5.7.6.1 Shortest Path Examples
The following examples demonstrate SQL-based shortest path analytics.
Example 5-18 Shortest Path Setup and Computation
Consider shortest path, for example. Internally, Oracle Database uses the bidirectional Dijkstra algorithm. The following code snippet shows an entire prepare, perform, and cleanup workflow.
set serveroutput on
DECLARE
wt1 varchar2(100); -- intermediate working tables
n number;
path varchar2(1000);
weights varchar2(1000);
BEGIN
-- prepare
opg_apis.find_sp_prep('connectionsGE$', wt1);
dbms_output.put_line('working table name ' || wt1);
-- compute
opg_apis.find_sp(
'connectionsGE$',
1, -- start vertex ID
53, -- destination vertex ID
wt1, -- working table (for Dijkstra expansion)
dop => 1, -- degree of parallelism
stats_freq=>1000, -- frequency to collect statistics
path_output => path, -- shortest path (a sequence of vertices)
weights_output => weights, -- edge weights
options => null
);
dbms_output.put_line('path ' || path);
dbms_output.put_line('weights ' || weights);
-- cleanup (commented out here; see text after the example)
-- opg_apis.find_sp_cleanup('connectionsGE$', wt1);
END;
/
This example may produce the following output. Note that if no working table name is provided, the preparation step will automatically generate a temporary table name and create it. Because the temporary working table name uses the session ID, your output will probably be different.
working table name "CONNECTIONSGE$$TWFS12" path 1 3 52 53 weights 4 3 1 1 1 PL/SQL procedure successfully completed.
If you want to know the definition of the working table or tables, then skip the cleanup phase (as shown in the preceding example that comments out the call to find_sp_cleanup). After the computation is done, you can describe the working table or tables.
SQL> describe "CONNECTIONSGE$$TWFS12"
Name Null? Type
--------- -------- ----------------------------
NID NUMBER
D2S NUMBER
P2S NUMBER
D2T NUMBER
P2T NUMBER
F NUMBER(38)
B NUMBER(38)
For advanced users who want to try different table creation options, such as using in-memory or advanced compression, you can pre-create the preceding working table and pass the name in.
Example 5-19 Shortest Path: Create Working Table and Perform Analytics
The following statements show some advanced options, first creating a working table with the same column structure and basic compression enabled, then passing it to the SQL-based computation. The code optimizes the intermediate table for computations with CREATE TABLE compression and in-memory options.
create table connections$MY_EXP(
NID NUMBER,
D2S NUMBER,
P2S NUMBER,
D2T NUMBER,
P2T NUMBER,
F NUMBER(38),
B NUMBER(38)
) compress nologging;
DECLARE
wt1 varchar2(100) := 'connections$MY_EXP';
n number;
path varchar2(1000);
weights varchar2(1000);
BEGIN
dbms_output.put_line('working table name ' || wt1);
-- compute
opg_apis.find_sp(
'connectionsGE$',
1,
53,
wt1,
dop => 1,
stats_freq=>1000,
path_output => path,
weights_output => weights,
options => null
);
dbms_output.put_line('path ' || path);
dbms_output.put_line('weights ' || weights);
-- cleanup
-- opg_apis.find_sp_cleanup('connectionsGE$', wt1);
END;
/
At the end of the computation, if the working table has not been dropped or truncated, you can check the content of the working table, as follows. Note that the working table structure may vary between releases.
SQL> select * from connections$MY_EXP;
NID D2S P2S D2T P2T F B
---------- ---------- ---------- ---------- ---------- ---------- ----------
1 0 1.000E+100 1 -1
53 1.000E+100 0 -1 1
54 1.000E+100 1 53 -1 1
52 1.000E+100 1 53 -1 1
5 1 1 1.000E+100 0 -1
26 1 1 1.000E+100 0 -1
8 1000 1 1.000E+100 0 -1
3 1 1 2 52 0 0
15 1 1 1.000E+100 0 -1
21 1 1 1.000E+100 0 -1
19 1 1 1.000E+100 0 -1
...
Example 5-20 Shortest Path: Perform Multiple Calls to Same Graph
To perform multiple calls to the same graph, only a single call to the preparation step is needed. The following shows an example of computing shortest path for multiple pairs of vertices in the same graph.
DECLARE
wt1 varchar2(100); -- intermediate working tables
n number;
path varchar2(1000);
weights varchar2(1000);
BEGIN
-- prepare
opg_apis.find_sp_prep('connectionsGE$', wt1);
dbms_output.put_line('working table name ' || wt1);
-- find shortest path from vertex 1 to vertex 53
opg_apis.find_sp( 'connectionsGE$', 1, 53,
wt1, dop => 1, stats_freq=>1000, path_output => path, weights_output => weights, options => null);
dbms_output.put_line('path ' || path);
dbms_output.put_line('weights ' || weights);
-- find shortest path from vertex 2 to vertex 36
opg_apis.find_sp( 'connectionsGE$', 2, 36,
wt1, dop => 1, stats_freq=>1000, path_output => path, weights_output => weights, options => null);
dbms_output.put_line('path ' || path);
dbms_output.put_line('weights ' || weights);
-- find shortest path from vertex 30 to vertex 4
opg_apis.find_sp( 'connectionsGE$', 30, 4,
wt1, dop => 1, stats_freq=>1000, path_output => path, weights_output => weights, options => null);
dbms_output.put_line('path ' || path);
dbms_output.put_line('weights ' || weights);
-- cleanup
opg_apis.find_sp_cleanup('connectionsGE$', wt1);
END;
/
The example's output may be as follows: three shortest paths have been found for the multiple pairs of vertices provided.
working table name "CONNECTIONSGE$$TWFS12" path 1 3 52 53 weights 4 3 1 1 1 path 2 36 weights 2 1 1 path 30 21 1 4 weights 4 3 1 1 1 PL/SQL procedure successfully completed.
Parent topic: SQL-Based Property Graph Analytics