Mnesors for databases
📝 Original Info
- Title: Mnesors for databases
- ArXiv ID: 0805.2179
- Date: 2009-12-15
- Authors: ** Gilles Champenois (Collège Saint‑André, Saint‑Maur, France) – gilles_champenois@yahoo.fr **
📝 Abstract
We add commutativity to axioms defining mnesors and substitute a bitrop for the lattice. We show that it can be applied to relational database querying: set union, intersection and selection are redifined only from the mnesor addition and the granular multiplication. Union-compatibility is not required.💡 Deep Analysis
📄 Full Content
Mnesors for databases
Gilles CHAMPENOIS
Collège Saint-André, Saint-Maur, France
gilles_champenois@yahoo.fr
ABSTRACT. We add commutativity to axioms defining
mnesors and substitute a bitrop for the lattice. We show
that it can be applied to relational database querying: set
union, intersection and selection are redefined only from
the mnesor addition and the granular multiplication.
Union-compatibility is not required.
“If you tell me you have 50 different ways of representing
data in your system at the logical level, then I’ll tell you that
you have 49 too many.”
Ted Codd (1923-2003)
I. INTRODUCTION
The theory of mnesors is here modified by assuming commutativity. We used for instance to
consider the colomn tuple
Sweden
Germany
⎡
⎣ ⎢
⎤
⎦ ⎥ as an ordered stack, Sweden being older in the stack than
Germany. So
Sweden
Germany
⎡
⎣ ⎢
⎤
⎦ ⎥ was different to
Germany
Sweden
⎡
⎣ ⎢
⎤
⎦ ⎥ . Now by assuming commutativity
( x + y = y + x), the order does not matter, i.e.
Sweden
Germany
⎡
⎣ ⎢
⎤
⎦ ⎥ equals
Germany
Sweden
⎡
⎣ ⎢
⎤
⎦ ⎥ . So we will simply
write
Sweden
Germany
⎧
⎨
⎩
⎫
⎬
⎭
.
Our purpose is to find a mathematical model for information [1][2] similar to abstract vectors.
We first define a structure called a bitrop which plays the role of the field for vectors, and then
we will define semimodules over bitrops. The resulting two-sorted structure forms an interesting
linear algebra because it mixes properties of lattices (boolean for example) with properties of
vectors: the addition of mnesors aggregates information and the external multiplication selects
information.
We first define what we call a bitrop. A bitrop B is a set with two operations, a commutative
addition and a distributive multiplication. Moreover, it has an element τ called the center of B
verifying the next two properties.
x ⊗τ = x
for any x ∈B
(1)
τ ⊕τ = τ
(2)
Two other properties are added. The subset of elements verifying λ ⊕τ = τ is denoted by B
+.
So for any x,y ∈B and λ,µ ∈B
+
there exists α ∈B
+ such that x ⊕y
(
) ⊗α = x (3) absorption property
x ⊗λ = x ⊗µ implies λ = µ
(4) cancellation property
EXAMPLE. The min-plus integers with the minimum as addition (+) and the addition as
multiplication (⊗) form a commutative bitrop.
II. DEFINITION OF A COMMUTATIVE MNESOR SPACE
A mnesor space is a semimodule ( M ) over a commutative bitrop. M possesses an addition
(written +) and an identity element 0. According to vector scalars, bitrop elements are called
granulars. The commutative semimodule M verifies the following properties:
(unital property)
xτ = x
(4)
(mnesor distributivity)
x + y
(
) λ = x λ + y λ
(5)
(associativity of granular multiplication)
xλ
(
)µ = x λ ⊗µ
(
)
(6)
(granular distributivity)
x λ ⊕µ
(
) = xλ + xµ
(7)
The absorption property is added:
For any mnesors x, y , there exists a granular α ∈B
+ such that x + y
(
)α = x
(8)
Idempotence. The addition of mnesors is idempotent.
PROOF. Letting λ = µ = τ in (5) yields xτ + xτ = x τ ⊕τ
(
) = xτ . Thus, x + x = x, for any
x ∈M [by (4)]
Addition ordering. A mnesor x is a prefix of a given mnesor a if we can write x + a = a. The
relation “is a prefix of” is an order relation (since M is a commutative idempotent monoid) called
addition ordering.
Multiplication ordering. “ x is lower than a” iff we can write x = a λ where λ ∈B
+ ( x is said to
belong to the orbit set of a).
PROOF. Reflexivity ( x = xτ),
Antisymmetry ( x = a λ and a = xµ implies
x = xτ = x τ ⊕µ
(
) = xτ + xµ = x + a = aλ + a = a),
Obviously transitivity.
The two orderings are equivalent, that is x = a λ iff x + a = a.
PROOF.
(←) We apply property (8). There exists λ ∈B
+ such that x + a
(
) λ = x . But x + a = a, then,
aλ = x
( →) x + a = aλ + a = aλ + aτ = a λ ⊕τ
(
) = aτ = a
Mnesor intersection. Let be x,y ∈M given. Since the multiplication is commutative, then there
exist λ,µ ∈B
+ such that x λ = yµ.
PROOF. x + y
(
)λ = x and y + x
(
)µ = y . By multiplying by µ and λ, we get
x + y
(
)λ
(
)µ = xµ
and
y + x
(
)µ
(
)λ = yλ . Thus x + y
(
) λ ⊗µ
(
) = xµ = y λ.
If
ʹ′
λ is another granular that verifies x + y
(
) ʹ′
λ = x , then y
ʹ′
λ = yλ = xµ. Thus, y λ is uniquely
defined for each x. x λ = yµ is denoted by the operation x oy (the intersection of x and y).
Note that the intersection is commutative, associative and idempotent.
Lattice. M,+,o
(
) is a lattice.
PROOF. The addition and the multiplication of mnesors are commutative, associative, idempotent.
Absorption
laws
hold:
x + x oy
(
) = x + xµ = xτ + xµ = x τ ⊕µ
(
) = xτ = x
and
x o x + y
(
) = xτ = x.
III. EXAMPLES
Three of the operations of relational algebra can be expressed with mnesor addition and external
multiplication. But here there’s no need for union-compatibility.
Set union. The set union of tables x and y is performed by the addition x + y.
EXAMPLES. The bitrop is the boolean lattice of intergovernmental organization membership.
Sweden
German
Reference
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