msc thesis presentation
DESCRIPTION
Querying for model-driven spreadsheetsTRANSCRIPT
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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
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Problem: Querying Spreadsheets
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Problem: Querying Spreadsheets
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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
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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
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Example5
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Example: Running Data6
Model-Driven spreadsheet representing: orders, clients, and products
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Example: Running Data7
Spreadsheet data instance
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Example: Running Query8
Query: How much have we profited from each client?
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Solution: Google QUERY Function
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Solution: Google QUERY Function
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Denormalization
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Solution: Google QUERY Function
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Google Query:
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Solution: Google QUERY Function
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Denormalization
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Solution: Google QUERY Function
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Google Query:
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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’
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Solution: Envisioned Approach
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Query: How much have we profited from each client?
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Solution: Envisioned Approach
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Model Inference
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Solution: Envisioned Approach
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Model Inference
Spreadsheet data instance
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QuerySheet: Architecture19
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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
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Preliminary Study21
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Preliminary Study22
Min
ut
es
QuerySheet was found to be approx. ~70% faster than Google’s QUERY Function
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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
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Contributions24
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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)
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Conclusion26
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Conclusion27
Spreadsheet querying is more:
Humanized
Understandable
Robust
Productive
More functionality
Automatically deal with problems caused by
querying denormalized data
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Future Work28
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Future Work29
Incremental Denormalization
Graphical Querying Interface
Query/Model/Instance Bidirectionality
Evaluation
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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