# Conceptos de pgRouting¶

Esta es una guía simple que va a través de los pasos básicos para empezar trabajar con pgRouting. Esta guía cubre:

## Graphs¶

### Definición de grafo¶

A graph is an ordered pair $$G = (V ,E)$$ where:

• $$V$$ is a set of vertices, also called nodes.

• $$E \subseteq \{( u, v ) \mid u , v \in V \}$$

There are different kinds of graphs:

• Grafo no dirigido

• $$E \subseteq \{( u, v ) \mid u , v \in V\}$$

• Undirected simple graph

• $$E \subseteq \{( u, v ) \mid u , v \in V, u \neq v\}$$

• Grafo dirigido

• $$E \subseteq \{( u, v ) \mid (u , v) \in (V X V) \}$$

• Directed simple graph

• $$E \subseteq \{( u, v ) \mid (u , v) \in (V X V), u \neq v\}$$

Graphs:

• Do not have geometries.

• Some graph theory problems require graphs to have weights, called cost in pgRouting.

In pgRouting there are several ways to represent a graph on the database:

• With cost

• (id, source, target, cost)

• With cost and reverse_cost

• (id, source, target, cost, reverse_cost)

Donde:

Columna

Descripción

id

Identifier of the edge. Requirement to use the database in a consistent. manner.

source

target

cost

Peso de la arista (source, target):

• Cuando negativo: la arista (source, target) no existe en el grafo.

• cost must exist in the query.

reverse_cost

Peso de la arista (target, source)

• Cuando negativo: la arista (target, source) no existe en el grafo.

The decision of the graph to be directed or undirected is done when executing a pgRouting algorithm.

### Graph with cost¶

The weighted directed graph, $$G_d(V,E)$$:

• Graph data is obtained with a query

SELECT id, source, target, cost FROM edges

• El conjunto de aristas $$E$$

• $$E = \{(source_{id}, target_{id}, cost_{id}) \text{ when } cost_{id} \ge 0 \}$$

• Edges where cost is non negative are part of the graph.

• Conjunto de vértices $$V$$

• $$V = \{source_{id} \cup target_{id}\}$$

• All vertices in source and target are part of the graph.

Grafo dirigido

In a directed graph the edge $$(source_{id}, target_{id}, cost_{id})$$ has directionality: $$source_{id} \rightarrow target_{id}$$

For the following data:

SELECT *
FROM (VALUES (1, 1, 2, 5), (2, 1, 3, -3))
AS t(id, source, target, cost);
id | source | target | cost
----+--------+--------+------
1 |      1 |      2 |    5
2 |      1 |      3 |   -3
(2 rows)



Edge $$2$$ ($$1 \rightarrow 3$$) is not part of the graph.

The data is representing the following graph:

Grafo no dirigido

In an undirected graph the edge $$(source_{id}, target_{id}, cost_{id})$$ does not have directionality: $$source_{id} \frac{\;\;\;\;\;}{} target_{id}$$

• In terms of a directed graph is like having two edges: $$source_{id} \leftrightarrow target_{id}$$

For the following data:

SELECT *
FROM (VALUES (1, 1, 2, 5), (2, 1, 3, -3))
AS t(id, source, target, cost);
id | source | target | cost
----+--------+--------+------
1 |      1 |      2 |    5
2 |      1 |      3 |   -3
(2 rows)



Edge $$2$$ ($$1 \frac{\;\;\;\;\;}{} 3$$) is not part of the graph.

The data is representing the following graph:

### Graph with cost and reverse_cost¶

The weighted directed graph, $$G_d(V,E)$$, is defined by:

• Graph data is obtained with a query

SELECT id, source, target, cost, reverse_cost FROM edges

• The set of edges $$E$$:

• E = \begin{split} \begin{align} & {\{(source_{id}, target_{id}, cost_{id}) \text{ when } cost_{id} >=0 \}} \\ & \cup \\ & {\{(target_{id}, source_{id}, reverse\_cost_{id}) \text{ when } reverse\_cost_{id} >=0 \}} \end{align} \end{split}

• Edges $$(source \rightarrow target)$$ where cost is non negative are part of the graph.

• Edges $$(target \rightarrow source)$$ where reverse_cost is non negative are part of the graph.

• The set of vertices $$V$$:

• $$V = \{source_{id} \cup target_{id}\}$$

• All vertices in source and target are part of the graph.

Grafo dirigido

In a directed graph both edges have directionality

• edge $$(source_{id}, target_{id}, cost_{id})$$ has directionality: $$source_{id} \rightarrow target_{id}$$

• edge $$(target_{id}, source_{id}, reverse\_cost_{id})$$ has directionality: $$target_{id} \rightarrow source_{id}$$

For the following data:

SELECT *
FROM (VALUES (1, 1, 2, 5, 2), (2, 1, 3, -3, 4), (3, 2, 3, 7, -1))
AS t(id, source, target, cost, reverse_cost);
id | source | target | cost | reverse_cost
----+--------+--------+------+--------------
1 |      1 |      2 |    5 |            2
2 |      1 |      3 |   -3 |            4
3 |      2 |      3 |    7 |           -1
(3 rows)



Edges not part of the graph:

• $$2$$ ($$1 \rightarrow 3$$)

• $$3$$ ($$3 \rightarrow 2$$)

The data is representing the following graph:

Grafo no dirigido

In a directed graph both edges do not have directionality

• Edge $$(source_{id}, target_{id}, cost_{id})$$ is $$source_{id} \frac{\;\;\;\;\;}{} target_{id}$$

• Edge $$(target_{id}, source_{id}, reverse\_cost_{id})$$ is $$target_{id} \frac{\;\;\;\;\;}{} source_{id}$$

• In terms of a directed graph is like having four edges:

• $$source_i \leftrightarrow target_i$$

• $$target_i \leftrightarrow source_i$$

For the following data:

