james long 1

8/2/2019 James Long 1

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Guava: Graphical User Interfaces as

Updatable Views

James F. Terwilliger

Portland State University

Graphical User Interfaces areAlready Updatable Views:

Use GUI as a conceptual model, and program tothat conceptual model, with a novel mapping to

physical storage called a channel


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2

Table P_1588:

Data Dictionary:P_1588: Patients from WebRn Application, enteredthrough form Endoscopy Patient

Domain(Detail/Smkh_1670) = {0, 1, 2, 3, 4, X}

0: Non-Smoker 1: Light smoker, 1-4 cigs/day

2: Moderate smoker, 5-8 cigs/day 3: Heavy smoker, 9-12 cigs/day

4: Chimney, 13+ cigs/day X: Data not available

1

DetailP_1588_ID

578a-b440-cdf2-8e21 Smkh_1670

Attr


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Queries: UI and QI

3

Think Query By Example

Show me the Endoscopist and severity of completed Endoscopies

where Bob was the Anesthetist and complications occurred

Graphical User Interfaces as UpdatableViews


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4

G-Tree: A Structure to Represent the UI

Endoscopy

(Entity)

Personnel

(Container)Outcomes

(Container)

Endoscopist

(Attribute)Anesthetist

(Attribute)Procedure

Complete

(Attribute)Severity

(Attribute)Details

(Control)

Endoscopy

Details

(Entity)

Primary

Finding

(Attribute)

Other

Findings

(Attribute)

Anesthesia

Required

(Attribute)

Complications

Occurred

(Attribute)

Post-

Operative

Instructions

(Attribute)

Other

Surgery

Required

(Attribute)

Single-Launch



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5

G-Trees Natural Schema

Endoscopy

(Entity)

Personnel

(Container)Outcomes

(Container)

Endoscopist


(Attribute)

Procedure

Complete

(Attribute)Severity

(Attribute)Details

(Control)

Endoscopy

Details

(Entity)

Primary

Finding

(Attribute)

Other

Findings

(Attribute)

Anesthesia

Required

(Attribute)

Complications

Occurred

(Attribute)

Post-

Operative

Instructions

(Attribute)

Other

Surgery

Required

(Attribute)

Single-Launch

Endoscopy(

ID, Endoscopist,Anesthetist, )

EndoscopyDetails(

ID, PrimaryFinding,OtherFindings, )


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6

G-Trees: Query

Endoscopy

(Entity)

Personnel

(Container)Outcomes

(Container)

Endoscopist


(Attribute)

= BobProcedure

Complete

(Attribute)

= true

Severity

(Attribute)Details

(Control)

Endoscopy

Details

(Entity)

Primary

Finding

(Attribute)

Other

Findings

(Attribute)

Anesthesia

Required

(Attribute)

Complications

Occurred

(Attribute)

= true

Post-

Operative

Instructions

(Attribute)

Other

Surgery

Required

(Attribute)

Single-Launch



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7

G-Trees: Query

Endoscopy

(Entity)

Personnel

(Container)Outcomes

(Container)

Endoscopist

(AttributeAnesthetist

(Attribute)

= BobProcedure

Complete

(Attribute)

= true

Severity

(Attribute)Details

(Control)

Endoscopy

Details

(Entity)

Primary

Finding

(Attribute)

Other

Findings

(Attribute)

Anesthesia

Required

(Attribute)

Complications

Occurred

(Attribute)

= true

Post-

Operative

Instructions

(Attribute)

Other

Surgery

Required

(Attribute)

Single-LaunchEndoscopist, Severity

(Anesthetist=Bob^ProcedureComplete=true(Endoscopy) ComplicationsOccurred=true(EndoscopyDetails))



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What does application middleware do?

