Semiring Evaluation

ProvSQL evaluates provenance circuits over arbitrary (m-)semirings. This page explains the semiring interface, walks through two existing implementations, gives a step-by-step guide for adding a new compiled semiring, and discusses the symbolic representation semirings used by tests and tutorials.

Note

This page is about compiled semirings – semirings implemented in C++ and invoked through provenance_evaluate_compiled (via SQL wrappers such as sr_boolean or sr_counting). Compiled semirings are the preferred option when performance matters.

ProvSQL also exposes an SQL-level mechanism, provenance_evaluate, that lets users assemble a semiring directly in SQL by supplying plus, times, monus and delta functions along with a zero and a one element. That path requires no C++ code or recompilation, but is much slower and limited to what the SQL type system can express. It is described in Semiring Evaluation and is not what this page covers.

The `Semiring<V>` Interface

All semirings inherit from the abstract template class semiring::Semiring<V> defined in Semiring.h. The template parameter V is the carrier type (e.g., bool, unsigned, std::string).

Required Methods (Pure Virtual)

Every semiring must override the following pure-virtual methods:

Method	Semantics
`zero()`	Additive identity \(\mathbb{0}\).
`one()`	Multiplicative identity \(\mathbb{1}\).
`plus(vector<V>)`	Additive operation \(v_0 \oplus v_1 \oplus \cdots\). An empty vector should return `zero()`.
`times(vector<V>)`	Multiplicative operation \(v_0 \otimes v_1 \otimes \cdots\). An empty vector should return `one()`.
`monus(x, y)`	M-semiring difference \(x \ominus y\).
`delta(x)`	Delta operator \(\delta(x)\).

zero, one, plus, and times are load-bearing: every evaluator traverses the circuit applying them. monus and delta are only exercised by specific SQL features – EXCEPT / EXCEPT ALL for monus, and GROUP BY with aggregates (without HAVING) for delta. A semiring that does not sensibly implement one of them can throw SemiringException from its override; evaluation will then fail only for queries that actually use the corresponding gate, and all other queries remain evaluable.

Note

The algebraic axioms a new semiring should satisfy are machine-checked in the ProvSQL Lean 4 library. The Provenance.SemiringWithMonus module defines the SemiringWithMonus typeclass and proves the key monus identities – monus_smallest (\(a \ominus b\) is the least \(c\) such that \(a \le b + c\)), monus_self, zero_monus, monus_add, add_monus – plus the characterisation of idempotent m-semirings (idempotent_iff_add_monus, plus_is_join). A contributor adding a new compiled semiring can use that module as a formal reference for what the zero / one / plus / times / monus methods are required to compute – the Lean class is the ground truth, and the C++ overrides should be a faithful implementation of it. The Provenance.Semirings.* namespace already contains verified instances for Bool, Nat (counting), BoolFunc (Boolean formulas), How (the how-provenance universal semiring), Why, Which (lineage), MinMax, Tropical, Lukasiewicz, and Viterbi, each with a proof of the m-semiring axioms and of any extra properties (absorptivity, idempotence, left-distributivity of multiplication over monus) that matter for optimisation.

Optional Methods

The following methods have default implementations that throw SemiringException:

Method	Gate type
`cmp(s1, op, s2)`	`gate_cmp` – comparison of aggregate values.
`semimod(x, s)`	`gate_semimod` – semimodule scalar multiplication (aggregation).
`agg(op, values)`	`gate_agg` – aggregation operator.
`value(string)`	`gate_value` – interpret a literal string as a semiring value.

Overriding these methods is only useful for pseudo-semirings that produce a symbolic representation of the provenance (e.g. the formula semiring renders a cmp gate as a literal string like "x > 5"). A proper semiring does not evaluate cmp gates through these overrides: instead, before the main circuit traversal starts, having_semantics.hpp walks the circuit, finds every cmp gate that compares an aggregate against a constant, and computes its semiring value using the ordinary plus / times / monus operations of the semiring. Each result is injected into the provenance mapping keyed by the cmp gate itself, so the main traversal reaches those gates with a pre-resolved value and treats them like ordinary leaves. The semiring’s cmp / agg / … overrides are therefore never reached on real queries.

Absorptive Semirings

Override absorptive() to return true if \(a \oplus a = a\) for all \(a\) (e.g., Boolean, Why-provenance). The evaluator exploits this flag to enable several optimizations, which can significantly improve performance.