SELECT *
FROM (VALUES (1, 1, 2, 5, 2), (2, 1, 3, -3, 4), (3, 2, 3, 7, -1))
AS t(id, source, target, cost, reverse_cost);
id | source | target | cost | reverse_cost
----+--------+--------+------+--------------
1 |      1 |      2 |    5 |            2
2 |      1 |      3 |   -3 |            4
3 |      2 |      3 |    7 |           -1
(3 rows)



Edges not part of the graph:

• $$2$$ ($$1 \frac{\;\;\;\;\;}{} 3$$)

• $$3$$ ($$3 \frac{\;\;\;\;\;}{} 2$$)

The data is representing the following graph:

## Graphs without geometries¶

Personal relationships, genealogy, file dependency problems can be solved using pgRouting. Those problems, normally, do not come with geometries associated with the graph.

### Ejemplo de Wiki¶

Solve the example problem taken from wikipedia):

Donde:

• Problem is to find the shortest path from $$1$$ to $$5$$.

• Is an undirected graph.

• Although visually looks like to have geometries, the drawing is not to scale.

• No geometries associated to the vertices or edges

• Has 6 vertices $$\{1,2,3,4,5,6\}$$

• Has 9 edges:

\begin{split} \begin{align} E = & \{(1,2,7), (1,3,9), (1,6,14), \\ & (2,3,10), (2,4,13), \\ & (3,4,11), (3,6,2), \\ & (4,5,6), \\ & (5,6,9) \} \end{align} \end{split}

• The graph can be represented in many ways for example:

#### Prepare the database¶

Create a database for the example, access the database and install pgRouting:

$createdb wiki$ psql wiki
wiki =# CREATE EXTENSION pgRouting CASCADE;


#### Crear una tabla¶

The basic elements needed to perform basic routing on an undirected graph are:

Columna

Tipo

Descripción

id

ENTEROS

source

ENTEROS

Identificador del primer vértice de la arista.

target

ENTEROS

Identificador del segundo vértice de la arista.

cost

FLOTANTES

Peso de la arista (source, target)

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

Using this table design for this example:

CREATE TABLE wiki (
id SERIAL,
source INTEGER,
target INTEGER,
cost INTEGER);
CREATE TABLE


#### Insert the data¶

INSERT INTO wiki (source, target, cost) VALUES
(1, 2, 7),  (1, 3, 9), (1, 6, 14),
(2, 3, 10), (2, 4, 15),
(3, 6, 2),  (3, 4, 11),
(4, 5, 6),
(5, 6, 9);
INSERT 0 9


#### Find the shortest path¶

To solve this example pgr_dijkstra is used:

SELECT * FROM pgr_dijkstra(
'SELECT id, source, target, cost FROM wiki',
1, 5, false);
seq | path_seq | node | edge | cost | agg_cost
-----+----------+------+------+------+----------
1 |        1 |    1 |    2 |    9 |        0
2 |        2 |    3 |    6 |    2 |        9
3 |        3 |    6 |    9 |    9 |       11
4 |        4 |    5 |   -1 |    0 |       20
(4 rows)



To go from $$1$$ to $$5$$ the path goes thru the following vertices: $$1 \rightarrow 3 \rightarrow 6 \rightarrow 5$$

#### Información de vertices¶

To obtain the vertices information, use pgr_extractVertices – Propuesto

SELECT id, in_edges, out_edges
FROM pgr_extractVertices('SELECT id, source, target FROM wiki');
id | in_edges | out_edges
----+----------+-----------
3 | {2,4}    | {6,7}
5 | {8}      | {9}
4 | {5,7}    | {8}
2 | {1}      | {4,5}
1 |          | {1,2,3}
6 | {3,6,9}  |
(6 rows)



## Graphs with geometries¶

### Crear una Base de Datos de Ruteo¶

The first step is to create a database and load pgRouting in the database.

Typically create a database for each project.

Once having the database to work in, load your data and build the routing application in that database.

createdb sampledata
psql sampledata -c "CREATE EXTENSION pgrouting CASCADE"


### Cargar Datos¶

Existen varias herramientas de codigo abierto que pueden ayudar, como:

shp2pgsql:
• cargador a postgresql de archivos shape

ogr2ogr:
• herramienta de conversión de datos vectoriales

osm2pgsql:
• cargar datos de OSM a postgresql

Tener en cuenta que estas herramientas no importan los datos a una estructura compatible con pgRouting y cuando esto sucede, la topología necesita ser ajustada.

• Breakup a segments on each segment-segment intersection

• When missing, add columns and assign values to source, target, cost, reverse_cost.

• Connect a disconnected graph.

• Create the complete graph topology

• Create one or more graphs based on the application to be developed.

• Create a contracted graph for the high speed roads

• Create graphs per state/country

In few words:

Prepare the graph

What and how to prepare the graph, will depend on the application and/or on the quality of the data and/or on how close the information is to have a topology usable by pgRouting and/or some other factors not mentioned.

The steps to prepare the graph involve geometry operations using PostGIS and some others involve graph operations like pgr_contraction to contract a graph.

The workshop has a step by step on how to prepare a graph using Open Street Map data, for a small application.

• Have the geometries indexed.

• Have the identifiers columns indexed.

Please consult the PostgreSQL documentation and the PostGIS documentation.

### Construir una topología de ruteo¶

The basic information to use the majority of the pgRouting functions id, source, target, cost, [reverse_cost] is what in pgRouting is called the routing topology.

reverse_cost is optional but strongly recommended to have in order to reduce the size of the database due to the size of the geometry columns. Having said that, in this documentation reverse_cost is used in this documentation.

When the data comes with geometries and there is no routing topology, then this step is needed.

