Soufflé requires the declaration of relations. A relation is a set of ordered tuples (x1, …, xk) where each element xi is a member of a data domain denoted by an attribute type. In the previous example, the declaration In Soufflé, relations declarations define the domain of relations, their constraints, and their execution behaviour. Soufflé uses different relation representations internally that can be chosen by the programmer. Inlining, magic-set transformations, and component behaviour is also controlled by the relation declarations.
The relation declaration,
.decl A(x:number, y:number).
defines the relation
A that contains pairs of numbers. The first attribute is named
x and the second attribute is named
y. Attributes have a type which is specified by an identifier followed by a colon after the attribute name. In the above example, the type is a
number. The type-checker of Soufflé will infer the type of variables using the attribute types of relations.
Identifiers follow the C++/C standards except that a question mark may appear anywhere:
- The identifier can only be composed of letters (lower or upper case), numbers, or the question mark and underscore characters. That means the name cannot contain whitespace, or any symbols other than underscores or question marks.
- The identifier must begin with a letter (lower or upper case), an underscore, or a question mark. It can not start with a number.
Representation of Relations
Relations can be represented using different internal data structures in Soufflé, each exhibiting different performance characteristics. By default, the B-tree is used to store tuples of a relation. However, this default representation can be overridden by users, by specifying a relation qualifier for an alternative representation. Currently, the possible data structures are B-tree, Brie, and Eqrel (for equivalence relations).
The B-tree data structure is used by default, however the direct flavour (see below) can be forced by adding the
btree qualifier to a relation declaration:
.decl A(x:number, y:symbol) btree
The B-tree is the default data structure, which performs reasonably well in general use cases. In Soufflé, two flavours of the B-tree are offered. The first is a direct version, where tuple data is stored directly in the B-tree. The second is an indirect version, where the B-tree stores pointers to an external table data structure which holds the actual tuple data.
By default, a relation without qualifiers will be direct if it has arity ≤ 6, and indirect if it has arity > 6. This choice is made because larger arity tuples take more space in the B-tree data structure, so cache coherence can be improved by using pointers instead (and storing the tuples in an efficient list data structure. If the
btree qualifier is specified for a relation, the direct B-tree representation is used even if the arity > 6.
More details on the Soufflé B-tree can be found in this paper.
The Brie data structure is a specialised data structure designed for dense data. It can be used by adding the
brie qualifier to a relation declaration.
.decl A(x:number, y:symbol) brie
The Brie data structure is a specialised form of a trie, or prefix tree. The benefits of using a prefix tree-style data structure for dense data can be illustrated as follows.
Consider a 3-arity relation containing tuples
(0,0,0), (0,0,1), (0,0,2)
In this case, all tuples share the common prefix
0, 0, and differ only in the final digit. This data can be described as
dense, since a common prefix reduces redundant stored information in the prefix tree. On the other hand, a relation containing
(0,0,0), (1,2,3), (4,5,6)
is not dense, and the prefix tree provides no benefit.
The Brie data structure in Soufflé similarly provides a performance benefit for highly dense data (arity <= 2). However, it is slower than the B-tree in the average case, and so its use must be considered carefully and its performance will depend on the data in the relation.
More details on the Brie can be found in this paper.
An equivalence relation is a special kind of binary relation which exhibits three properties: reflexivity, symmetry, and transitivity. An equivalence relation could be expressed in Datalog as follows:
.decl equivalence(x:number, y:number) equivalence(a, b) :- rel1(a), rel2(b). // every element of rel1 is equivalent to every element of rel2 equivalence(a, a) :- equivalence(a, _). // reflexivity equivalence(a, b) :- equivalence(b, a). // symmetry equivalence(a, c) :- equivalence(a, b), equivalence(b, c). // transitivity
However, this expression of an equivalence relation may require a quadratic number of tuples in the size of the input domain. In Soufflé, the Eqrel data structure provides a linear representation of equivalence relations, by using a union-find based algorithm. The
eqrel qualifier specifies that a relation is an equivalence relation relation and it becomes a self-computing data-structure. The rules for reflexivity, symmetry, and transitivity can be ommitted.
