Finding All the Keys

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# Finding All the Keys - PowerPoint PPT Presentation

Finding All the Keys. Computationally, finding all the keys can be done by exhaustive search: Given a table with 6 attributes, the number of all possible combinations of attributes is:.

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Presentation Transcript
Finding All the Keys
• Computationally, finding all the keys can be done by exhaustive search:
• Given a table with 6 attributes, the number of all possible combinations of attributes is:
• Since testing if a set of attributes is a candidate key or not is not difficult, trying out all 63 possibilities is a breeze for a computer

Department of Computer Science and Engineering, HKUST

Slide 1

Heuristics to Reduce the Possibilities
• Of course, students have to do it by hand (in exams)!
• Go back to the example in chap6.ppt: R = (A, B, C, G, H, I)F = A  B A  C CG  H CG  I B  H
• Heuristics can cut down the total combinations from 63 to a few:
• Attributes that no other attributes determine must be part of ANY candidate key (i.e., A and G)
• Attributes that don’t determine any other attributes but are determined by other attributes should not belong to ANY candidate key (i.e., H and I, which does not conflict with our previous conclusion)
• Only 4 possibilities remain: AG, AGB, AGC, AGBC
• Since A->B and A-> C, so AG is the only key for R

Department of Computer Science and Engineering, HKUST

Slide 2

FDs require just Logical Reasoning
• The above deductions are just logical reasoning, which are not unique to database design
• Other “obvious” results can be deduced by reasoning:
• R(A,B) is always in BCNF, regardless of what FDs are given
• Consider all 4 possibilities:
• Case 1: no FDs, R must be in BCNF (since no FD can violate BCNF definition!)
• Case 2: Only A->B, then A is a candidate key, FD does not violate BCNF
• Case 3: Only B->A, then B is a candidate key, FD does not violate BCNF
• Case 4: Both A->B and B->A, both A and B are candidate keys; neither FD violates BCNF
• There are other “interesting” properties that can be proven by reasoning
• In real life, FDs may not be very complicated but knowing why FDs affects data redundancy and updates, how to reason on FDs and how to decompose a table help to get a better database design

Department of Computer Science and Engineering, HKUST

Slide 3

To Normalize or Not to Normalize, That is the Question
• Good practice: All tables must be in 3NF, in BNCF if possible
• Problems with having a lot of tables:
• Computational cost is high (a lot of joins, but can create a physical view)
• Insertion cost COULD BE high, inserting a set of values into the database may cause several tables to be updated (likewise for deletion)
• When NOT to normalize (i.e., use a big table)?
• High retrieval speed is required
• When a table is never updated (e.g., access log for a website), inconsistency and update anomaly due to data redundancy are not concerns
• Each transaction generates a large group of data (e.g., IP address, cookies, time, date, URL, etc., in an access log table), appending all the data into a table is more efficient than updating several tables
• Although a non-normalized table is much bigger than the normalized tables, searching a large table is still much faster than doing joins

Department of Computer Science and Engineering, HKUST

Slide 4