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Finding All the Keys

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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Finding All the Keys

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  1. 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

  2. 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

  3. 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

  4. 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

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