All the start and end vertices of the geometries need an identifier that is to be stored in a source and target columns of the table of the data. Likewise, cost and reverse_cost need to have the value of traversing the edge in both directions.

If the columns do not exist they need to be added to the table in question. (see ALTER TABLE)

The function pgr_extractVertices – Propuesto is used to create a vertices table based on the edge identifier and the geometry of the edge of the graph.

Finally using the data stored on the vertices tables the source and target are filled up.

See Datos Muestra for an example for building a topology.

Data coming from OSM and using osm2pgrouting as an import tool, comes with the routing topology. See an example of using osm2pgrouting on the workshop.

For this example the cost and reverse_cost values are going to be the double of the length of the geometry.

#### Update costs to length of geometry¶

Suppose that cost and reverse_cost columns in the sample data represent:

• $$1$$ when the edge exists in the graph

• $$-1$$ when the edge does not exist in the graph

Using that information updating to the length of the geometries:

UPDATE edges SET
cost = sign(cost) * ST_length(geom) * 2,
reverse_cost = sign(reverse_cost) * ST_length(geom) * 2;
UPDATE 18


Which gives the following results:

SELECT id, cost, reverse_cost FROM edges;
id |        cost        |    reverse_cost
----+--------------------+--------------------
6 |                  2 |                  2
7 |                  2 |                  2
4 |                  2 |                  2
5 |                  2 |                 -2
8 |                  2 |                  2
12 |                  2 |                 -2
11 |                  2 |                 -2
10 |                  2 |                  2
17 |     2.999999999998 |     2.999999999998
14 |                  2 |                  2
18 | 3.4000000000000004 | 3.4000000000000004
13 |                  2 |                 -2
15 |                  2 |                  2
16 |                  2 |                  2
9 |                  2 |                  2
3 |                 -2 |                  2
1 |                  2 |                  2
2 |                 -2 |                  2
(18 rows)



Note that to be able to follow the documentation examples, everything is based on the original graph.

Returning to the original data:

UPDATE edges SET
cost = sign(cost),
reverse_cost = sign(reverse_cost);
UPDATE 18


#### Update costs based on codes¶

Other datasets, can have a column with values like

• FT vehicle flow on the direction of the geometry

• TF vehicle flow opposite of the direction of the geometry

• B vehicle flow on both directions

Preparing a code column for the example:

ALTER TABLE edges ADD COLUMN direction TEXT;
ALTER TABLE
UPDATE edges SET
direction = CASE WHEN (cost>0 AND reverse_cost>0) THEN 'B'
WHEN (cost>0 AND reverse_cost<0) THEN 'FT'
WHEN (cost<0 AND reverse_cost>0) THEN 'TF'
ELSE '' END;
UPDATE 18


Adjusting the costs based on the codes:

UPDATE edges SET
cost = CASE WHEN (direction = 'B' OR direction = 'FT')
THEN ST_length(geom) * 2
ELSE -1 END,
reverse_cost = CASE WHEN (direction = 'B' OR direction = 'TF')
THEN ST_length(geom) * 2
ELSE -1 END;
UPDATE 18


Which gives the following results:

SELECT id, cost, reverse_cost FROM edges;
id |        cost        |    reverse_cost
----+--------------------+--------------------
6 |                  2 |                  2
7 |                  2 |                  2
4 |                  2 |                  2
5 |                  2 |                 -1
8 |                  2 |                  2
12 |                  2 |                 -1
11 |                  2 |                 -1
10 |                  2 |                  2
17 |     2.999999999998 |     2.999999999998
14 |                  2 |                  2
18 | 3.4000000000000004 | 3.4000000000000004
13 |                  2 |                 -1
15 |                  2 |                  2
16 |                  2 |                  2
9 |                  2 |                  2
3 |                 -1 |                  2
1 |                  2 |                  2
2 |                 -1 |                  2
(18 rows)



Returning to the original data:

UPDATE edges SET
cost = sign(cost),
reverse_cost = sign(reverse_cost);
UPDATE 18
ALTER TABLE edges DROP COLUMN direction;
ALTER TABLE


## Compruebe la Topología de Ruteo¶

There are lots of possible problems in a graph.

• The data used may not have been designed with routing in mind.

• A graph has some very specific requirements.

• The graph is disconnected.

• There are unwanted intersections.

• The graph is too large and needs to be contracted.

• A sub graph is needed for the application.

• and many other problems that the pgRouting user, that is the application developer might encounter.

### Crossing edges¶

To get the crossing edges:

SELECT a.id, b.id
FROM edges AS a, edges AS b
WHERE a.id < b.id AND st_crosses(a.geom, b.geom);
id | id
----+----
13 | 18
(1 row)



That information is correct, for example, when in terms of vehicles, is it a tunnel or bride crossing over another road.

It might be incorrect, for example:

1. When it is actually an intersection of roads, where vehicles can make turns.

2. When in terms of electrical lines, the electrical line is able to switch roads even on a tunnel or bridge.

When it is incorrect, it needs fixing:

1. For vehicles and pedestrians

• If the data comes from OSM and was imported to the database using osm2pgrouting, the fix needs to be done in the OSM portal and the data imported again.

• In general when the data comes from a supplier that has the data prepared for routing vehicles, and there is a problem, the data is to be fixed from the supplier

2. For very specific applications

• The data is correct when from the point of view of routing vehicles or pedestrians.

• The data needs a local fix for the specific application.

Once analyzed one by one the crossings, for the ones that need a local fix, the edges need to be split.

