Querying for Model-Querying for Model-Driven SpreadsheetsDriven Spreadsheets

Rui PereiraProf. João Saraiva(Supervisor)

Prof. Orlando Belo (Co-Supervisor)

University of MinhoUniversity of MinhoDepartment of InformaticsDepartment of Informatics

Problem: Querying Spreadsheets

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Problem: Querying Spreadsheets

3

Spreadsheets are generally used to store

information

Much like database systems

Have no way to query what data they contain

Attempts have been made to replicate

traditional querying systems for spreadsheets

MS-Query

Google QUERY Function

Problem: Querying Spreadsheets

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Highly restrict user’s spreadsheet data

Requires data to be in a tabular format

Requires header to be present (in first row)

Column letters ≠ Column labels

Counter intuitive queries

Data evolution not supported

Example5

Example: Running Data6

Model-Driven spreadsheet representing: orders, clients, and products

Example: Running Data7

Spreadsheet data instance

Example: Running Query8

Query: How much have we profited from each client?

Solution: Google QUERY Function

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Solution: Google QUERY Function

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Denormalization

Solution: Google QUERY Function

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Google Query:

Solution: Google QUERY Function

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Denormalization

Solution: Google QUERY Function

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Google Query:

Solution: Envisioned Approach

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Solution: Envisioned Approach

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Proposed Query: SELECT Client.*, sum(TotalPrice)FROM Client JOIN OrderGROUP BY Client.*LABEL sum(TotalPrice) ‘Profits’

Solution: Envisioned Approach

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Query: How much have we profited from each client?

Solution: Envisioned Approach

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Model Inference

Solution: Envisioned Approach

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Model Inference

Spreadsheet data instance

QuerySheet: Architecture19

QuerySheet: Architecture20

SELECT Pilots.*, Sum(Hours)WHERE Destination = ‘LIS’GROUP BY Pilots.*LABEL Sum(Hours) ‘Total Hours’

=query(A1:F53; “SELECT B, SUM(F) WHERE D = ‘LIS’ GROUP BY B LABEL SUM(F) ‘Total Hours’”

conforms to

conforms to

denormalization

model inference

execution

translation

Preliminary Study21

Preliminary Study22

Min

ut

es

QuerySheet was found to be approx. ~70% faster than Google’s QUERY Function

Preliminary Study23

After each question, students were asked to

choose which system they preferred in

regards to being:

Intuitive

Faster to write

Easier to write

Understandable

Almost all prefered QuerySheet on every aspect

Contributions24

Contributions25

Querying Model-Driven Spreadsheets, Jácome Cunha, João Fernandes, Jorge

Mendes, Rui Pereira, and João Saraiva. In proceedings of the IEEE Symposium on

Visual Languages and Human-Centric Computing (VL/HCC 2013), San Jose, CA,

USA. IEEE Computer Society, September 2013.

QuerySheet: A Bidirectional Query Environment for Model-Driven

Spreadsheets, Orlando Belo, Jácome Cunha, João Fernandes, Jorge Mendes, Rui

Pereira, and João Saraiva. In proceedings of the IEEE Symposium on Visual

Languages and Human-Centric Computing (VL/HCC 2013), San Jose, CA, USA. IEEE

Computer Society, September 2013.

Spreadsheet Querying, Rui Pereira. In proceedings of the 5th International School

on Domain Specific Languages (DSL’2013), Cluj-Napoca, Romania, 2013. (to

appear)

Graphical Querying of Model-Driven Spreadsheet, Jácome Cunha, João Paulo

Fernandes, Rui Pereira, and João Saraiva. In proceedings of the 16th International

Conference on Human-Computer Interaction (HCI2014), Heraklion, Crete, Greece,

June 2014. (submitted extended abstract)

QuerySheet Software Prototype. (Available at ssaapp.di.uminho.pt)

Conclusion26

Conclusion27

Spreadsheet querying is more:

Humanized

Understandable

Robust

Productive

More functionality

Automatically deal with problems caused by

querying denormalized data

Future Work28

Future Work29

Incremental Denormalization

Graphical Querying Interface

Query/Model/Instance Bidirectionality

Evaluation

30

Querying for Model-Querying for Model-Driven SpreadsheetsDriven Spreadsheets

Rui PereiraProf. João Saraiva(Supervisor)

Prof. Orlando Belo (Co-Supervisor)

University of MinhoUniversity of MinhoDepartment of InformaticsDepartment of Informatics