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CHAPTER 16 TWO REMARKS ON SQL S UNION
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UNION as defined in the SQL standard relies on something called Subclause 9.3, Set operation result data types. I certainly don t want, nor do I need, to explain that subclause in detail here; however, I d like to give a simple example. Consider the tables T3 and T4 shown in Figure 16-2.
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CHAPTER 16 TWO REMARKS ON SQL S UNION
SELECT * FROM T3 UNION SELECT * FROM T4 ; Or the semantically equivalent query: TABLE T3 UNION TABLE T4 ; In accordance with Subclause 9.3 of the standard, then: Columns X and Y in the result of this query are both of type NUMERIC(p,1). All values in those columns are obtained by first implicitly converting ( coercing ) some INTEGER value from either T3 or T4 to type NUMERIC(p,1). The overall result thus consists exclusively of rows that appear in neither T3 nor T4! A very strange kind of union, you might be forgiven for thinking. Note: In order to head off a possible objection here, let me address the question So what would the relational model do in this example In fact, there are two possibilities: Suppose INTEGER and NUMERIC(p,1) have a common supertype; without any serious loss of generality, let that common supertype be NUMERIC(p,1). Then columns X and Y in the result will indeed be of type NUMERIC(p,1), as in SQL, but every row in that result will be a row from T3 or T4 or both. (See the book Databases, Types, and the Relational Model: The Third Manifesto, 3rd edition, Addison-Wesley, 2006, by Hugh Darwen and myself, for further explanation.) Alternatively, suppose INTEGER and NUMERIC(p,1) have no common supertype. Then the union won t be permitted in the first place. It can still effectively be performed by carrying out some explicit data type conversions first, of course.
Duplicate Rows
The SQL definition of UNION also relies on the concept of duplicate rows. (Actually the relational definition does too, in a sense, but the concept of duplicate rows doesn t have the same bizarre meaning in the relational world that it does in SQL.) Here s the pertinent part of the SQL definition (a and b here denote the tables to be unioned ): Let r be a row that is a duplicate of some row in a or some row in b or both. Then the result contains exactly one duplicate of r. Before I go any further, let me make it crystal clear that I m not interested here in UNION ALL ; that is, I m not interested in the case where we want to preserve duplicate rows, somehow, in the result of the union. I m also not interested in the case where the input tables already include duplicate rows, though whether they do or not doesn t really affect the present discussion. Rather, the point is that even UNION DISTINCT does necessarily rely on SQL s concept of duplicate rows. Note: In case you weren t aware of the fact, the SQL standard does allow DISTINCT to be specified in UNION as an explicit alternative to ALL. Also, DISTINCT is the default for UNION, although ALL is the default for SELECT.
CHAPTER 16 TWO REMARKS ON SQL S UNION
So what exactly is it about SQL s concept of duplicate rows that warrants the characterization bizarre Well, the basic point is that two rows r1 and r2 can be distinct meaning, to spell the point out explicitly, that they re not the same row and yet be regarded as duplicates of one another! Several factors contribute to this strange state of affairs: One has to do with nulls (as you might expect), but I certainly don t want to get into that can of worms here. Another has to do with the notion, already touched on in the discussion of Subclause 9.3 earlier, that two scalar values for example, the integer 2 and the rational number 2.0 can be regarded as equal even though they re of different data types. A third has to do with yet another SQL weirdness: namely, the fact that two scalar values of the same type can be distinct and yet be regarded as equal. And this third phenomenon has at least three manifestations in turn: Suppose X and Y are of types CHAR(2) and CHAR(3), respectively, and suppose their current values are PQ and PQ , respectively (note the trailing blank in the latter case). Then those values are certainly distinct, but the comparison X = Y gives TRUE if PAD SPACE applies to the pertinent collation. See the book A Guide to the SQL Standard, 4th edition, Addison-Wesley, 2000, by Hugh Darwen and myself, for further explanation. Suppose X and Y are both of type CHAR(3), and suppose their current values are PQR and pqr , respectively. Then those values are certainly distinct, but the comparison X = Y gives TRUE if the pertinent collation is case-insensitive. Again, see the book A Guide to the SQL Standard, 4th edition, Addison-Wesley, 2000, by Hugh Darwen and myself, for further explanation. In the case of certain user-defined types (the so-called structured types, to be specific), the corresponding = operator is user-defined as well, and there s no requirement that it have the semantics that two values are equal if and only if they re the very same value. (Actually, there s no requirement that an = operator even be defined! Discussion of the implications of that point would take us way beyond the scope of this chapter, however.) As a result of such considerations, again it s possible for the result of a union to include rows that don t appear in either of the operands! (In fact, I might say, perfectly accurately but possibly confusingly, that the result includes rows that don t appear in the union of those operands.) Figure 16-3 gives an example.
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