CostAnalysis: 1 Cost Analysis Rule-of-Thumb Guidelines As a guide, consider denormalizing if: –redundancy is minimal and update anomalies are not expected.

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CostAnalysis: 1 Cost Analysis Rule-of-Thumb Guidelines As a guide, consider denormalizing if: –redundancy is minimal and update anomalies are not expected (e.g., StreetNr City State  Zip) –replicated objects are large (e.g., images in View) –join frequencies are very high when compared to updates (e.g., approximate cost in Canadian dollars) Using actual application characteristics, estimate space and time requirements for various possibilities and compare costs.

CostAnalysis: 2 Cost Estimation (Space) Case 1: Room(RoomNr, RoomName, NrBeds, Cost) Guest(GuestNr, GuestName, StreetNr, City) Reservation(GuestNr, RoomNr, ArrivalDate, NrDays) vs. Case 2: Room(RoomNr, RoomName, NrBeds, Cost) Reservation(GuestNr, GuestName, StreetNr, City, RoomNr, ArrivalDate, NrDays) vs. Case 3: Guest(GuestNr, GuestName, StreetNr, City) Reservation(GuestNr, RoomNr, ArrivalDate, NrDays, RoomName, NrBeds, Cost) vs. Case 4: Reservation(GuestNr, GuestName, StreetNr, City, RoomNr, ArrivalDate, NrDays, RoomName, NrBeds, Cost) Assume: 5 rooms, 100 reservations, and 80 guests. 5  4 =  4 =  4 =  4 =  7 =  4 =  7 =  10 = 1000

CostAnalysis: 3 Cost Estimation (Time) Case 1: Room(RoomNr, RoomName, NrBeds, Cost) Guest(GuestNr, GuestName, StreetNr, City) Reservation(GuestNr, RoomNr, ArrivalDate, NrDays) vs. Case 2: Room(RoomNr, RoomName, NrBeds, Cost) Reservation(GuestNr, GuestName, StreetNr, City, RoomNr, ArrivalDate, NrDays) Most important queries/updates: 1. (40%) What rooms are available? 2. (30%) Make a reservation. 3. (10%) Change a reservation. 4. (10%) Cancel a reservation. 5. (the rest) Miscellaneous. Assume indexed on primary keys. 1. Case 1 & 2: Using the Reservation table, retrieve reservations that could overlap the requested date and determine room availability. (Case 1 insignificantly better  the only difference is that Case 1 transfers fewer values in its records.) …

CostAnalysis: 4 Semantic Change? Case 1: Room(RoomNr, RoomName, NrBeds, Cost) Guest(GuestNr, GuestName, StreetNr, City) Reservation(GuestNr, RoomNr, ArrivalDate, NrDays) vs. Case 2: Room(RoomNr, RoomName, NrBeds, Cost) Reservation(GuestNr, GuestName, StreetNr, City, RoomNr, ArrivalDate, NrDays) Most important queries/updates: (30%) Make a reservation.... Assume indexed on primary keys. 2. Case 1: Insert tuple in Reservation (1 read & 1 write) and insert tuple in Guest, if necessary, (1 read and (usually) 1 write). Case 2: Insert tuple in Reservation (1 read & 1 write); check duplicate guest information (read file, or add secondary index). (Developer) Do we really need to check duplicate guest information? (Proprietor) Hmmm, maybe not; it doesn’t matter if it is different. (Developer) Does a guest always need the same guest number? (Proprietor) Not really; there are no guest numbers in our manual system. (Developer) Aha! Great, this really lets us save  watch this.

CostAnalysis: 5 Unique GuestNr in Reservation Observe that we have a new set of keys: { {GuestNr}, {RoomNr, ArrivalDate} } And thus a new generated database scheme: Reservation(GuestNr, GuestName, City, Street, RoomNr, ArrivalDate, NrDays) Room(RoomNr, RoomName, NrBeds, Cost)