I 1

Francesca Bugiotti
Università Roma Tre
17/12/2009
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Model management
 What is
– A systematic approach to metadata management, which
handles schemas by means of a set of predefined
operators.
 Its goals
– Enhance the productivity of software developers, by
offering them techniques that allow for high-level
specifications and abstraction over recurring tasks
involving the manipulation of schemas.
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Model management
 Model management systems
– Handle schemas and mappings and support a wide
variety of operations on them.
 MIDST
– We propose MIDST[1,2,3], a platform originally conceived
for model-independent schema and data translation, as
the basis to build a model management system.
– The so built model management system aims at being
model-independent and model-aware.
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What model management addresses
 Concrete needs: they are a formalization of concrete
and frequent database maintenance problems
–
–
–
–
data integration over heterogeneous databases
data exchange between independent databases
ETL
wrapper generation for the access to relational
databases from object-oriented applications
– web site generation from databases.
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What model management addresses
 Model management solutions to formalized problems:
- schema integration
- schema evolution
-
forward engineering
round-trip engineering
-…
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Schema integration
S3
S1
S2
map23
S1
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map12
S2
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Forward engineering
V2
V1
map1
S1
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map2
S2
S2
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Round-trip engineering
S2
S1
map1
I1
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map2
I2
I2
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Model management problems solution
 Solutions to model management problems are
given in terms of scripts.
 A script is a set of model management operators
which are executed according to a specific control
flow.
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Operators
 The operators involved in the script specifications are:
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Match
Diff
Merge
Compose
Modelgen
Copy
…
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Match
 Given two schemas S1 and S2, we define
map12 = MATCH(S1,S2)
where MATCH is the operator identifying
correspondences between the two schemas and hence
yielding a possible mapping.
 There are several algorithms implementing MATCH
operators.
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Match
S2
S1
A
B
A
B
C
D
E
B
A
Match(S1,S2) = ?
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Match
S2
S1
A
A
B
C
D
E
B
A
B
Match(S1,S2) = map12
S2
S1
A
B
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A
B
C
D
E
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B
A
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Diff
 Given two schemas S and S1 the difference
diff(S, S1)
is a schema S2 that contains all the schema elements of
S that do not appear in S1.
 It can be interpreted as a set-oriented difference.
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Example
S1
S
A
B
A
B
C
D
E
B
A
Diff(S,S1) = ?
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Example
S1
S
A
B
A
B
C
D
E
B
A
Diff(S,S1) = S2
S2
A
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A
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B
C
D
E
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Merge
 Given S and S1, their merge
merge(S, S1)
is a schema S2 that contains the schema elements that
appear in at least one of S or S1, modulo equivalence.
 It can be interpreted as a set-oriented union.
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Example
S1
S
A
B
A
B
C
D
E
F
A
Merge(S,S1) = ?
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Example
S2
S1
A
B
A
B
C
D
E
F
A
Merge(S1,S2) = S3
S3
A
B
F
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A
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B
C
D
E
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Compose
 Given three schemas: S1, S2, S3 and two mappings,
map12 between S1 and S2 and map23 between S2 and
S3, we define map13 as the composition of map12 and
map23 as the mapping between S1 and S3.
Compose(S1, S2,S3, map12, map23) = map13
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Modelgen
 Given a schema S of a source model M and a target
model M 1 , the translation
modelgen(S, M 1 )
is a schema S1 of M1 that corresponds to S .
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Modelgen
M = ER Model
S
M1 = Relational Model
Modelgen(S,M1) = ?
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Example
S1
S
Modelgen(S,M1) = S1
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Operators
 A major goal is to provide model-independent
operators, which guarantee some kind of model closure
property.
 Here we move from a simplified version of Bernstein’s
solving procedure for the round-trip engineering problem
[4], in order to introduce the needed operators and explain
how they are implemented in a model-independent
fashion.
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Round-trip engineering
 One of the most meaningful model management problems.
 Let us take it as an example to illustrate our approach to model
management problems.
S1
I1
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S2
I2
S1: specification schema
I1: an implementation schema obtained
from S1
I2: a modified version of the
implementation I2
S2: a new specification which corresponds
to I2.
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Round-trip engineering
S1
PCode
Title
Project
(0,N)
(1,1)
Manager
SSN
Name
EID
S1is the specification schema which is
translated into its corresponding
implementation schema I1.
It is a common example where the
specification is expressed in ER and
the implementation is relational.
I1
Project (PCode, Title, MGRSSN*)
Manager (SSN, EID, Name)
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The translation might be performed
using MIDST itself, since it was
conceived as an implementation of
the MODELGEN operator.