SELECT ST_AsText((ST_Dump(ST_Split(a.geom, b.geom))).geom)
FROM edges AS a, edges AS b
WHERE a.id = 13 AND b.id = 18
UNION
SELECT ST_AsText((ST_Dump(ST_Split(b.geom, a.geom))).geom)
FROM edges AS a, edges AS b
WHERE a.id = 13 AND b.id = 18;
st_astext
---------------------------
LINESTRING(3.5 2.3,3.5 3)
LINESTRING(3 3,3.5 3)
LINESTRING(3.5 3,4 3)
LINESTRING(3.5 3,3.5 4)
(4 rows)



The new edges need to be added to the edges table, the rest of the attributes need to be updated in the new edges, the old edges need to be removed and the routing topology needs to be updated.

For each pair of crossing edges a process similar to this one must be performed.

The columns inserted and the way are calculated are based on the application. For example, if the edges have a trait name, then that column is to be copied.

Para llos cálculos de pgRouting

• factor based on the position of the intersection of the edges can be used to adjust the cost and reverse_cost columns.

• Capacity information, used on the Flow - Familia de funciones functions does not need to change when splitting edges.

WITH
first_edge AS (
SELECT (ST_Dump(ST_Split(a.geom, b.geom))).path[1],
(ST_Dump(ST_Split(a.geom, b.geom))).geom,
ST_LineLocatePoint(a.geom,ST_Intersection(a.geom,b.geom)) AS factor
FROM edges AS a, edges AS b
WHERE a.id = 13 AND b.id = 18),
first_segments AS (
SELECT path, first_edge.geom,
capacity, reverse_capacity,
CASE WHEN path=1 THEN factor * cost
ELSE (1 - factor) * cost END AS cost,
CASE WHEN path=1 THEN factor * reverse_cost
ELSE (1 - factor) * reverse_cost END AS reverse_cost
FROM first_edge , edges WHERE id = 13),
second_edge AS (
SELECT (ST_Dump(ST_Split(b.geom, a.geom))).path[1],
(ST_Dump(ST_Split(b.geom, a.geom))).geom,
ST_LineLocatePoint(b.geom,ST_Intersection(a.geom,b.geom)) AS factor
FROM edges AS a, edges AS b
WHERE a.id = 13 AND b.id = 18),
second_segments AS (
SELECT path, second_edge.geom,
capacity, reverse_capacity,
CASE WHEN path=1 THEN factor * cost
ELSE (1 - factor) * cost END AS cost,
CASE WHEN path=1 THEN factor * reverse_cost
ELSE (1 - factor) * reverse_cost END AS reverse_cost
FROM second_edge , edges WHERE id = 18),
all_segments AS (
SELECT * FROM first_segments
UNION
SELECT * FROM second_segments)
INSERT INTO edges
(capacity, reverse_capacity,
cost, reverse_cost,
x1, y1, x2, y2,
geom)
(SELECT capacity, reverse_capacity, cost, reverse_cost,
ST_X(ST_StartPoint(geom)), ST_Y(ST_StartPoint(geom)),
ST_X(ST_EndPoint(geom)), ST_Y(ST_EndPoint(geom)),
geom
FROM all_segments);
INSERT 0 4


After adding all the split edges required by the application, the newly created vertices need to be added to the vertices table.

INSERT INTO vertices (in_edges, out_edges, x, y, geom)
(SELECT nv.in_edges, nv.out_edges, nv.x, nv.y, nv.geom
FROM pgr_extractVertices('SELECT id, geom FROM edges') AS nv
LEFT JOIN vertices AS v USING(geom) WHERE v.geom IS NULL);
INSERT 0 1


#### Actualizar la topología de aristas¶

/* -- set the source information */
UPDATE edges AS e
SET source = v.id
FROM vertices AS v
WHERE source IS NULL AND ST_StartPoint(e.geom) = v.geom;
UPDATE 4
/* -- set the target information */
UPDATE edges AS e
SET target = v.id
FROM vertices AS v
WHERE target IS NULL AND ST_EndPoint(e.geom) = v.geom;
UPDATE 4


#### Removing the surplus edges¶

Once all significant information needed by the application has been transported to the new edges, then the crossing edges can be deleted.

DELETE FROM edges WHERE id IN (13, 18);
DELETE 2


There are other options to do this task, like creating a view, or a materialized view.

#### Actializar la topología de vértices¶

To keep the graph consistent, the vertices topology needs to be updated

UPDATE vertices AS v SET
in_edges = nv.in_edges, out_edges = nv.out_edges
FROM (SELECT * FROM pgr_extractVertices('SELECT id, geom FROM edges')) AS nv
WHERE v.geom = nv.geom;
UPDATE 18


#### Checking for crossing edges¶

There are no crossing edges on the graph.

SELECT a.id, b.id
FROM edges AS a, edges AS b
WHERE a.id < b.id AND st_crosses(a.geom, b.geom);
id | id
----+----
(0 rows)



### Disconnected graphs¶

Para obtener la conectividad del grafo:

SELECT * FROM pgr_connectedComponents(
'SELECT id, source, target, cost, reverse_cost FROM edges'
);
seq | component | node
-----+-----------+------
1 |         1 |    1
2 |         1 |    3
3 |         1 |    5
4 |         1 |    6
5 |         1 |    7
6 |         1 |    8
7 |         1 |    9
8 |         1 |   10
9 |         1 |   11
10 |         1 |   12
11 |         1 |   13
12 |         1 |   14
13 |         1 |   15
14 |         1 |   16
15 |         1 |   17
16 |         1 |   18
17 |         2 |    2
18 |         2 |    4
(18 rows)



In this example, the component $$2$$ consists of vertices $$\{2, 4\}$$ and both vertices are also part of the dead end result set.

This graph needs to be connected.

Nota

With the original graph of this documentation, there would be 3 components as the crossing edge in this graph is a different component.