8

Physical

Schema

NaturalSchem

a

Queries (QI)


Insert, Update, Delete(UI)Schema Modifications(Design) Horizontal or Vertical

Merging/PartitioningPivoting or unpivoting

Encoding or translation ofvaluesBusiness logic

Physical Design, BusinessLogic

Information preservation

Referential Integrity

Statistics, Histograms


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Graphical Representation

9

T1

T2

T3

T4

T5

HMerge

VPartition

Unpivot

Apply

Unpivot


HMerge


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The Channel

10

Physical

Schema

Horiz.Merge

Vert.Part.

Apply UnpivotHoriz.Merge

Unpivot


NaturalSchem

a

Q,Ins,Up,Del,DDL ,Loop,Error, FK


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Transformations for Physical Design

11

Vertical Partition Vertically partition into two tables with a 1:1 relationship

Vertical Merge Vertically merge two tables with a 1:1 relationship

Horizontal Partition

Horizontally partition based on the value in a column Horizontal Merge

Horizontally merge, and introduce a provenance column

Pivot/Unpivot

Similar to data warehouse operations, moving data to schema(pivot) or schema to data (unpivot)

Apply Apply an invertible function to data in each tuple



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Statements that the Channel Transforms

12

Queries in extended relational algebra

Inserts, updates, and deletes (DML)

Add/rename/drop table, column, domain element (DDL) Element DDL corresponds to changing elements in a drop-

down list

Transformations may also introduce element operations Add/drop foreign key constraints

Loop statements For each tuple t in query Q, do statements S

Error checks If query Q returns a non-empty result, raise an error

Transformations are closed with respect to these

statements Graphical User Interfaces as UpdatableViews


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Operational Processing

13

NaturalSchem

a

Physical

Schema

Transformation O

InsertIns(T,R)

DMLODML (Ins(T,R))

Ins(T, R),Up(T,F,C,R

),Loop(t,Q,S)



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14

Unpivot Transformation: Example

Represents the decision to transform a table into(key, attribute, value) rows

Before: After:

Patient

Patient_ID

SSN

FirstName

LastName

HomePhone

CellPhone

Patient

Patient_ID

Attribute

Value

Unpivot(Patient,Attribute, Value)



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Definition of Unpivot


15


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Generalized Transformations

16

MultiPivot Generalization of Pivot, where there can be multiple

attribute columns and multiple value columns

GVPartition

Generalization of VPartition, where there are arbitrarilymany output tables, and each column can belong to any ofthem

PPartition

Horizontal partition by predicate rather than provenancecolumn, and rows can end up in one to arbitrarily manyoutputs



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Application-Specific Transformations

Adorn Add columns, and specify data to be held in the new columns,

such as environment data

Audit Add start/end timestamps, and ensure that data is deprecated

rather than deleted (temporal database features) Others

Use lookup table (slightly different than function application)

Establish surrogate key

These actions are similar to the transformations forphysical design Transform queries, DML, DDL, FKs

Want to be information preserving, preserve key semantics



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Correspondence Assertions


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Developer directive that establishes a relationship amongthe extents of schema elements The set of staff members is a subset of the set of people.

The value of column X is the same as the value of column Y inthis other table.

Column Equate Marks a column as holding redundant data, and removes it

from the physical database

Table Equate Marks a table as holding redundant data, and removes it from

the physical database

Plays with definition of information preservation


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Channel Transformation: Definition

19

NaturalDB

Physical DB

Transformation O

Transformation ODB(D), where O is expressible inextended relational algebra

Transformation OSchema(S), describing schema

changesGraphical User Interfaces as UpdatableViews


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Transformation Semantics


20

The core, physical design transformations have awell-understood definition in terms of instance-at-a-

time transformation

Oblivious Put

HPartition(Ta, C):

instout

(t) = Cols(Ta)-C

C=t

instin

(Ta)

(for each value t found in the domain of C)


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Definition of Information Preservation

21

A transformation O is a transformation of schema anddata, expressed in extended relational algebra, thatsatisfies the following information preservationproperties: If I pose a query against the natural schema, I will get

back the same result as if the physical schema matchedthe conceptual schema

If I issue an insert, update, or delete against theconceptual schema, then issue a query for data in themodified table, I will get back exactly what I would get if

there were no transformations in the channel If I issue a DDL statement against the conceptual schema,

then issue a query for data in the modified table, I will getback the instance of the table as if there were notransformations in the channel, but with altered schema