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Round-trip engineering
I1
Project (PCode, Title, MGRSSN*)
Manager (SSN, EID, Name)
I2
Project (PCode, Title, MGRID*)
Manager (SSN, EID, Name, Degree)
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I2is the implementation
schema which is a modified
version of I1.
The transformation involves a
change in the key of a
referred relation. The key of
Manager, which is referred
by MGRSSN of Project in I1,
becomes EID in I2.
As a consequence, the column
MGRSSN of Project,
referencing SSN ofManager,
has to reference EID. MGRID
is the version of MGRSSN
modified accordingly.
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Round-trip engineering
I2
Project (PCode, Title, MGRID*)
Manager (SSN, EID, Name, Degree)
S2
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Our goal is to generate S2,
the appropriately revised version of
the specification schema, such that
its corresponding implementation is
I2.
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Operators in scripts
 The solution which has been provided for the round-trip engineering is
based on a set of model management operators: DIFF, MERGE and
MODELGEN.
 DIFF and MERGE have been used to compute the difference and the
union of schemas.
 MODELGEN has been used as a solution to translate the specification
schema into the implementation and to compute the reversed
differences.
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The Round-trip solving script
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Midst and Modelgen
 The platform MIDST was originally conceived as a framework to
perform model-independent schema and data translations.
 MIDST was designed as a model-generic implementation of
MODELGEN.
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Translations
Entity
Relationship
WSM
XSD
Object
Oriented
Object
Relational
XSD
Object
Relational
Relational
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Translations
Entity
Relationship
WSM
XSD
Object
Oriented
Object
Relational
XSD
Object
Relational
Relational
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The metamodel approach
 The constructs in the various model are rather similar:
– Can be classified into a few categories
(“metaconstructs”)
IE: the entity of the ER, the Object of the OO can be
reconduct to the same abstract concept, the “Abstract”
of our supermodel.
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The supermodel
 A model that includes all the meta-constructs (in their
most general forms)
– Each model is subsumed by the supermodel (modulo
construct renaming)
– Each schema for any model is also schema for the
supermodel (modulo construct renaming).
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Translations specification
 Translations can be defined on metaconstructs


And there are standard accepted ways to deal with translation
of metaconstructs
They can be performed within the supermodel
 Each translation from the supermodel SM to a target model
M is also a translation from any other model to M.
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Translation specification
 The Datalog is used to specify the translation
A translation script in our tool is a set of datalog rules.
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Datalog
 Declarative language
 We specify the condition for the insertion
 For every set of construct that matchs the conditions
in B we create a new construct A
A <- B
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Datalog rule example
 We generate a new Abstract for each Aggregation
Abstract(
OID: SK1(oid),
Name: name )

Aggregation(
OID: oid,
Name: name );
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Another rule
We copy only Lexical of Aggregation
Lexical (
OID: SK1(oid),
aggregationOID: SK2(aggOID),
Name:name,
isIdentifier:isId,
isNullable:isN,
isOptional:isO,
type:t)
<Lexical (
OID: oid,
aggregationOID: aggOID,
Name:name,
isIdentifier:isId,
isNullable:isN,
isOptional:isO,
type:t),
Aggregation(
OID:aggOID);
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Approach
 It is possible to apply the same approach to other
model management operators?
 How can we define other operators with respect to our
supermodel?
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Construct characteristics
 Every costruct has:
–
–
–
–
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An identification OID
A name
A set of properties
A set of references
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Construct characteristics
 Every costruct has:
–
–
–
–
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An identification OID
A name
A set of properties
A set of references
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SM_Lexical (
OID: SK1 oid,
aggregationOID: aggOID,
Name:name,
isIdentifier:isId,
isNullable:isN,
isOptional:isO,
type:t
)
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Construct equivalence
 Two constructs are equivalent if they have:
– The same name
– The same set of properties
– And refer to equivalent costructs
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Comparison
 There is a recursive definition of equivalence.
 We can order the construct and start the matching
from the constructs without references.
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Construct characteristics
 Those can be found also
in the rules
–
–
–
–
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An identification OID
A name
A set of properties
A set of references
SM_Lexical (
OID: SK1(oid),
aggregationOID: SK2(aggOID),
Name:name,
isIdentifier:isId,
isNullable:isN,
isOptional:isO,
type:t
)
<SM_Lexical (
OID: oid,
aggregationOID: aggOID,
Name:name,
isIdentifier:isId,
isNullable:isN,
isOptional:isO,
),
SM_Aggregation(
OID:aggOID
);
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Example
 An equivalence comparison may work as follows:
 1.comparison of the aggregations or abstracts without
any references;
 2. comparison of constructs which may refer to them
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Model management operators by examples
An Example of a possible implementation of model
management operators follow.
The adopted language is Datalog.
The tool is MIDST.