#### Prepare storage for connection information¶

ALTER TABLE vertices ADD COLUMN component BIGINT;
ALTER TABLE
ALTER TABLE edges ADD COLUMN component BIGINT;
ALTER TABLE


#### Save the vertices connection information¶

UPDATE vertices SET component = c.component
FROM (SELECT * FROM pgr_connectedComponents(
'SELECT id, source, target, cost, reverse_cost FROM edges'
)) AS c
WHERE id = node;
UPDATE 18


#### Save the edges connection information¶

UPDATE edges SET component = v.component
FROM (SELECT id, component FROM vertices) AS v
WHERE source = v.id;
UPDATE 20


#### Get the closest vertex¶

The closest vertex to component $$1$$ is vertex $$4$$. And the closest edge to vertex $$4$$ is edge $$14$$.

WITH
edges_sql AS (SELECT id, geom FROM edges WHERE component = 1),
point_sql AS (SELECT geom AS point FROM vertices WHERE component = 2),
results AS (
SELECT
id::BIGINT AS edge_id,
ST_LineLocatePoint(geom, point) AS fraction,
CASE WHEN ST_Intersects(ST_Buffer(geom, 2, 'side=right endcap=flat'), point)
THEN 'r'
ELSE 'l' END::CHAR AS side,
geom <-> point AS distance,
point,
ST_MakeLine(point, ST_ClosestPoint(geom, point)) AS new_line
FROM  edges_sql, point_sql
WHERE ST_DWithin(geom, point, 2)
ORDER BY geom <-> point),
prepare_cap AS (
SELECT row_number() OVER (PARTITION BY point ORDER BY point, distance) AS rn, *
FROM results),
cap AS (
SELECT edge_id, fraction, side, distance, point, new_line
FROM prepare_cap
WHERE rn <= 1
)
SELECT edge_id, fraction, side, distance, point AS geom, new_line AS edge, id AS closest_vertex
INTO closest
FROM cap JOIN vertices ON (point = geom) ORDER BY distance LIMIT 1;
SELECT 1


The edge can be used to connect the components, using the fraction information about the edge $$14$$ to split the connecting edge.

#### Conectando componentes¶

There are three basic ways to connect the components

• From the vertex to the starting point of the edge

• From the vertex to the ending point of the edge

• From the vertex to the closest vertex on the edge

• This solution requires the edge to be split.

The following query shows the three ways to connect the components:

WITH
info AS (
SELECT
edge_id, fraction, side, distance, ce.geom, edge, v.id AS closest,
source, target, capacity, reverse_capacity, e.geom AS e_geom
FROM closest AS ce
JOIN vertices AS v USING (geom)
JOIN edges AS e ON (edge_id = e.id)
ORDER BY distance LIMIT 1),
three_options AS (
SELECT
closest AS source, target, 0 AS cost, 0 AS reverse_cost,
capacity, reverse_capacity,
ST_X(geom) AS x1, ST_Y(geom) AS y1,
ST_X(ST_EndPoint(e_geom)) AS x2, ST_Y(ST_EndPoint(e_geom)) AS y2,
ST_MakeLine(geom, ST_EndPoint(e_geom)) AS geom
FROM info

UNION

SELECT closest, source, 0, 0, capacity, reverse_capacity,
ST_X(geom) AS x1, ST_Y(geom) AS y1,
ST_X(ST_StartPoint(e_geom)) AS x2, ST_Y(ST_StartPoint(e_geom)) AS y2,
ST_MakeLine(info.geom, ST_StartPoint(e_geom))
FROM info
/*
UNION
-- This option requires splitting the edge
SELECT closest, NULL, 0, 0, capacity, reverse_capacity,
ST_X(geom) AS x1, ST_Y(geom) AS y1,
ST_X(ST_EndPoint(edge)) AS x2, ST_Y(ST_EndPoint(edge)) AS y2,
edge
FROM info */
)

INSERT INTO edges
(source, target,
cost, reverse_cost,
capacity, reverse_capacity,
x1, y1, x2, y2,
geom)
(SELECT
source, target, cost, reverse_cost, capacity, reverse_capacity,
x1, y1, x2, y2, geom
FROM three_options);
INSERT 0 2


#### Checking components¶

Ignoring the edge that requires further work. The graph is now fully connected as there is only one component.

SELECT * FROM pgr_connectedComponents(
'SELECT id, source, target, cost, reverse_cost FROM edges'
);
seq | component | node
-----+-----------+------
1 |         1 |    1
2 |         1 |    2
3 |         1 |    3
4 |         1 |    4
5 |         1 |    5
6 |         1 |    6
7 |         1 |    7
8 |         1 |    8
9 |         1 |    9
10 |         1 |   10
11 |         1 |   11
12 |         1 |   12
13 |         1 |   13
14 |         1 |   14
15 |         1 |   15
16 |         1 |   16
17 |         1 |   17
18 |         1 |   18
(18 rows)



### Contraction of a graph¶

The graph can be reduced in size using Contraction - Familia de funciones

When to contract will depend on the size of the graph, processing times, correctness of the data, on the final application, or any other factor not mentioned.

A fairly good method of finding out if contraction can be useful is because of the number of dead ends and/or the number of linear edges.

A complete method on how to contract and how to use the contracted graph is described on Contraction - Familia de funciones

#### Callejones sin salida¶

SELECT id FROM vertices
WHERE array_length(in_edges || out_edges, 1) = 1;
id
----
1
5
9
13
14
2
4
(7 rows)



That information is correct, for example, when the dead end is on the limit of the imported graph.

Visually node $$4$$ looks to be as start/ending of 3 edges, but it is not.

Is that correct?

• Is there such a small curb:

• That does not allow a vehicle to use that visual intersection?

• Is the application for pedestrians and therefore the pedestrian can easily walk on the small curb?

• Is the application for the electricity and the electrical lines than can easily be extended on top of the small curb?

• Is there a big cliff and from eagles view look like the dead end is close to the segment?

When there are many dead ends, to speed up, the Contraction - Familia de funciones functions can be used to divide the problem.

