Purpose

Property references allow for accessing property values of vertices and edges.

Syntax

property_reference::=

Description of the illustration property_reference.eps

property_name::=

Description of the illustration property_name.eps

Semantics

Syntactically, a property access is an element variable followed by a dot (.) and the name of the property. A property name is an identifier and may thus be either double quoted or unquoted.

The label expression specified for an element pattern determines which properties can be referenced:

• If no label expression is specified, then depending on the type of element variable, either all vertex properties or all edge properties in the graph can be referenced.

• Otherwise, if a label expression is specified, then the set of properties that can be referenced is the union of the properties of labels belonging to vertex (or edge) tables that have at least one label that satisfies the label expression.

If multiple labels satisfy the label expression but they define the same property but of a different data type, then such properties may only be referenced if the data types are union compatible. The resulting value will then have the union compatible data type.

If multiple labels satisfy the label expression while some labels have a particular property that other labels do not, then such properties can still be referenced. The property reference will result in null values for any vertex or edge that does not have the property.

Furthermore, if the element variable is not bound to a graph element, then the result is the null value. Note that the only way an element variable is optionally bound is when the element variable is an iterator variable declared in ONE ROW PER STEP. Specifically, the edge variable and the second vertex variable declared in ONE ROW PER STEP will not be bound to a graph element when the path pattern matches an empty path, for example because a quantifier iterated zero times.

Examples

Example 1

The following query lists the date of birth of all persons and universities in the graph:

SELECT GT.name, GT.birthday
FROM GRAPH_TABLE ( students_graph
  MATCH (p IS person|university)
  COLUMNS (p.name, p.dob AS birthday)
) GT
ORDER BY GT.birthday, GT.name;

Note that since only persons John, Bob, Mary, Alice have dates of birth while universities (ABC and XYZ) do not, null values are returned for universities. These appear as empty strings in the output:

NAME       BIRTHDAY
---------- ---------
John       13-JUN-63
Bob        11-MAR-66
Mary       25-SEP-82
Alice      01-FEB-87
ABC
XYZ

Example 2

The following query matches all PERSON vertices and returns their NAME and HEIGHT:

SELECT *
FROM GRAPH_TABLE ( students_graph
  MATCH (n IS person)
  COLUMNS ( n.name, n.height )
)
ORDER BY height;

The result is:

NAME           HEIGHT
---------- ----------
Mary             1.65
Alice	     1.7
Bob              1.75
John             1.8 

Here, even though label PERSON does not have property HEIGHT, the property can still be referenced because vertex table PERSONS has labels PERSON and PERSON_HT and since label PERSON matches the label expression, the set of properties that can be referenced is the union of the properties of labels PERSON and PERSON_HT, which includes the property HEIGHT of label PERSON_HT.

Purpose

Vertex and edge ID functions allow for obtaining unique identifiers for graph elements.

Syntax

element_id_function::=

Description of the illustration element_id_function.eps

vertex_id_function::=

Description of the illustration vertex_id_function.eps

edge_id_function::=

Description of the illustration edge_id_function.eps

element_reference::=

Description of the illustration element_reference.eps

Semantics

Syntactically, the VERTEX_ID and EDGE_ID functions take an element reference, which should be a vertex reference in case of VERTEX_ID and an edge reference in case of EDGE_ID. The two functions generate identifiers for graph elements that are globally unique within a database.

Content-wise, vertex and edge identifiers are JSON object that contains the following information:

• Owner of the graph that the vertex or edge is part of.

• Name of the graph that the vertex or edge is part of.

• Element table that the vertex or edge is defined in.

• Key value of the vertex or edge.

If the referenced element variable is not bound to a graph element, then the functions return the null value.

Examples

Example 1

The following query lists the vertex identifiers of friends of Mary:

SELECT CAST(p2_id AS VARCHAR2(200)) AS p2_id
FROM GRAPH_TABLE ( students_graph
  MATCH (p1 IS person) -[e1 IS friends]- (p2 IS person)
  WHERE p1.name = 'Mary'
  COLUMNS (vertex_id(p2) AS p2_id)
)
ORDER BY p2_id;

The result is:

P2_ID
--------------------------------------------------------------------------------------------------------
{"GRAPH_OWNER":"SCOTT","GRAPH_NAME":"STUDENTS_GRAPH","ELEM_TABLE":"PERSONS","KEY_VALUE":{"PERSON_ID":1}}
{"GRAPH_OWNER":"SCOTT","GRAPH_NAME":"STUDENTS_GRAPH","ELEM_TABLE":"PERSONS","KEY_VALUE":{"PERSON_ID":3}}
{"GRAPH_OWNER":"SCOTT","GRAPH_NAME":"STUDENTS_GRAPH","ELEM_TABLE":"PERSONS","KEY_VALUE":{"PERSON_ID":4}}

