pgr_kruskalBFS¶
pgr_kruskalBFS
— Prim algorithm for Minimum Spanning Tree with Depth First
Search ordering.
Availability
Version 3.0.0
New Official function
Description¶
Visits and extracts the nodes information in Breath First Search ordering of the Minimum Spanning Tree created using Prims’s algorithm.
The main Characteristics are:
It’s implementation is only on undirected graph.
Process is done only on edges with positive costs.
The total weight of all the edges in the tree or forest is minimized.
When the graph is connected
The resulting edges make up a tree
When the graph is not connected,
Finds a minimum spanning tree for each connected component.
The resulting edges make up a forest.
Kruskal’s running time: \(O(E * log E)\)
Returned tree nodes from a root vertex are on Breath First Search order
Breath First Search Running time: \(O(E + V)\)
Signatures¶
pgr_kruskalBFS(Edges SQL, Root vid [, max_depth])
pgr_kruskalBFS(Edges SQL, Root vids [, max_depth])
RETURNS SET OF (seq, depth, start_vid, node, edge, cost, agg_cost)
Single vertex¶
pgr_kruskalBFS(Edges SQL, Root vid [, max_depth])
RETURNS SET OF (seq, depth, start_vid, node, edge, cost, agg_cost)
- Example
The Minimum Spanning Tree having as root vertex \(2\)
SELECT * FROM pgr_kruskalBFS(
'SELECT id, source, target, cost, reverse_cost FROM edge_table ORDER BY id',
2
);
seq | depth | start_vid | node | edge | cost | agg_cost
-----+-------+-----------+------+------+------+----------
1 | 0 | 2 | 2 | -1 | 0 | 0
2 | 1 | 2 | 1 | 1 | 1 | 1
3 | 1 | 2 | 3 | 2 | 1 | 1
4 | 2 | 2 | 4 | 3 | 1 | 2
5 | 3 | 2 | 9 | 16 | 1 | 3
6 | 4 | 2 | 12 | 15 | 1 | 4
7 | 5 | 2 | 11 | 13 | 1 | 5
8 | 6 | 2 | 6 | 11 | 1 | 6
9 | 6 | 2 | 10 | 12 | 1 | 6
10 | 7 | 2 | 5 | 10 | 1 | 7
11 | 7 | 2 | 13 | 14 | 1 | 7
12 | 8 | 2 | 8 | 7 | 1 | 8
13 | 9 | 2 | 7 | 6 | 1 | 9
(13 rows)
Multiple vertices¶
pgr_kruskalBFS(Edges SQL, Root vids [, max_depth])
RETURNS SET OF (seq, depth, start_vid, node, edge, cost, agg_cost)
- Example
The Minimum Spanning Tree starting on vertices \(\{13, 2\}\) with \(depth <= 3\)
SELECT * FROM pgr_kruskalBFS(
'SELECT id, source, target, cost, reverse_cost FROM edge_table ORDER BY id',
ARRAY[13,2], max_depth := 3
);
seq | depth | start_vid | node | edge | cost | agg_cost
-----+-------+-----------+------+------+------+----------
1 | 0 | 2 | 2 | -1 | 0 | 0
2 | 1 | 2 | 1 | 1 | 1 | 1
3 | 1 | 2 | 3 | 2 | 1 | 1
4 | 2 | 2 | 4 | 3 | 1 | 2
5 | 3 | 2 | 9 | 16 | 1 | 3
6 | 0 | 13 | 13 | -1 | 0 | 0
7 | 1 | 13 | 10 | 14 | 1 | 1
8 | 2 | 13 | 5 | 10 | 1 | 2
9 | 2 | 13 | 11 | 12 | 1 | 2
10 | 3 | 13 | 8 | 7 | 1 | 3
11 | 3 | 13 | 6 | 11 | 1 | 3
12 | 3 | 13 | 12 | 13 | 1 | 3
(12 rows)
Parameters¶
Parameter |
Type |
Description |
---|---|---|
Edges SQL |
|
SQL query described in Inner query. |
Root vid |
|
Identifier of the root vertex of the tree.
|
Root vids |
|
Array of identifiers of the root vertices.
|
Optional Parameters¶
Parameter |
Type |
Default |
Description |
---|---|---|---|
max_depth |
|
\(9223372036854775807\) |
Upper limit for depth of node in the tree
|
Inner query¶
Column |
Type |
Default |
Description |
---|---|---|---|
id |
|
Identifier of the edge. |
|
source |
|
Identifier of the first end point vertex of the edge. |
|
target |
|
Identifier of the second end point vertex of the edge. |
|
cost |
|
Weight of the edge (source, target)
|
|
reverse_cost |
|
-1 |
Weight of the edge (target, source),
|
Where:
- ANY-INTEGER
SMALLINT, INTEGER, BIGINT
- ANY-NUMERICAL
SMALLINT, INTEGER, BIGINT, REAL, FLOAT
Result Columns¶
Returns SET OF (seq, depth, start_vid, node, edge, cost, agg_cost)
Column |
Type |
Description |
---|---|---|
seq |
|
Sequential value starting from \(1\). |
depth |
|
Depth of the
|
start_vid |
|
Identifier of the root vertex.
|
node |
|
Identifier of |
edge |
|
Identifier of the
|
cost |
|
Cost to traverse |
agg_cost |
|
Aggregate cost from |
See Also¶
The queries use the Sample Data network.
Indices and tables