#### Linear edges¶

To get the linear edges:

SELECT id FROM vertices
WHERE array_length(in_edges || out_edges, 1) = 2;
id
----
3
15
17
(3 rows)



This information is correct, for example, when the application is taking into account speed bumps, stop signals.

When there are many linear edges, to speed up, the Contraction - Familia de funciones functions can be used to divide the problem.

## Function’s structure¶

Once the graph preparation work has been done above, it is time to use a

La forma general de una llamada a una función de pgRouting es:

pgr_<name>(Inner queries, parameters, [ Optional parameters)

Donde:

• Inner queries: Are compulsory parameters that are TEXT strings containing SQL queries.

• parameters: Additional compulsory parameters needed by the function.

• Optional parameters: Are non compulsory named parameters that have a default value when omitted.

The compulsory parameters are positional parameters, the optional parameters are named parameters.

For example, for this pgr_dijkstra signature:

pgr_dijkstra(SQL de aristas, salida, destino, [directed])

• Is the first parameter.

• It is compulsory.

• It is an inner query.

• It has no name, so Edges SQL gives an idea of what kind of inner query needs to be used

• vid inical:

• Is the second parameter.

• It is compulsory.

• It has no name, so start vid gives an idea of what the second parameter’s value should contain.

• destino

• Is the third parameter.

• It is compulsory.

• It has no name, so end vid gives an idea of what the third parameter’s value should contain

• directed

• Is the fourth parameter.

• It is optional.

• It has a name.

The full description of the parameters are found on the Parameters section of each function.

A function might have different overloads. The most common are called:

Dependiendo de la sobrecarga, los tipos de los parámetros cambian.

• One: ANY-INTEGER

• Many: ARRAY [ANY-INTEGER]

Depending of the function the overloads may vary. But the concept of parameter type change remains the same.

### Uno a Uno¶

Cuando se rutea desde:

• Desde un vértice inicial

• al un vértice final

### Uno a Muchos¶

Cuando se rutea desde:

• Desde un vértice inicial

• a los vértices finales many

### Muchos a Uno¶

Cuando se rutea desde:

• Desde muchos vértices iniciales

• al un vértice final

### Muchos a Muchos¶

Cuando se rutea desde:

• Desde muchos vértices iniciales

• a los vértices finales many

### Combinaciones¶

Cuando se rutea desde:

• A partir de muchos diferentes vértices de inicio

• a muchos diferentes vértices finales

• Cada tupla especifica un par de vértices iniciales y un vértice final

• Los usuarios pueden definir las combinaciones como deseen.

• Necesita una SQL de combinaciones

## Consultas Internas¶

Hay varios tipos de consultas internas válidas y también las columnas devueltas dependen de la función. El tipo de consulta interna dependerá de los requisitos de las funcion(es). Para simplificar la variedad de tipos, se utiliza ENTEROS y FLOTANTES.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

### SQL aristas¶

#### General¶

SQL de aristas para

Columna

Tipo

x Defecto

Descripción

id

ENTEROS

source

ENTEROS

Identificador del primer vértice de la arista.

target

ENTEROS

Identificador del segundo vértice de la arista.

cost

FLOTANTES

Peso de la arista (source, target)

reverse_cost

FLOTANTES

-1

Peso de la arista (target, source)

• Cuando negativo: la arista (target, source) no existe, por lo tanto no es parte del grafo.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

#### General without id¶

SQL de aristas para

Columna

Tipo

x Defecto

Descripción

source

ENTEROS

Identificador del primer vértice de la arista.

target

ENTEROS

Identificador del segundo vértice de la arista.

cost

FLOTANTES

Peso de la arista (source, target)

reverse_cost

FLOTANTES

-1

Peso de la arista (target, source)

• Cuando negativo: la arista (target, source) no existe, por lo tanto no es parte del grafo.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

#### General with (X,Y)¶

SQL de aristas para

Parámetro

Tipo

x Defecto

Descripción

id

ENTEROS

source

ENTEROS

Identificador del primer vértice de la arista.

target

ENTEROS

Identificador del segundo vértice de la arista.

cost

FLOTANTES

Peso de la arista (source, target)

• Cuando es negativo: la arista (source, target) no existe, por lo tanto no es parte del grafo.

reverse_cost

FLOTANTES

-1

Peso de la arista (target, source),

• Cuando negativo: la arista (target, source) no existe, por lo tanto no es parte del grafo.

x1

FLOTANTES

Coordenada X del vértice source.

y1

FLOTANTES

Coordenada Y del vértice source.

x2

FLOTANTES

Coordenada X del vértice target.

y2

FLOTANTES

Coordenada Y del vértice target.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

#### Flujo¶

Edges SQL for Flow - Familia de funciones

SQL de aristas para

Columna

Tipo

x Defecto

Descripción

id

ENTEROS

source

ENTEROS

Identificador del primer vértice de la arista.

target

ENTEROS

Identificador del segundo vértice de la arista.

capacity

ENTEROS

Peso de la arista (source, target)

reverse_capacity

ENTEROS

-1

Peso de la arista (target, source)

• Cuando negativo: la arista (target, source) no existe, por lo tanto no es parte del grafo.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

Edges SQL for the following functions of Flow - Familia de funciones

Columna

Tipo

x Defecto

Descripción

id

ENTEROS

source

ENTEROS

Identificador del primer vértice de la arista.

target

ENTEROS

Identificador del segundo vértice de la arista.

capacity

ENTEROS

Capacidad de la arista (source, target)

• Cuando negativo: la arista (target, source) no existe, por lo tanto no es parte del grafo.

reverse_capacity

ENTEROS

-1

Capacidad de la arista (target, source)

• Cuando negativo: la arista (target, source) no existe, por lo tanto no es parte del grafo.

cost

FLOTANTES

Peso de la arista (source, target) si existe

reverse_cost

FLOTANTES

$$-1$$

Peso de la arista (target, source) si existe

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

### SQL Combinaciones¶

Used on combination signatures

Parámetro

Tipo

Descripción

source

ENTEROS

target

ENTEROS

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

### SQL restricciones¶

Columna

Tipo

Descripción

path

ARRAY [ENTEROS]

Secuencia de identificadores de aristas que forman un camino que no se permite tomar. - Arreglos vacios o NULL son ignorados. - Arreglos que tienen NULL arrojan una excepción.