The following example demonstrates the use of an equivalence relation, and is semantically equivalent to the example above with the benefit of using less memory and faster execution time.
.decl eqrel_fast(x : number, y : number) eqrel eqrel_fast(a,b) :- rel1(a), rel2(b).
More details on equivalence relation in Soufflé can be found in this paper.
Nullary relations are special relations. Their arity is zero, i.e., they don’t have attributes. They are defined as
These relations are either empty or contain the empty tuple
(). Internatlly, they are implemented
as a boolean variable. Semantically, they can be seen as a proposition rather than a relation.
In Soufflé, the default data structure is the B-tree, with the direct version for relations with arity ≤ 6, or the indirect version for relations with arity > 6.
In Soufflé, relations are cluster of indexes. The indexes are automatically chosen using a combinatorial optimisation problem so that all operations on a relation can be covered by an index using a minimal number of indexes. We refer to these operations as primitive searches, which may evaluate billions of times in large-scale Datalog applications. More details on our auto-indexing technique can be found in this paper. Souffe’s auto-indexing technique alleviates the burden of selecting indexes for Datalog programs by the end-user.
The relation qualifier
magic enables the magic-set transformation for a relation. A magic set transformation specializes the evaluation for a Datalog program for a given set of output relations. The magic-set transformation does not always lead to better performance. Soufflé provides the relation qualifier
magic to enable magic-set transformation and the relation qualifier
no_magic to disable magic-set transformation (note that
no_magic also implies
no_inline). More information on the magic-set transformation can be found here.
Soufflé offers the ability to manually select one or more program relations to be inlined, i.e., a substitution of the relations are performed. This may lead to performance gains by re-computing results rather than storing them. For example,
.decl R(arg:number) inline
replaces every occurrence of predicate
R by its rules, i.e.,
inline keyword directs Soufflé to transform the program into an equivalent form that does not contain the marked relations. On a high level, the transformation is essentially achieved by replacing all occurrences of the marked relation with the bodies of each of its rules, while ensuring program semantics are preserved.
Consider the following Soufflé program,
.decl natural_number(x:number) natural_number(0). natural_number(x+1) :- natural_number(x), x < 10000. .decl natural_pairs(x:number, y:number) inline natural_pairs(x,y) :- natural_number(x), natural_number(y). .decl query(x:number) query(x) :- natural_pairs(x,y), x < 5, y < x.
which will be transformed into:
.decl natural_number(x:number) natural_number(0). natural_number(x+1) :- natural_number(x), x < 10000. .decl query(x:number) query(x) :- natural_number(x), natural_number(y), x < 5, y < x.
The advantage of inlineing is to improve the readability of the original code.
The new program avoids computing all tuples for the intermediate relation
natural_pairs, which would contain 100,000,000 entries.
The result is a signficant improvement in speed, as millions of unnecessary tuples no longer need to be computed,
without having to compromise code quality.
As inlining can potentially bind variables to specific constants, the process may also provide gains when used in conjunction with the Magic Set transformation, which specialises rules based on constant propagation.
In general, inlining is most appropriate when used for large relations where it is not beneficial to compute and cache all tuples beforehand.
Suppose the following relation was marked to be inlined:
.decl a(x:number, y:number) inline a(x,y) :- d(x,x), e(y). a(x,y) :- f(y,x).
and the relation appears in the following rule:
b(x) :- c(x,z), b(y), a(y,z).
The first stage of inlining is to match the arguments of the body atom,
a(y,z), with the heads of each of its rules. Argument-matching is done through a process called unification, where the most general unifier is found. In this case, both rules have the head
a(x,y). It is important to note, however, that the variable
y appearing in the body atom
a(y,z) is distinct from the
y appearing in the head atom
a(x,y). An α-reduction must hence be performed to avoid naming conflicts. In this case, we can rename the head atom of the rules to be
a(x0,y0), producing the following equivalent rules for
a(x0,y0) :- d(x0,x0), e(y0). a(x0,y0) :- f(y0,x0).