Example 2

The following query uses JSON dot-notation syntax to obtain a set of JSON objects representing the vertex keys of vertices corresponding to friends of Mary:

SELECT GT.p2_id.KEY_VALUE
FROM GRAPH_TABLE ( students_graph
  MATCH (p1 IS person) -[e1 IS friends]- (p2 IS person)
  WHERE p1.name = 'Mary'
  COLUMNS (vertex_id(p2) AS p2_id)
) GT
ORDER BY key_value;

The result is:

KEY_VALUE
----------------------------------------
{"PERSON_ID":1}
{"PERSON_ID":3}
{"PERSON_ID":4}

Example 3

The following query uses the JSON_VALUE function to obtain all the element table names of edges in the graph:

SELECT DISTINCT json_value(e_id, '$.ELEM_TABLE') AS elem_table
FROM GRAPH_TABLE ( students_graph
  MATCH -[e]-
  COLUMNS (edge_id(e) AS e_id)
)
ORDER BY elem_table;

The result is:

ELEM_TABLE
----------------------------------------
FRIENDS
STUDENT_OF

Purpose

The vertex and edge equal predicates allow for specifying that two vertex variables (or two edge variables) should or should not bind to the same vertex (or edge).

Syntax

element_equal_predicate::=

Description of the illustration element_equal_predicate.eps

vertex_equal_predicate::=

Description of the illustration vertex_equal_predicate.eps

edge_equal_predicate::=

Description of the illustration edge_equal_predicate.eps

Semantics

If at least one of the referenced element variables is not bound to a graph element, then the predicates evaluate to the null value. Otherwise, they evaluate to TRUE or FALSE.

Examples

Example 1

The following query finds friends of friends of Mary. Here, the vertex_equal predicate is used to make sure Mary herself is not included in the result.

SELECT name
FROM GRAPH_TABLE ( students_graph
  MATCH (p IS person)
          -[IS friends]- (friend IS person)
            -[IS friends]- (friend_of_friend IS person)
  WHERE p.name = 'Mary' AND NOT vertex_equal(p, friend_of_friend)
  COLUMNS (friend_of_friend.name)
)
ORDER BY name;

The result is:

NAME
----------
Bob
John

Purpose

The SOURCE and DESTINATION predicates allow for testing if a vertex is the source or the destination of an edge. They are useful, for example, for determining the direction of edges that are matched via any-directed edge patterns.

Syntax

source_predicate::=

Description of the illustration source_predicate.eps

destination_predicate::=

Description of the illustration destination_predicate.eps

Semantics

The SOURCE predicate takes a vertex and an edge as input and returns TRUE or FALSE depending on whether the vertex is (not) the source of the edge.

The DESTINATION predicate also takes a vertex and an edge as input and returns TRUE or FALSE depending on whether the vertex is (not) the destination of the edge.

If at least one of the referenced element variables is not bound to a graph element, then the predicates evaluate to the null value. Otherwise, they evaluate to TRUE or FALSE.

Examples

Example 1

The following query matches FRIENDS edges that are either incoming or outgoing from Mary. For each edge, it return the NAME property for the source of the edge as well as the NAME property of the destination of the edge.

SELECT *
FROM GRAPH_TABLE ( students_graph
       MATCH (p1 IS person) -[e IS friends]- (p2 IS person)
       WHERE p1.name = 'Mary'
       COLUMNS (e.friendship_id,
                e.meeting_date,
                CASE WHEN p1 IS SOURCE OF e THEN p1.name ELSE p2.name END AS from_person,
                CASE WHEN p1 IS DESTINATION OF e THEN p1.name ELSE p2.name END AS to_person))
ORDER BY friendship_id;

FRIENDSHIP_ID MEETING_DATE FROM_PERSON TO_PERSON
------------- ------------ ----------- ---------
            2 19-SEP-00    Mary        Alice
            3 19-SEP-00    Mary        John
            4 10-JUL-01    Bob         Mary

Example 2

The following query find friends of friends of John such that the two FRIENDS edges are either both incoming or outgoing.