Cost

FLOTANTES

Costo de tomar el camino prohibido.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

### SQL de puntos¶

SQL de puntos para

Parámetro

Tipo

x Defecto

Descripción

pid

ENTEROS

valor

• Use con un valor positivo, dado que internamente se convertirá a un valor negativo

• Si columna esta presente, no puede ser NULL.

• Si columna no esta presente, un valor secuencial negativo se otorgará automáticamente.

edge_id

ENTEROS

Identificador de la arista «más cercana» al punto.

fraction

FLOTANTES

El valor en <0,1> que indica la posición relativa desde el primer punto de la arista.

side

CHAR

b

Valor en [b, r, l, NULL] que indica si el punto es:

• A la derecha r,

• A la izquierda l,

• En ambos lados b, NULL

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

FLOTANTES:

SMALLINT, INTEGER, BIGINT, REAL, FLOAT

## Parámetros¶

The main parameter of the majority of the pgRouting functions is a query that selects the edges of the graph.

Parámetro

Tipo

Descripción

SQL de aristas

TEXT

SQL de aristas descritas más adelante.

Depending on the family or category of a function it will have additional parameters, some of them are compulsory and some are optional.

The compulsory parameters are nameless and must be given in the required order. The optional parameters are named parameters and will have a default value.

### Párametros para las funciones Via¶

Parámetro

Tipo

x Defecto

Descripción

SQL de aristas

TEXT

Consulta SQL como se describe.

vértices

ARRAY [ENTEROS]

directed

BOOLEAN

true

• Cuando true el gráfo se considera Dirigido

• Cuando false el gráfico se considera como No Dirigido.

strict

BOOLEAN

false

• Cuando true si un camino le faltan paradas y regresa EMPTY SET

• Cuando false, ignora las rutas faltantes y devuelve todas las rutas encontradas

U_turn_on_edge

BOOLEAN

true

• Cuando true saliendo de un vértice visitado no intentará evitar el uso de la arista utilizada para alcanzarlo. En otras palabras, se permite la vuelta en U usando la arista con el mismo identificador.

• Cuando false al salir de un vértice visitado intenta evitar el uso de la arista utilizada para alcanzarlo. En otras palabras, se utiliza la vuelta en U utilizando la arista con el mismo identificador cuando no se encuentra ninguna otra ruta.

### Para las funciones de TRSP¶

Columna

Tipo

Descripción

SQL de aristas

TEXT

Consulta SQL como se describe.

SQL de restricciones

TEXT

Consulta SQL como se describe.

SQL de combinaciones

TEXT

SQL de combinaciones como se describe a abajo

salida

ENTEROS

salidas

ARRAY [ENTEROS]

Arreglo de identificadores de vértices destino.

destino

ENTEROS

destinos

ARRAY [ENTEROS]

Arreglo de identificadores de vértices destino.

Donde:

ENTEROS:

SMALLINT, INTEGER, BIGINT

Hay varios tipos de columnas devueltas que dependen de la función.

### Columnas devueltas para una trayectoria¶

Used on functions that return one path solution

Devuelve el conjunto de (seq, path_seq [, start_vid] [, end_vid], node, edge, cost, agg_cost)

Columna

Tipo

Descripción

seq

INTEGER

Valor secuencial a partir de 1.

path_seq

INTEGER

Posición relativa en la ruta. Tiene el valor 1 para el inicio de una ruta.

start_vid

BIGINT

Identificador del vértice inicial. Se devuelve cuando hay varias vetrices iniciales en la consulta.

end_vid

BIGINT

Identificador del vértice final. Se devuelve cuando hay varios vértices finales en la consulta.

node

BIGINT

Identificador del nodo en la ruta de start_vid a end_vid.

edge

BIGINT

Identificador de la arista utilizado para ir del node al siguiente nodo de la secuencia de ruta. -1 para el último nodo de la ruta.

cost

FLOAT

Costo para atravesar desde node usando edge hasta el siguiente nodo en la secuencia de la ruta.

agg_cost

FLOAT

Costo agregado desde start_vid hasta node.

Used on functions the following:

Devuelve el conjunto de (seq, path_seq [, start_pid] [, end_pid], node, edge, cost, agg_cost)

Columna

Tipo

Descripción

seq

INTEGER

Valor secuencial a partir de 1.

path_seq

INTEGER

Posición relativa en la ruta.

• 1 para la primera fila de la secuencia de ruta.

start_pid

BIGINT

Identificador del vértice/punto inicial de la ruta.

• Cuando negativo, es el identificador del punto inicial.

• Regresado en Muchos a Uno y Muchos a Muchos

end_pid

BIGINT

Identificador d vértice/punto final del camino.

• Cuando negativo, es el identificador del vertice final.

• Cuando es negativo, es el identificador del vértice destino.

• Regresado en Uno a Muchos y Muchos a Muchos

node

BIGINT

Identificador del nodo en la ruta de start_vid a end_vid.

• Cuando es positivo, es el identificador de un vértice.

• Cuando es negativo, es identificador de un punto.

edge

BIGINT

Identificador de la arsita utilizada para ir del node al siguiente nodo de la secuencia de ruta.

• -1 para la última fila de la ruta.

cost

FLOAT

Costo para atravesar desde node usando edge hasta el siguiente nodo en la secuencia de la ruta.