Unification can now proceed. In this case,
a(y,z) must be unified with
a(x0,y0) for both rules, which can be done by substituting
z in both rules. As a result, we must substitute in the following rule bodies to replace
d(y,y), e(z). f(z,y).
Note that unification still works in the presence of constants, in which case variables in the body become bound, possibly allowing for further optimisation.
There are now two unified bodies that can replace the original atom. Since both bodies must be considered, two new rules are created to replace the original rule for
b, hence producing the following final program:
b(x) :- c(x,z), b(y), d(y,y), e(z). b(x) :- c(x,z), b(y), f(z,y).
More complex techniques for inlining arise when dealing with negation, records, aggregators, and so on, but they are all centred on removing the relation whilst preserving program equivalence.
Inlining works in all situations, provided the following conditions are met:
- Relations marked as
printsizecannot be inlined, as they are semantically necessary.
- There cannot be a cycle in the precedence graph where every node in the cycle is inlined.
- More specifically, let G be the precedence graph, and let G’ be the subset of G containing only inlined nodes. Then, G’ cannot contain a cycle.
- The restriction is theoretically necessary, as otherwise no ordering for the inlining process can be imposed such that all relations in the cycle are removed.
- The counter argument,
$, cannot be used as an argument or in the rule body of an inlined relation.
- At the moment, relations appearing in aggregators cannot be inlined, though this is only a restriction in practice due to the way certain functors are handled.
The relation qualifier
no_inline directs Soufflé to not inline the marked relation. Note that
no_inline is implied by the
no_magic relation qualifier.
inline-exclude can be used to prevent the given relations from being inlined and overrides any
inline relation qualifiers. Note that
inline-exclude is implied by the
The relation qualifier
override controls whether rules in a relation that is defined in a component, can be overwritten in a sub-component.
The component model of Soufflé is described here.
Choice Domain / Functional-Dependency Constraint
Programmers can impose one or more functional dependency constraints on relations.
With functional dependencies, non-determistic selections are available for use-cases
such as expressing worklist algorithm in Soufflé. Functional dependency
is defined as a relational qualifier using the keyword
choice-domain in a relation
declaration. For the sake of brevity, our syntax omits the co-domain (i.e. the
right hand side of the arrow). Therefore, a choice-domain
D for a relation with
X implicitly defines a functional dependency of
D -> X \ D.
You find more information about choice here.
In the following, we define relation declarations in Soufflé more formally using syntax diagrams and EBNF. The syntax diagrams were produced with Bottlecaps.
Soufflé has pre-defined types such as
float. Used-defined types have a name. If a type has been defined in a component, the type can be still accessed outside the component using a qualified name. More details about the type system can be found here.
type_name ::= "number" | "symbol" | "unsigned" | "float" | IDENT ("." IDENT )*
An attribute binds a name with a type.
attribute ::= IDENT ":" type_name
A relation declaration declares one or more relations. Each relation has a fixed number of attributes. The definition of attributes is followed by relation qualifiers.
relation_decl ::= '.decl' IDENT ( ',' IDENT )* '(' attribute ( ',' attribute )* ')' ( 'override' | 'inline' | 'no_inline' | 'magic' | 'no_magic' | 'brie' | 'btree' | 'eqrel' )* choice_domain
A choice-domain imposes a functional dependency constraint. The functional dependency constraint is expressed by its domain only. A domain can be either a single attribute or a subset of attributes.
choice_domain ::= ( 'choice-domain' ( IDENT | '(' IDENT ( ',' IDENT )* ')' ) ( ',' ( IDENT | '(' IDENT ( ',' IDENT )* ')' ) )* )?
The syntax of Soufflé changed over time. Older code bases can be still used with modern versions of Soufflé. In older versions of Soufflé we used
.decl A(x:number) input .decl B(x:number) output B(x) :- A(x).
for loading and storing facts. However, we have now I/O directives which permit to change the I/O parameters.
.decl A(x:number) .input A .decl B(x:number) .output B B(x) :- A(x).
You can enable the old legacy syntax using the command-line flag
--legacy, but you will receive a warning that this legacy syntax is deprecated.