Author: Mats Rydberg <
mats@neotechnology.com>
Abstract
This CIP describes syntax and semantics for Cypher constraints. These are language constructs that impose
restrictions on the shape of the data graph, and how statements are allowed to change it.
Cypher has a loose notion of a schema, in which nodes and relationships may take very heterogeneous forms, both in
terms of properties and in graph patterns. Constraints allow us to mould the heterogeneous nature of the property graph
into a more regular form.
This CIP specifies the general syntax for constraint definition (and constraint removal), and provides several examples of
possible use cases for constraints. However, the specification does not otherwise specify or limit the space of expressible
constraints that the syntax and semantics allow.
This specification also covers the return structure of constraint commands, see Return record.
The constraint syntax is defined as follows:
Grammar definition for constraint syntax.
References to existing grammar parts:
<SymbolicName>
<Pattern>
<Expression>
<PropertyExpression>
References to new grammar parts:
<ConstraintCommand>
<CreateConstraint>
<DropConstraint>
<ConstraintPredicate>
<Unique>
<NodeKey>
<GroupedPropertyExpression>
The
REQUIRE
clause works exactly like the
WHERE
clause in a standard Cypher query, with the addition of also supporting
the special constraint operators
IS UNIQUE
,
IS NODE KEY
, and the new
<GroupedExpression>
expression. This allows
for complex concrete constraint definitions (using custom predicates) within the specified syntax.
For details on
IS UNIQUE
,
IS NODE KEY
, and
<GroupedExpression>
, see the dedicated sections below:
Uniqueness,
Node key, Grouped expression.
The term 'constraint expression' is used in the following to describe the expressions that constitute the body of the
constraint predicate.
All constraints provide the user the option to specify a nonempty name at constraint creation time. This name is
subsequently the handle with which a user may refer to the constraint, for example when dropping it. In the case where a
name is not provided, the system will generate a unique name.
A constraint is removed by referring to its name.
Example of dropping a constraint with name
foo
:
The semantics for constraints follow these general rules:
1. The constraint pattern define the constraint domain, where all elements that would be returned by a
MATCH
clause
with the same pattern constitute the domain, with one notable exception (see
3.).
2. The constraint expressions defined in the
REQUIRE
clauses of the constraint definition must all evaluate to
true
, at all
times.
3
. Elements for which a constraint expression evaluate to
null
under Cypher’s ternary logic are excluded from the
constraint domain, even if they fit within the constraint pattern.
4
. The constraint expression must be deterministic and free of side effects (such as graph mutations).
The following list describes the situations in which an error will be raised:
Attempting to add a constraint on a graph where the data does not comply with a constraint predicate.
Attempting to add a constraint with a name that already exists.
Attempting to add a constraint that the underlying engine does not support enforcing.
Attempting to drop a constraint referencing a non-existent name.
Attempting to modify the graph in such a way that it would violate a constraint.
Once a constraint has been added, it may not be amended. Should a user wish to change a constraint definition, the
constraint has to be dropped and added anew with an updated structure.
This CIP introduces the concept of a grouped expression, consisting of one or more property expressions. A grouped
expression expresses a new value type in Cypher: a tuple type. This type exists only for the purposes of the
IS UNIQUE
and
IS NODE KEY
operators and this CIP does not further extend its applicability.
The tuple type is composed of the types of the property expressions. These rules apply:
1
. When one of the contained property expressions is
null
, the tuple type is also
null
.
2. When compared for equality to another tuple type, the comparison is equivalent to comparing the property
expressions of the tuples respectively, in a conjunction.
A wider definition is not necessary for this type to satisfy the requirements of the
IS UNIQUE
and
IS NODE KEY
operators.
The new operator
IS UNIQUE
is only valid as part of a constraint predicate. It takes as argument a
grouped expression,
and asserts that it is unique across the domain of the constraint. Following on rule 3. above, elements for which the
grouped expression is
null
are not part of the constraint domain. In particular, in the case where the grouped expression
is a single property expression, this means that the uniqueness constraint does not hinder the existence of multiple
elements having a
null
value for the specified property.
Example of a constraint definition using
IS UNIQUE
, over the domain of nodes labeled with
:Person
:
The new operator
IS NODE KEY
is only valid as part of a constraint predicate. It takes as argument a
grouped expression,
and asserts that two conditions hold:
1. Each property expression within the grouped expression cannot be
null
.
2. The grouped expression is unique across the domain of the constraint.
By way of 1. the node key constraint avoids applicability of rule 3. above. The domain of a node key constraint is thus
exactly defined as all elements which fit the constraint pattern.
Example of a constraint definition using
IS NODE KEY
, over the domain of nodes labeled with
:Person
:
The node key constraint can be equivalently expressed using a combination of the
IS UNIQUE
and
IS NOT NULL
operators. The below example illustrates this.
Example of a constraint definition using
IS UNIQUE
and
IS NOT NULL
, over the domain of nodes labeled with
:Person
:
It is possible to define multiple
REQUIRE
clauses within the scope of the same constraint. The semantics between these is
that of a conjunction (under standard 2-valued boolean logic) between the constraint predicates of the clauses, such that
the constraint is upheld if and only if for all
REQUIRE
clauses, the joint predicate evaluates to
true
.