SELECT *
FROM GRAPH_TABLE ( students_graph
       MATCH (p1 IS person) -[e1 IS friends]- (p2 IS person)
               -[e2 IS friends]- (p3 IS person)
       WHERE p1.name = 'John'
         AND ((p1 IS SOURCE OF e1 AND p2 IS SOURCE OF e2) OR
             (p1 IS DESTINATION OF e1 AND p2 IS DESTINATION OF e2))
       COLUMNS (p1.name AS person_1,
                CASE WHEN p1 IS SOURCE OF e1
                  THEN 'Outgoing' ELSE 'Incoming'
                  END AS e1_direction,
                p2.name AS person_2,
                CASE WHEN p2 IS SOURCE OF e2
                  THEN 'Outgoing' ELSE 'Incoming'
                  END AS e2_direction,
                p3.name AS person_3))
ORDER BY 1, 2, 3;

PERSON_1   E1_DIRECTION PERSON_2   E2_DIRECTION PERSON_3
---------- ------------ ---------- ------------ ----------
John       Incoming     Mary       Incoming     Bob
John       Outgoing     Bob        Outgoing     Mary

Notice how the path from John via Mary to Alice is not part of the result since it has an incoming edge followed by an outgoing edge and thus not two edges in the same direction.

Purpose

Aggregations in GRAPH_TABLE are used to compute one or more values for a set of vertices or edges in a variable-length path. This is done using the same Aggregate Functions that are also available for non-graph queries.

Syntax

All the aggregate functions that are available for non-graph queries are also available for graph queries. See Aggregate Functions for the syntax of these functions.

Aggregate functions can be used in WHERE and COLUMNS clauses in GRAPH_TABLE, with the restriction that WHERE clauses within quantified patterns may not contain aggregate functions.

Syntactically, the value expressions in the aggregations must contain references to vertices and edges in the graph pattern, rather than to columns of tables like in case of regular (non-graph) SQL queries.

Semantics

See Aggregate Functions for the semantics of aggregate functions.

The arguments of the aggregate function together must reference exactly one group variable. In addition, they can reference any number of singleton variables. Note that an element variable is said to have group degree of reference when the variable is declared in a quantified path pattern while the reference occurs outside the quantified path pattern. On the other hand, if the reference does not cross a quantifier then the reference has singleton degree of reference. Singleton variables may be element pattern variables declared in the graph pattern or iterator variables declared in the Rows Clause. Also see Element Variable for more details on the contextual interpretation of graph element references.

The order in which values are aggregated in case of LISTAGG, JSON_ARRAYAGG and XMLAGG is non-deterministic unless an ORDER BY clause is specified. For example: LISTAGG(edge1.property1 ORDER BY edge1.property1)). There is currently no way to explicitly order by path order in such a way that elements are ordered in the same order as the vertices or edges in the path. However, when omitting the ORDER BY clause, the current implementation nevertheless implicitly orders by path order, but it should not be relied upon as this behavior may change over time.

Restrictions

• Only WHERE clauses that are not within a quantified pattern may contain aggregations. For example, the graph pattern WHERE clause as well as non-quantified element pattern WHERE clauses may contain aggregations, while parenthesized path pattern WHERE clauses may not contain aggregations since parenthesized path patterns currently have a restriction that they must always be quantified.

• The arguments of an aggregate function in GRAPH_TABLE together must reference exactly one group variable. In addition, they may reference any number of singleton variables. For example, MATCH -[e1]-> WHERE SUM(e1.prop) > 10 is not allowed since variable e1 has singleton degree of reference within the SUM aggregate, while MATCH -[e2]->{1,10} WHERE SUM(e2.prop) > 10 and MATCH -[e3]->{1,1} WHERE SUM(e3.prop) > 10 are allowed since variables e2 and e3 have group degree of reference within the SUM aggregates.

• Variable references must be inside property references, vertex or edge ID functions, or JSON dot-notation expressions. For example, vertex_equal, edge_equal, IS SOURCE OF and IS DESTINATION OF cannot be used in aggregate functions. For example, COUNT(edge1) is not allowed but COUNT(edge_id(edge1)) and COUNT(edge1.some_property)) are allowed.

• The arguments of an aggregate function in GRAPH_TABLE cannot reference anything other than a vertex or edge declared within the graph pattern of the GRAPH_TABLE. For example, it is not possible to reference a column that is passed from an outer query.

• In case of LISTAGG, JSON_ARRAYAGG and XMLAGG there is no way to specify that the order of elements in the result should be in the order of the vertices or edges in the path, although the current implement nevertheless implicitly orders by path order.

Examples

Example 1

The following query finds all paths that have a length between 2 and 5 edges ({2,5}), starting from a person named Alice and following both incoming and outgoing edges labeled friends. Edges along paths should not be traversed twice (COUNT(edge_id(e) = COUNT(DISTINCT edge_id(e))). The query returns all friendship IDs along paths as well as the length of each path.

