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Deco Declarative Crowdsourcing Hector Garcia-Molina, Aditya Parameswaran, Hyunjung Park, Alkis Polyzotis, Jennifer Widom Stanford and UCSC Scoop The Stanford.

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Presentation on theme: "Deco Declarative Crowdsourcing Hector Garcia-Molina, Aditya Parameswaran, Hyunjung Park, Alkis Polyzotis, Jennifer Widom Stanford and UCSC Scoop The Stanford."— Presentation transcript:

1 Deco Declarative Crowdsourcing Hector Garcia-Molina, Aditya Parameswaran, Hyunjung Park, Alkis Polyzotis, Jennifer Widom Stanford and UCSC Scoop The Stanford – Santa Cruz Project for Cooperative Computing with Algorithms, Data, and People

2 2 The Big Picture Same as everyone elses… DBMS like thing Declarative queries Web

3 3 The Big Picture Same as everyone elses… DBMS like thing Declarative queries Web WSQ/DSQ [ Goldman & Widom, SIGMOD 2000 ]

4 Primary Focus (distinguishing features?) Theoretical foundations Generality / flexibility Query optimization 4

5 The Deco Data Model Goals for a new data model (shamelessly stolen from myself) 1)Well-defined 2)Understandable 3)Sufficiently expressive (and not more) 4)Similar to existing models 5)Implementable 5

6 6 The Deco Data Model RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

7 Rest of This Presentation 1. Small motivating example 2. Relations and other stuff 3. Mapping from conceptual schema to actual schema 4. Semantics: valid instance (actual to conceptual) Not included in presentation Enough examples, especially data Normal forms (BCNF/4NF) Metadata/annotations Various details… 7 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

8 restaurantratingcuisine Chez Panisse4.9French Chez Panisse4.9California Bytes3.8California o Small Example 8 User view restaurant Chez Panisse Bytes restaurantrating Chez Panisse4.8 Chez Panisse5.0 Chez Panisse4.9 Bytes3.6 Bytes4.0 restaurantcuisine Chez PanisseFrench Chez PanisseCalifornia BytesCalifornia BytesCalifornia Anchor Dependent resolution rule resolution rule fetch rule 1. Fetch 2. Resolve 3. Join fetch rule Bytes Chez Panisse fetch rule French

9 Relations and other stuff 1.Relations 2.Attributes designated as anchor or dependent 3.Resolution rules dealing with uncertainty 4.Fetch rules access methods to externally obtained data 9 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

10 Relations and Attributes R (restaurant, address, rating, cuisine) S (address, city, zip) 10 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

11 Relations and Attributes R (restaurant, address, [rating], [cuisine]) S (address, [city, zip]) [ dependent attribute groups ] 11 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

12 Relations and Attributes R (restaurant, address, [rating], [cuisine]) S (address, [city, zip]) [ dependent attribute groups ] anchor attributes 12 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

13 Resolution Rules R (restaurant, address, [rating], [cuisine]) S (address, [city, zip]) One resolution rule per dependent attribute-group restaurant,address rating (F=avg) restaurant cuisine ( F=dup-elim) address city,zip (F=majority) LHS RHS with (black-box) function F Given LHS values and one or more RHS values, F returns zero or more (new) values for RHS 13 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

14 Fetch Rules R (restaurant, address, [rating], [cuisine]) S (address, [city, zip]) LHS RHS with procedure P Given LHS value, procedure P can obtain RHS values from external source(s) restaurant,address rating restaurant cuisine address city,zip rating restaurant,address cuisine restaurant,address rating,cuisine restaurant,address restaurant,address 14 anchor attributes (subset of) anchor dependent group(s) dependent group(s) anchor anchor attributes (subset of) anchor dependent group(s) dependent group(s) anchor RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

15 Conceptual Schema (end user) R (restaurant, address, rating, cuisine) S (address, city, zip) 15 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system)

16 Actual Schema R (restaurant, address, [rating], [cuisine]) S (address, [city, zip]) restaurant,address rating restaurant cuisine address city,zip One RR per dependent attribute-group Deco tables [decomposed] One for anchor attributes One for each resolution rule 16 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system) A1(restaurant, address) A2(restaurant, address, rating) A3(restaurant, cuisine) A4(address) A5(address, city, zip) A1(restaurant, address) A2(restaurant, address, rating) A3(restaurant, cuisine) A4(address) A5(address, city, zip)

17 Actual Schema R (restaurant, address, [rating], [cuisine]) S (address, [city, zip]) restaurant,address rating restaurant cuisine address city,zip One RR per dependent attribute-group Fetch Rules add tuples Resolution Rules resolve uncertainty (for query result) 17 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system) A1(restaurant, address) A2(restaurant, address, rating) A3(restaurant, cuisine) A4(address) A5(address, city, zip) A1(restaurant, address) A2(restaurant, address, rating) A3(restaurant, cuisine) A4(address) A5(address, city, zip) +

18 Valid Instance of Database 18 RDBMS Actual schema Conceptual schema Schema designer relations and other stuff End user relations automatic (system) Given: Current contents of Deco tables (actual schema) Fetch Rules and Resolution Rules Valid instance (conceptual schema) is any state of relations obtained by: 1. Fetch add tuples to Deco tables by invoking FR procedures 2. Resolve resolve dependent attributes using RR functions 3. Join full outerjoin of Deco tables for each relation

19 restaurantratingcuisine Chez Panisse4.9French Chez Panisse4.9California Bytes3.8California o Small Example 19 User view restaurant Chez Panisse Bytes restaurantrating Chez Panisse4.8 Chez Panisse5.0 Chez Panisse4.9 Bytes3.6 Bytes4.0 restaurantcuisine Chez PanisseFrench Chez PanisseCalifornia BytesCalifornia BytesCalifornia Anchor Dependent resolution rule resolution rule fetch rule 1. Fetch 2. Resolve 3. Join fetch rule Bytes Chez Panisse fetch rule French


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