | agg_cost
-----+----------+---------+------+------+------+----------
1 |        1 |      10 |    6 |    4 |    1 |        0
2 |        2 |      10 |    7 |    8 |    1 |        1
3 |        3 |      10 |   11 |    9 |    1 |        2
4 |        4 |      10 |   16 |   16 |    1 |        3
5 |        5 |      10 |   15 |    3 |    1 |        4
6 |        6 |      10 |   10 |   -1 |    0 |        5
7 |        1 |      17 |    6 |    4 |    1 |        0
8 |        2 |      17 |    7 |    8 |    1 |        1
9 |        3 |      17 |   11 |   11 |    1 |        2
10 |        4 |      17 |   12 |   13 |    1 |        3
11 |        5 |      17 |   17 |   -1 |    0 |        4
(11 rows)

### Many to One¶

pgr_binaryBreadthFirstSearch(Edges SQL, start vids, end vid, [directed])
RETURNS SET OF (seq, path_seq, start_vid, node, edge, cost, agg_cost)
OR EMPTY SET
Example:

From vertices $$\{6, 1\}$$ to vertex $$17$$ on a directed graph

'SELECT id, source, target, cost, reverse_cost from edges',
ARRAY[6, 1], 17);
seq | path_seq | start_vid | node | edge | cost | agg_cost
-----+----------+-----------+------+------+------+----------
1 |        1 |         1 |    1 |    6 |    1 |        0
2 |        2 |         1 |    3 |    7 |    1 |        1
3 |        3 |         1 |    7 |    8 |    1 |        2
4 |        4 |         1 |   11 |   11 |    1 |        3
5 |        5 |         1 |   12 |   13 |    1 |        4
6 |        6 |         1 |   17 |   -1 |    0 |        5
7 |        1 |         6 |    6 |    4 |    1 |        0
8 |        2 |         6 |    7 |    8 |    1 |        1
9 |        3 |         6 |   11 |   11 |    1 |        2
10 |        4 |         6 |   12 |   13 |    1 |        3
11 |        5 |         6 |   17 |   -1 |    0 |        4
(11 rows)

### Many to Many¶

pgr_binaryBreadthFirstSearch(Edges SQL, start vids, end vids, [directed])
RETURNS SET OF (seq, path_seq, start_vid, end_vid, node, edge, cost, agg_cost)
OR EMPTY SET
Example:

From vertices $$\{6, 1\}$$ to vertices $$\{10, 17\}$$ on an undirected graph

'SELECT id, source, target, cost, reverse_cost from edges',
ARRAY[6, 1], ARRAY[10, 17],
directed => false);
seq | path_seq | start_vid | end_vid | node | edge | cost | agg_cost
-----+----------+-----------+---------+------+------+------+----------
1 |        1 |         1 |      10 |    1 |    6 |    1 |        0
2 |        2 |         1 |      10 |    3 |    7 |    1 |        1
3 |        3 |         1 |      10 |    7 |    4 |    1 |        2
4 |        4 |         1 |      10 |    6 |    2 |    1 |        3
5 |        5 |         1 |      10 |   10 |   -1 |    0 |        4
6 |        1 |         1 |      17 |    1 |    6 |    1 |        0
7 |        2 |         1 |      17 |    3 |    7 |    1 |        1
8 |        3 |         1 |      17 |    7 |    8 |    1 |        2
9 |        4 |         1 |      17 |   11 |   11 |    1 |        3
10 |        5 |         1 |      17 |   12 |   13 |    1 |        4
11 |        6 |         1 |      17 |   17 |   -1 |    0 |        5
12 |        1 |         6 |      10 |    6 |    2 |    1 |        0
13 |        2 |         6 |      10 |   10 |   -1 |    0 |        1
14 |        1 |         6 |      17 |    6 |    4 |    1 |        0
15 |        2 |         6 |      17 |    7 |    8 |    1 |        1
16 |        3 |         6 |      17 |   11 |   11 |    1 |        2
17 |        4 |         6 |      17 |   12 |   13 |    1 |        3
18 |        5 |         6 |      17 |   17 |   -1 |    0 |        4
(18 rows)

### Combinations¶

RETURNS SET OF (seq, path_seq, start_vid, end_vid, node, edge, cost, agg_cost)
OR EMPTY SET
Example:

Using a combinations table on an undirected graph

The combinations table:

SELECT source, target FROM combinations;
source | target
--------+--------
5 |      6
5 |     10
6 |      5
6 |     15
6 |     14
(5 rows)