• 0 para la primera fila de la secuencia de ruta.

agg_cost

FLOAT

Costo agregado desde start_vid hasta node.

• 0 para la primera fila de la secuencia de ruta.

Used on functions the following:

Regresa (seq, path_seq, start_vid, end_vid, node, edge, cost, agg_cost)

Columna

Tipo

Descripción

seq

INTEGER

Valor secuencial a partir de 1.

path_seq

INTEGER

Posición relativa en la ruta. Tiene el valor 1 para el inicio de una ruta.

start_vid

BIGINT

Identificador del vértice inicial de la ruta actual.

end_vid

BIGINT

Identificador del vértice final de la ruta actual.

node

BIGINT

Identificador del nodo en la ruta de start_vid a end_vid.

edge

BIGINT

Identificador de la arista utilizado para ir del node al siguiente nodo de la secuencia de ruta. -1 para el último nodo de la ruta.

cost

FLOAT

Costo para atravesar desde node usando edge hasta el siguiente nodo en la secuencia de la ruta.

agg_cost

FLOAT

Costo agregado desde start_vid hasta node.

### Multiple paths¶

#### Selective for multiple paths.¶

The columns depend on the function call.

Conjunto de (seq, path_id, path_seq [, start_vid] [, end_vid], node, edge, cost, agg_cost)

Columna

Tipo

Descripción

seq

INTEGER

Valor secuencial a partir de 1.

path_id

INTEGER

• Tiene valor 1 para el primero de la ruta de start_vid a end_vid.

path_seq

INTEGER

Posición relativa en la ruta. Tiene el valor 1 para el inicio de una ruta.

start_vid

BIGINT

Identificador del vértice inicial. Se devuelve cuando hay varias vetrices iniciales en la consulta.

end_vid

BIGINT

Identificador del vértice final. Se devuelve cuando hay varios vértices finales en la consulta.

node

BIGINT

Identificador del nodo en la ruta de start_vid a end_vid.

edge

BIGINT

Identificador de la arista utilizado para ir del node al siguiente nodo de la secuencia de ruta. -1 para el último nodo de la ruta.

cost

FLOAT

Costo para atravesar desde node usando edge hasta el siguiente nodo en la secuencia de la ruta.

agg_cost

FLOAT

Costo agregado desde start_vid hasta node.

#### Non selective for multiple paths¶

Regardless of the call, al the columns are returned.

Devuelve el conjunto de (seq, path_id, path_seq, start_vid, end_vid, node, edge, cost, agg_cost)

Columna

Tipo

Descripción

seq

INTEGER

Valor secuencial a partir de 1.

path_id

INTEGER

• Tiene valor 1 para el primero de la ruta de start_vid a end_vid.

path_seq

INTEGER

Posición relativa en la ruta. Tiene el valor 1 para el inicio de una ruta.

start_vid

BIGINT

end_vid

BIGINT

node

BIGINT

Identificador del nodo en la ruta de start_vid a end_vid.

edge

BIGINT

Identificador de la arista utilizado para ir del node al siguiente nodo de la secuencia de ruta. -1 para el último nodo de la ruta.

cost

FLOAT

Costo para atravesar desde node usando edge hasta el siguiente nodo en la secuencia de la ruta.

agg_cost

FLOAT

Costo agregado desde start_vid hasta node.

### Columnas devueltas para funciones de costo¶

Used in the following

Conjunto de (start_vid, end_vid, agg_cost)

Columna

Tipo

Descripción

start_vid

BIGINT

end_vid

BIGINT

agg_cost

FLOAT

Costo afregado desde start_vid hasta end_vid.

Nota

Cuando las columnas del vértice inicial o del destino continen valores negativos, el identificador es para un Punto.

### Columnas devueltas para funciones de flujo¶

Edges SQL for the following

Columna

Tipo

Descripción

seq

INT

Valor secuencial a partir de 1.

arista

BIGINT

Identificador de la arista en la consulta original(edges_sql).

start_vid

BIGINT

Identificador del primer vértice de la arista.

end_vid

BIGINT

Identificador del segundo vértice de la arista.

flujo

BIGINT

Flujo a través del arista en la dirección (start_vid, end_vid).

residual_capacity

BIGINT

Capacidad residual del arista en la dirección (start_vid, end_vid).

Edges SQL for the following functions of Flow - Familia de funciones

Columna

Tipo

Descripción

seq

INT

Valor secuencial a partir de 1.

arista

BIGINT

Identificador de la arista en la consulta original(edges_sql).

origen

BIGINT

Identificador del primer vértice de la arista.

objetivo

BIGINT

Identificador del segundo vértice de la arista.

flujo

BIGINT

Flujo a través de la arista en la dirección (origen, destino).

residual_capacity

BIGINT

Capacidad residual de la arista en la dirección (origen, destino).

costo

FLOAT

El costo de enviar este flujo a través de la arista en la dirección (origen, destino).

agg_cost

FLOAT

### Return columns for spanning tree functions¶

Edges SQL for the following

Devuelve CONJUNTO DE (edge, cost)

Columna

Tipo

Descripción

edge

BIGINT

cost

FLOAT

Coste para atravezar el borde.

## Consejos de Rendimiento¶

### Para las funciones de Ruteo¶

Para obtener resultados más rápidos, delimitar las consultas a un área de interés para el ruteo.

En este ejemplo, usar una consulta SQL interna que no incluya algunas aristas en la función de ruteo y dentro del área de los resultados.

SELECT * FROM pgr_dijkstra($$SELECT id, source, target, cost, reverse_cost from edges WHERE geom && (SELECT st_buffer(geom, 1) AS myarea FROM edges WHERE id = 2)$$,
1, 2);
seq | path_seq | node | edge | cost | agg_cost
-----+----------+------+------+------+----------
(0 rows)



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