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A transformation O is a transformation of schema anddata, expressed in extended relational algebra, thatsatisfies the following information preservationproperties:

OQuery (QT) (ODB (D)) = instin(T)

OQuery(QT) (ODML(Ins(T,R)) (ODB(D))) = instin(T) R

OQuery (QT) (ODML(Up(T,F,C,R)) (ODB(D))) =

NOT F instin(T) CRF instin(T)

OQuery(QT) (ODML(Del(T,F)) (ODB(D))) = NOT F instin(T)

OQuery(QT) (ODDL((T)) (ODB(D))) = (T)(instin(T))Graphical User Interfaces as Updatable

Views


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Sample Proof (Insert through HPartition,

part 1)


23

Show me what is in thecolumns C of table T_a inthe input (natural) schema


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Sample Proof (part 2)


24

Standard relationalequivalence

Use instance-at-a-timesemantics as axiom


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Sample Proof (part 3)


25

Result is whatever was in T_abefore, plus the inserted rows

Q


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A transformation O that cannot be expressed inrelational algebra cannot use the same formulae:

OQuery (QT) (ODB (D)) = instin(T)

OQuery(QT) (ODML(Ins(T,R)) (ODB(D))) = instin(T) R

OQuery (QT) (ODML(Up(T,F,C,R)) (ODB(D))) =

NOT F instin(T) CRF instin(T)

OQuery(QT) (ODML(Del(T,F)) (ODB(D))) = NOT F instin(T)

OQuery(QT) (ODDL((T)) (ODB(D))) = (T)(instin(T))



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Natural Schema:T1.(A,B) References T2.(A,B)

X Y A BT1:

T2:

T3:

T4:

A B C

A B P CAfter Horizontal Merge:

A M N O SAfter Pivot:

Provenance columnchanges key FK nolonger references the

whole key, nor the wholetable

Some key data

shifts to schemainformation partof FK has nothingto point to

We want to respect the keys and foreignkeys that are present in the naturalschema



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Maintain referential integrity through channel operators, and offer the

developer feedback as to efficiency

Tier 1: FK(T1.C1T2.C2) C2 is entire PK for T2

Only one FK allowed for T1.C1

Representable by standard foreign keys

Tier 2: FK(F | T1.C1 G | T2.C2) F and G are conditions on the key elements of tables T1 and T2,

respectively

C2 can be only a part of PK for T2

Can be multiple FKs defined on T1.C1, with OR semantics Representable by triggers (Ins, Up on T1; Up, Del on T2)

Tier 3: Check(Q1Q2) Representable by triggers, but potentially inefficient due to query complexity



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What do we have here? (In large print)

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An application-specific queryinterface, enabled by a new wayto look at data independence via a

channel



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Future Work: Alternative Data Models

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Relational model has a well-understood, standarddata and schema update language (input

statements)

Relational model has well-understood physical

design paradigms (channel transformations) XML supports create and drop, but not alter, in part

due to complex expressive power

Choice, order, grouping, mixed types

Other models to consider, such as RDF, OO Hybrid models

Transformation to translate from one model to another



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XML Channels

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Transformations Promote attribute to element Invert hierarchy

Queries XPath, XQuery

Alter queries using in-place replacement of references to nodes in

each axis DML

Node insert, node delete, replace value

DDL No DDL for XML schema defined

Could introduce some basic atomic changes Change cardinality

Impose order

Could also consider DDL to be a new total schema, plus XQuery

Simultaneous XSLT on schema and data



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This work is supported in part by Collins Medical Trust, by DHHS NIH National Institute of DiabetesDigestive and Kidney Diseases No. 5-R33-DK061778-03 awarded to Oregon Health & ScienceUniversity (OHSU), and by NSF grant No. 0534762.

Graphical User Interfaces as Updatable

Query Interface

Channel

Thanks!

james long 1

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