Since constraints always are named, but user-defined names are optional, the system must sometimes generate a
constraint name. In order for a user to be able to drop such a constraint, the system-generated name is therefore returned
in a standard Cypher result record. The result record has a fixed structure, with three string fields:
name
,
definition
,
and
details
.
A constraint command will always return exactly one record, if successful. Note that also
DROP CONSTRAINT
will return a
record.
This field contains the name of the constraint, either user- or system-defined.
This field contains the constraint definition, which is the contents of the constraint creation command following (and
including) the
FOR
clause.
The contents of this field are left unspecified, to be used for implementation-specific messages and/or details.
Consider the following constraint:
A correct result record for it could be:
In this section we provide several examples of constraints that are possible to express in the specified syntax.
The specification in this CIP is limited to the general syntax of constraints, and the following are simply
examples of possible uses of the language defined by that syntax. None of the examples provided are to be
viewed as mandatory for any Cypher implementation.
Consider the graph added by the statement below. The graph contains nodes labeled with
:Color
. Each color is
represented as an integer-type RGB value in a property
rgb
. Users may look up nodes labeled with
:Color
to extract
their RGB values for application processing. Users may also add new
:Color
-labeled nodes to the graph.
Owing to the duplication of the
rgb
property, the following attempt at adding a constraint will fail:
Now, consider the following query which retrieves the RGB value of a color with a given
name
:
The
WHERE
clause is here used to prevent an application from retrieving
null
values for user-defined colors where the
RGB values have not been specified correctly. It may, however, be eliminated by the introduction of a constraint asserting
the existence of that property:
Any updating statement that would create a
:Color
node without specifying an
rgb
property for it would now fail.
If we instead want to make the combination of the properties
name
and
rgb
unique, while simultaneously mandating
their existence, we could use a
NODE KEY
operator to capture all these requirements in a single constraint:
This constraint will make sure that all
:Color
nodes has a value for their
rgb
and
name
properties, and that the
combination is unique across all the nodes. This would allow several
:Color
nodes named
'grey'
, as long as their
rgb
values are distinct.
More complex constraint definitions are considered below:
Multiple property existence using conjunction
Using larger pattern
Property value limitations
Cardinality
Endpoint requirements
Label coexistence
Assuming a function
acyclic()
that takes a path as argument and returns
true
if and only if the same node does not
appear twice in the path, otherwise
false
, we may express:
Constraint example from CIR-2017-172
The main interaction between the constraints and the rest of the language occurs during updating statements. Existing
constraints will cause some updating statements to fail, thereby fulfilling the main purpose of this feature.
Alternative syntaxes have been discussed:
GIVEN
,
CONSTRAIN
,
ASSERT
instead of
FOR
ASSERT
,
ENFORCE
,
IMPLIES
instead of
REQUIRE
ADD
instead of
CREATE
It is desirable for verb pairs for modifying operations to be consistent in the language, and recent discussions are (so
far informally) suggesting
INSERT
/
DELETE
to be used for data modification, thus making
CREATE
and
DROP
available for schema modification such as constraints.
Using a prefix model for uniqueness and node keys, alike
REQUIRE UNIQUE (n.a, n.b)
This was discarded in favour of the suffix model due to similarity with already existing
IS NOT NULL
. Prefix
operators are uncommon in Cypher.
The use of an existing expression to express uniqueness — instead of using the operator
IS UNIQUE
— becomes unwieldy
for multiple properties, as exemplified by the following:
In SQL, the following constraints exist (inspired by
http://www.w3schools.com/sql/sql_constraints.asp):
NOT NULL
- Indicates that a column cannot store a null value.
UNIQUE
- Ensures that each row for a column must have a unique value.
PRIMARY KEY
- A combination of a
NOT NULL
and
UNIQUE
. Ensures that a column (or a combination of two or more
columns) has a unique identity, reducing the resources required to locate a specific record in a table.
FOREIGN KEY
- Ensures the referential integrity of the data in one table matches values in another table.
CHECK
- Ensures that the value in a column meets a specific condition
DEFAULT
- Specifies a default value for a column.
The
NOT NULL
SQL constraint is expressible using an
exists()
constraint predicate. The
UNIQUE
SQL constraint is
exactly as Cypher’s
IS UNIQUE
constraint predicate. The
PRIMARY KEY
SQL constraint is exactly as Cypher’s
IS NODE
KEY
constraint predicate.
SQL constraints may be introduced at table creation time in a
CREATE TABLE
statement, or in an
ALTER TABLE
statement:
Creating a
Person
table in SQL Server / Oracle / MS Access:
Creating a
Person
table in MySQL:
Adding a named composite
UNIQUE
constraint in MySQL / SQL Server / Oracle / MS Access:
Constraints make Cypher’s notion of schema more well-defined, allowing users to maintain graphs in a more regular,
easier-to-manage form.
Additionally, this specification is deliberately defining a constraint language within which a great deal of possible concrete
constraints are made possible. This allows different implementers of Cypher to independently choose how to limit the
scope of supported constraint expressions that fit their model and targeted use cases, while retaining a common and
consistent semantic and syntactic model.
Some constraints may prove challenging to enforce in a system seeking to implement the contents of this CIP, as these
generally require scanning through large parts of the graph to locate conflicting elements.