Example: The Boolean Semiring

Boolean (in Boolean.h) is the simplest semiring and a good template. It evaluates provenance to true/false: a tuple is in the result iff at least one derivation exists.

class Boolean : public semiring::Semiring<bool> {
public:
  value_type zero()  const override { return false; }
  value_type one()   const override { return true; }

  value_type plus(const std::vector<value_type> &v) const override {
    return std::any_of(v.begin(), v.end(), [](bool x) { return x; });
  }
  value_type times(const std::vector<value_type> &v) const override {
    return std::all_of(v.begin(), v.end(), [](bool x) { return x; });
  }
  value_type monus(value_type x, value_type y) const override {
    return x & !y;
  }
  value_type delta(value_type x) const override { return x; }

  bool absorptive() const override { return true; }
};

Key observations:

plus = OR (any derivation suffices).
times = AND (all inputs must hold).
monus = x AND NOT y.
delta = identity (Boolean is already normalized).
The semiring is absorptive: true OR true = true.

Example: The Counting Semiring

Counting (in Counting.h) counts the number of distinct derivations of each tuple. Its carrier type is unsigned.

class Counting : public semiring::Semiring<unsigned> {
public:
  value_type zero()  const override { return 0; }
  value_type one()   const override { return 1; }

  value_type plus(const std::vector<value_type> &v) const override {
    return std::accumulate(v.begin(), v.end(), 0);
  }
  value_type times(const std::vector<value_type> &v) const override {
    return std::accumulate(v.begin(), v.end(), 1, std::multiplies<value_type>());
  }
  value_type monus(value_type x, value_type y) const override {
    return x <= y ? 0 : x - y;
  }
  value_type delta(value_type x) const override {
    return x != 0 ? 1 : 0;
  }
};

This semiring is not absorptive (1 + 1 = 2 ≠ 1).

Step-by-Step: Adding a New Semiring

Create the header file in src/semiring/. Name it after the semiring (e.g., MySemiring.h). Implement the class inheriting from semiring::Semiring<V>, inside the semiring namespace.
Register with the compiled evaluator. In provenance_evaluate_compiled.cpp, the function provenance_evaluate_compiled_internal dispatches on a semiring name string and a return-type OID. Add a branch for your semiring:
```
// In the appropriate type branch (VARCHAR, INT, BOOL, etc.):
if (semiring == "mysemiring")
  return pec_...(constants, c, g, inputs, "mysemiring", drop_table);
```
The pec_* helper functions instantiate the C++ semiring class, call GenericCircuit::evaluate<MySemiring>(...), and convert the result to a PostgreSQL Datum.

Create the SQL wrapper function in sql/provsql.common.sql. Follow the pattern of existing compiled semirings:

CREATE OR REPLACE FUNCTION sr_mysemiring(token UUID, token2anot REGCLASS)
  RETURNS <return_type> AS
$$
  SELECT provsql.provenance_evaluate_compiled(token, token2anot, 'mysemiring', NULL::<return_type>);
$$ LANGUAGE SQL;

Add a regression test in test/sql/ with expected output in test/expected/. Follow the pattern of test/sql/sr_boolean.sql.
Document the new semiring in the user guide (doc/source/user/semirings.rst).

Evaluation Dispatch

When a user calls sr_boolean (or any compiled semiring function), the call chain is:

SQL function sr_boolean(token, mapping_table) calls provenance_evaluate_compiled(token, table, 'boolean', NULL::BOOLEAN).
The C++ function provenance_evaluate_compiled extracts the semiring name string and return-type OID, then calls provenance_evaluate_compiled_internal.
The internal function reads the circuit from mmap (via getGenericCircuit), creates a mapping from input gates to their annotations, and dispatches to the appropriate pec_* helper based on return type and semiring name.
The pec_* helper instantiates the semiring class and calls GenericCircuit::evaluate<S>(root, mapping), which performs a post-order DAG traversal applying semiring operations at each gate.

Symbolic Representation Semirings

Some semirings – in particular the formula semiring exposed by sr_formula – do not compute a numeric or boolean value but rather render the provenance as a symbolic expression. The formula semiring’s carrier is std::string and its operations are concatenations: plus joins the children with ⊕, times joins them with ⊗, and so on. The result is a textual rendering of the provenance circuit suitable for inclusion in tests, slides, or tutorials.

Two practical caveats follow from this:

Operand ordering is not deterministic. When plus (or any other commutative gate) walks its children, the order in which they are visited depends on internal traversal order, which can change between runs. Tests that print symbolic representations must therefore normalise the operand order before comparing – typically with a small replace / regexp_replace that rewrites any of the legal orderings to a canonical one. See test/sql/union.sql and test/sql/distinct.sql for examples.

Symbolic semirings are not “real” semirings. They render the structure of the circuit but do not satisfy the semiring axioms in the usual sense (e.g. concatenation of strings is associative but not commutative, idempotent only in trivial cases, etc.). They are meant for human inspection and testing, not for any algorithmic use that depends on the algebraic properties of the result. In particular, optional operations like cmp and agg can be sensibly implemented on a symbolic semiring – by rendering cmp(s1, op, s2) as "s1 op s2" – which is what the formula semiring does, and is the main reason these optional operations exist at all in the Semiring interface. See Optional Methods above for the full story of why real semirings do not need to implement them.