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Datalog implementation of equivalence
.
 Fundamental functional block to compare two constructs:
EQUIV_Aggregation [DEST] (
OID1: oid1,
OID2: oid2)
<SM_Aggregation [SOURCE_1] (
OID: oid1,
Name: name),
SM_Aggregation[SOURCE_2] (
OID: oid2,
Name: name );
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Datalog implementation of difference merge
 Fundamental functional block used to implement a SELECTIVE COPY.
SM_Aggregation(
OID: SK(oid),
Name: name )
<SM_Aggregation (
OID: oid,
Name: name ),
!EQUIV_Aggregation (
OID1: oid );
 Used both in difference and in merge.
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Automatic generation
 These operators can be automatically generated by the
MIDST application framework.
 The construct of the supermodel are used to generate
the rules used for the matching.
 The order of the application is important.
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Example
S1
PCode
Title
Project
(0,N)
(1,1)
Manager
SSN
Name
EID
I1
Project (PCode, Title, MGRSSN*)
Manager (SSN, EID, Name)
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Example
I1
Project (PCode, Title, MGRSSN*)
Manager (SSN, EID, Name)
I2
Project (PCode, Title, MGRID*)
Manager (SSN, EID, Name, Degree)
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Example
Step 1 : difference between the implementation schemas.
I1
Project (PCode, Title, MGRSSN*)
Manager (SSN, EID, Name)
1: DIFF(I1,I2)
G2’Project (MGRSSN*)
Manager (SSN, EID)
I2
Project (PCode, Title, MGRID*)
Manager (SSN, EID, Name, Degree)
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The Round-trip solving script
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Example
Step 2 : difference between the implementation schemas.
I1
Project (PCode, Title, MGRSSN*)
Manager (SSN, EID, Name)
G 2’ +
2: DIFF(I2,I1)
Project (MGRID*)
Manager (SSN, EID, Degree)
I2
Project (PCode, Title, MGRID*)
Manager (SSN, EID, Name, Degree)
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The Round-trip solving script
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Example
Step 3-4 : inversion of the two semidifferences.
G2’+
G2’-
Projectstub (MGRID*)
Projectstub (MGRSSN*)
Managerstub (SSN, EID, Degree)
Managerstub (SSN, EID)
3: REVERSE
4: REVERSE
S3’+
S3’Projectstub
(1,1)
(1,1)
(0,N)
(0,N)
Managerstub
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Projectstub
SSN
EID
Degree
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Managerstub
SSN
EID
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The Round-trip solving script
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Example
Step 5 : merge of the initial specification schema with the inverted
positive semidifference.
H
S3’+
S1
Project
PCode
Title
Projectstub
Projectstub
(1,1)
(1,1)
(1,1)
(0,N)
(0,N)
(0,N)
Manager
SSN
EID
Name
Managerstub
SSN
EID
EID
SSN
Degree
Managerstub
PCode
Title
Name
SSN
EID
Degee
5: MERGE
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The Round-trip solving script
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Example
Step 7 : difference between H and the inverted negative semidifference.
H
Projectstub
EID
SSN
S2
S3’PCode
Title
Project
Projectstub
(1,1)
(1,1)
(1,1)
(0,N)
(0,N)
(0,N)
Managerstub
Name
SSN
EID
Degee
Managerstub
SSN
EID
Manager
PCode
Title
SSN
EID
Name
Degree
6: DIFF
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The Round-trip solving script
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Demo
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Properties
 Model independence
– MIDST handles schemas as instances of subsets of the
available metaconstructs.
– The operators are defined as datalog rules declaring
transformations in terms of the supermodel
metaconstructs.
– The operators are defined in such a way that they are
valid for any model by specifying comparisons between
every available construct.
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Properties
 Model closure
– A model management operator (except MODELGEN)
applied to a set of input schemas of a model M yields
output schemas of the same model M.
 Model awareness
– Operators can be defined in such a way that they do not
add metaconstructs which are not present in the source
schemas (model awareness).
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References
 [1] P. Atzeni, P. Cappellari and P.A. Bernstein. Modelgen: Model-
independent schema translation. In ICDE Conference, pages 1111-1112,
2005.
 [2] P. Atzeni, P. Cappellari and G. Gianforme. MIDST: model-
independent schema and data translation. In SIGMOD, pages 1134-1136,
ACM, 2007.
 [3] P. Atzeni, P. Cappellari, R. Torlone, P.A. Bernstein and G.
Gianforme. Model-independent schema translation. In VLDB Journal.
 [4] P.A. Bernstein. Applying model management to classical meta data
problems. In CIDR, pages 209-220, 2003.
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Summary
 Model management
 Operators
 Model generic operators
 Operators in MIDST
 Example
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