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Source: /website/ROOT/scripts/jaxson/commonsjs SerializertoSource = function(obj) { return opsserialize(obj, { currProcessedObject : null, iterPrototype : null, canProcessFilter: function(property, currObj, propertyIdentifier) { if (thiscurrProcessed != currObj) { GetPrototypeObject(currObj, function(prototype) { thisiterPrototype = prototype; }); thiscurrProcessed = currObj; } if (typeof(iterPrototype) == "object") { for( prototypeIdentifier in iterPrototype) { if (prototypeIdentifier == propertyIdentifier) { return false; } } } return true; } }); } In the implementation of SerializetoSource is a single method call, and it is to opsserialize By default, opsserialize will serialize everything, and that should be avoided To be able to distinguish between an instance property and a property defined by the prototype property, the implementation of canProcessFilter has to figure out what properties are associated with the instance In the canProcessFilter method implementation is a reference to GetPrototypeObject.

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.

Next, enter your computer name (see Figure 13 12). This is the name that will be broadcast to other Windows systems when they browse to see your computer on the network. It should be a unique name that no other computer on the network shares. This is also known in Microsoft Windows networking terminology as the NetBIOS name.

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.

Once you have named your system, the wizard will prompt you for the workgroup to join (see Figure 13 13). This setting is used to connect multiple Windows systems in a group (much like AppleTalk zones from the OS 9 days). Enter the workgroup name, or select the name from the drop-down list of existing workgroups.

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 93 earlier, that two scalar values for example, the integer 2 and the rational number 20 can be regarded as equal even though they re of different data types.