SELECT *
FROM GRAPH_TABLE ( students_graph
       MATCH (p IS person) -[e IS friends]-{2,5} (friend IS person)
       WHERE p.name = 'Alice' AND
             COUNT(edge_id(e)) = COUNT(DISTINCT edge_id(e))
       COLUMNS (LISTAGG(e.friendship_id, ', ') AS friendship_ids,
                COUNT(edge_id(e)) AS path_length))
ORDER BY path_length, friendship_ids;

Note that in the element pattern WHERE clause of the query above, p.name references a property of a single edge, while edge_id(e) within the COUNT aggregates accesses a list of element IDs since the edge variable e is enclosed by the quantifier {2,5}. Similarly, the two property references in the COLUMNS clause access a list of property values and edge ID values.

The result is:

FRIENDSHIP_IDS    PATH_LENGTH
----------------- -----------
2, 3              2
2, 4              2
2, 3, 1           3
2, 4, 1           3
2, 3, 1, 4        4
2, 4, 1, 3        4

Example 2

The following query finds all paths between university ABC and university XYZ such that paths have a length of up to 3 edges ({,3}). For each path, a JSON array is returned such that the array contains the friendship_id value for edges labeled friends, and the subject value for edges labeled student_of. Note that the friendship_id property is cast to VARCHAR(100) to make it type-compatible with the subject property.

SELECT *
FROM GRAPH_TABLE ( students_graph
       MATCH (u1 IS university) -[e]-{,3} (u2 IS university)
       WHERE u1.name = 'ABC' AND u2.name = 'XYZ'
       COLUMNS (JSON_ARRAYAGG(CASE WHEN e.subject IS NOT NULL THEN e.subject
                              ELSE CAST(e.friendship_id AS VARCHAR(100)) END) AS path))
ORDER BY path;
The result is:
PATH
-----------------------
["Arts","3","Math"]
["Music","4","Math"]

Example 3

Example 3 The following query finds all paths that have a length between 2 and 3 edges ({2,3}), starting from a person named John and following only outgoing edges labeled friends and vertices labeled person. Vertices along paths should not have the same person_id as John (WHERE p.person_id <> friend.person_id).

SELECT *
FROM GRAPH_TABLE ( students_graph
       MATCH (p IS person) ( -[e IS friends]-> (friend IS person)
                             WHERE p.person_id <> friend.person_id){2,3}
       WHERE p.name = 'John'
       COLUMNS (COUNT(edge_id(e)) AS path_length,
                LISTAGG(friend.name, ', ') AS names,
                LISTAGG(e.meeting_date, ', ') AS meeting_dates ))
ORDER BY path_length;

Above, the COLUMNS clause contains three aggregates, the first to compute the length of each path, the second to create a comma-separated list of person names along paths, and the third to create a comma-separate list of meeting dates along paths.

The result of the query is:

PATH_LENGTH NAMES               MEETING_DATES                                                      
----------- ------------------- -----------------------------------                                
          2 Bob, Mary           01-SEP-00, 10-JUL-01                                               
          3 Bob, Mary, Alice    01-SEP-00, 10-JUL-01, 19-SEP-00

Purpose

JSON dot notation for property graphs allows for easy access to JSON data exposed as vertex or edge property values. It provides a simple syntax for common use cases, while SQL/JSON functions json_value and json_query can be used for more complex queries against property graphs containing JSON data.

Syntax

json_property_graph_object_access_expr::=

Description of the illustration json_property_graph_object_access_expr.eps

json_prop_graph_obj_access_step::=

Description of the illustration json_prop_graph_obj_access_step.eps

array_step::=

Description of the illustration json_prop_graph_obj_access_step.eps

Semantics

JSON dot notation for property graphs supports the same functionality as JSON Dot Notation for columns of JSON data. Please refer to JSON Object Access Expressions.

Examples

The following example creates a new graph on top of the persons table from the sample data. This graph will have a vertex property person_data of type JSON since the persons table has person_data column of type JSON. Then, a GRAPH_TABLE query that uses JSON dot notation is issued against this graph to obtain the role of all persons in the HR department.

CREATE PROPERTY GRAPH persons_graph VERTEX TABLES ( persons );

SELECT *
FROM GRAPH_TABLE ( persons_graph
       MATCH (n)
       WHERE n.person_data.department = 'HR'
       COLUMNS (n.name, n.person_data.role.string() AS role)
     );

The output of above SELECT query is:

NAME            ROLE
--------------- ---------------
Mary            HR Manager
Alice           HR Assistant

Note how item method string() is used in the COLUMNS clause to return a VARCHAR2(4000). Without the item method it would have returned a JSON string and the result would have been double quoted.