The query:

'SELECT id, source, target, cost, reverse_cost FROM edges',
'SELECT source, target FROM combinations',
false);
seq | path_seq | start_vid | end_vid | node | edge | cost | agg_cost
-----+----------+-----------+---------+------+------+------+----------
1 |        1 |         5 |       6 |    5 |    1 |    1 |        0
2 |        2 |         5 |       6 |    6 |   -1 |    0 |        1
3 |        1 |         5 |      10 |    5 |    1 |    1 |        0
4 |        2 |         5 |      10 |    6 |    2 |    1 |        1
5 |        3 |         5 |      10 |   10 |   -1 |    0 |        2
6 |        1 |         6 |       5 |    6 |    1 |    1 |        0
7 |        2 |         6 |       5 |    5 |   -1 |    0 |        1
8 |        1 |         6 |      15 |    6 |    2 |    1 |        0
9 |        2 |         6 |      15 |   10 |    3 |    1 |        1
10 |        3 |         6 |      15 |   15 |   -1 |    0 |        2
(10 rows)

## Parameters¶

Column

Type

Description

Edges SQL

TEXT

Edges SQL as described below

Combinations SQL

TEXT

Combinations SQL as described below

start vid

BIGINT

Identifier of the starting vertex of the path.

start vids

ARRAY[BIGINT]

Array of identifiers of starting vertices.

end vid

BIGINT

Identifier of the ending vertex of the path.

end vids

ARRAY[BIGINT]

Array of identifiers of ending vertices.

## Optional Parameters¶

Column

Type

Default

Description

directed

BOOLEAN

true

• When true the graph is considered Directed

• When false the graph is considered as Undirected.

## Inner Queries¶

### Edges SQL¶

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)

• When negative: edge (target, source) does not exist, therefore it’s not part of the graph.

Where:

ANY-INTEGER:

SMALLINT, INTEGER, BIGINT

ANY-NUMERICAL:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

### Combinations SQL¶

Parameter

Type

Description

source

ANY-INTEGER

Identifier of the departure vertex.

target

ANY-INTEGER

Identifier of the arrival vertex.

Where:

ANY-INTEGER:

SMALLINT, INTEGER, BIGINT

## Result Columns¶

Set of (seq, path_id, path_seq [, start_vid] [, end_vid], node, edge, cost, agg_cost)

Column

Type

Description

seq

INTEGER

Sequential value starting from 1.

path_id

INTEGER

Path identifier.

• Has value 1 for the first of a path from start_vid to end_vid.

path_seq

INTEGER

Relative position in the path. Has value 1 for the beginning of a path.

start_vid

BIGINT

Identifier of the starting vertex. Returned when multiple starting vetrices are in the query.

end_vid

BIGINT

Identifier of the ending vertex. Returned when multiple ending vertices are in the query.

node

BIGINT

Identifier of the node in the path from start_vid to end_vid.

edge

BIGINT

Identifier of the edge used to go from node to the next node in the path sequence. -1 for the last node of the path.

cost

FLOAT

Cost to traverse from node using edge to the next node in the path sequence.

agg_cost

FLOAT

Aggregate cost from start_vid to node.

Example:

Manually assigned vertex combinations.

'SELECT id, source, target, cost, reverse_cost FROM edges',
'SELECT * FROM (VALUES (6, 10), (6, 7), (12, 10)) AS combinations (source, target)');
seq | path_seq | start_vid | end_vid | node | edge | cost | agg_cost
-----+----------+-----------+---------+------+------+------+----------
1 |        1 |         6 |       7 |    6 |    4 |    1 |        0
2 |        2 |         6 |       7 |    7 |   -1 |    0 |        1
3 |        1 |         6 |      10 |    6 |    4 |    1 |        0
4 |        2 |         6 |      10 |    7 |    8 |    1 |        1
5 |        3 |         6 |      10 |   11 |    9 |    1 |        2
6 |        4 |         6 |      10 |   16 |   16 |    1 |        3
7 |        5 |         6 |      10 |   15 |    3 |    1 |        4
8 |        6 |         6 |      10 |   10 |   -1 |    0 |        5
9 |        1 |        12 |      10 |   12 |   13 |    1 |        0
10 |        2 |        12 |      10 |   17 |   15 |    1 |        1
11 |        3 |        12 |      10 |   16 |   16 |    1 |        2
12 |        4 |        12 |      10 |   15 |    3 |    1 |        3
13 |        5 |        12 |      10 |   10 |   -1 |    0 |        4
(13 rows)